Typical Child Effects

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D DOMESTIC VIOLENCE DRUG ABUSE DYNAMICAL SYSTEMS DYSLEXIA E EARLY CHILD CARE EDUCATION EARLY INTERVENTION PROGRAMS EATING DISORDERS EDUCATIONAL TECHNOLOGY divorce decree, which outlines for each individual his or her obligations for division of property and assets; support, if indicated; and provisions for children. Sep- arate from legal implications, divorce is a transition that implies logistic and psychological challenges for all involved. Common challenges for adults going through the divorce process are processing grief, restoring self-esteem, managing anger, and easing emotional pain for their children. Common tasks for parents going through the divorce process are devel- oping an identity as a divorced parent, becoming an effective single parent, dealing with their child(ren)’s anger, and establishing a workable co-parenting rela- tionship with their ex-spouse. Divorce is important to educational psychology because it is associated with family and child factors that have an indirect effect on children’s educational outcomes. Thus, this entry focuses on divorce within the context of families with young children. This review ﬁrst provides a brief, recent historical over- view of divorce in the United States. This is followed by highlights of typical child divorce effects, as well as developmentally speciﬁc child divorce effects. Finally, the impact of divorce on the learning environ- ment is presented, with a focus on school-based pro- gramming to support children and families. Historical Overview The divorce rate rose from 0.3 per 1,000 population in 1967 to its highest rate of 5.3 per 1,000 population in 1979. The change in social attitudes related to modern urbanization, including increased education and employment for women combined with smaller numbers of children per household, and the change in legal guidelines that allowed for no-fault divorce pri- marily account for this considerable change. Currently, 51 % of all U.S. marriages end in divorce. Often, children are involved, and more and more families with the youngest children are ﬁnding themselves in the predicament of divorce. For chil- dren who experience the divorce of their parents before age 12, at least two thirds experience it by the time they are 6 years old. Of all children who experi- ence the divorce of their parents before the age of 6, 40 % do so in the ﬁrst year of life, 20 % between 1 and 2years,15 % between2and3years,10 % between 3 and 4 years, and 15 % between4and5years.Thus, divorce is a common occurrence in the lives of infants, preschool, and early school-age children. Speciﬁc to the context of divorcing families with young children, the judicial system has had the task of considering divorce in the context of children’s best interests. This focus dates back to the 19th century, when it was initially legally speciﬁed that children have rights independent of their parents. This assump- tion was the basis for the later ‘‘best interests of the child’’ principle. The term was coined in the 1925 Fin- lay v. Finlay case and places judicial ofﬁcers in a paren- tal role to the family, determining what scenario best suits the needs of a given minor child. During the early 1900s, the realm of parenting responsibility was pre- dominantly determined by gender, with mothers being responsible for nurturance and fathers being responsi- ble for discipline. The general consensus in a divorce proceeding resided in a mother’s parenting role carry- ing greater weight for children’s development than the father’s. As a result, the majority of residence deci- sions placed children with th eir mothers. This earlier approach was mirrored in the 1970s with the Uniform Marriage and Divorce Act, which emphasized the emotional needs of children in the ‘‘tender years’’ as being best served by residing with their mothers. This presumption has been scrutinized for its unconstitution- ality and has gradually been replaced by a case-by-case review among judicial ofﬁce rs applying the best inter- ests of the child principle. Currently, the principle primarily pertains to deci- sions about child residence and parental access. These decisions are established in the form of parenting plans with outlined parenting time responsibility. What remains the same is the aim of the principle, which is to reduce the concept of parental ownership of children and minimize a competitive stance in liti- gation, with resulting judicial decisions articulated based on children’s needs rather than parents’ rights. The basis for understanding what is in children’s best interests has evolved out of collaboration between the legal and mental health professions. Speciﬁcally, between 1973 and 1986, and revised in 1996, the principle encompassed the idea that custody decisions should both safeguard the child’s need for continuity of relationships while reﬂecting the child’s sense of time. Some states used a criterion set forth in Michi- gan as a check against this conceptual deﬁnition of the best interests of the child principle. For the most part, however, states have used case law to guide decisions about child residence and access. Regardless of the availability of identiﬁed criteria or case law used to normalize the best interests of the Divorce 271 child principle, the lack of empirical research has limited its application. Namely, without empirical research as a guide, the application of the best inter- ests of the child principle has been fraught with difﬁ- culty and fodder for individuals involved in residence and access disputes, formerly known as custody disputes, to manipulate its intent for their purposes. In particular, individuals involved in high-conﬂict divorces, often centered on children and assets, express the needs of their children predominantly in terms of their own needs. High-Conflict Divorces Although divorce presents challenges for all children, particular family dynamics associated with high- conﬂict divorces have been shown to inﬂuence child outcomes. How and to what degree of success parents negotiate their continued relationship has been found to have a signiﬁcant impact on young children’s post- divorce adjustment that is quantitatively and qualita- tively different from other divorce factors. Within this renegotiation, the way parents communicate with each other, especially the conﬂict resolution strategies they use, is particularly important. Because of its recipro- cal nature, these communication patterns include both communication behavior and interpretation of verbal and nonverbal cues by the other parent. At the same time, divorce is often considered to be contentious by nature. Although some divorces are amicable, many are not. Thus, it is important to estab- lish what constitutes a type of communication and a level of conﬂict associated with negative postdi- vorce child adjustment. Low levels of conﬂict and high levels of communication optimally meet the best interests of the child principle observed by the legal community for child residence and parental access decisions. The reverse has also been found to be true, where high levels of conﬂict in families with shared parenting responsibility result in poor adjustment out- comes for children. In particular, children of high- conﬂict divorce display behavioral, cognitive, emo- tional, and social problems to a greater degree than do other children from separated or divorced families. Typical Child Effects Typical child effects include feelings of sadness, anger, and fear, which may manifest in behavior changes and/or emotional and behavioral problems. It is common for these problems to become evident in the school setting. Typical in school-age and adoles- cent children is the desire or fantasy for parents to reunite, fear of abandonment by one or both parents, and/or feelings of responsibility for the divorce. Infant/Toddler Age Children express their difﬁculties in the area where they are currently developing. Several developmental theories suggest that infant and toddler-age children experience signiﬁcant effects of divorce. Common behavioral manifestations in infant/toddler-age groups are increased crying; intensity of problems separating from either or both parents; regression to an earlier developmental stage, especially in toileting; and sleep problems. Attachment is considered the most signiﬁcant socio- emotional developmental milestone for the infant/ toddler-age group. According to attachment theory, it is important to build an attachment to a primary care- taker. Thus, the risks associated with divorce for this age group are related to attachment formation. These risks include feelings of loss of contact with the pri- mary attachment ﬁgure, resulting in child depression and regressive behavior, as well as separation and rela- tionship difﬁculties in lat er development. The risks inherent to separation from the primary caretaker for extended periods may affect current development and also threaten the foundational task of attachment for- mation and subsequent developmental tasks. Attach- ment theory assumes that the quality of attachment is closely linked to caretaker sensitivity to the child’s needs. One concept related to this assumption is the notion of the effect of these interactions over time in development of internal working models of attachment. Essentially, relationships with caretakers greatly inﬂu- ence the child’s way of thinking about new people and experiences. Thus, attachme nt quality is considered an important link to later development. School Age The majority of research on divorce effects in chil- dren has been aimed at child adjustment in school-age children. These studies have commonly focused on cognitive effects, such as school performance, and psychological and social functioning, including behavioral problems. At this age, cognitive ability increases, including the ability to take another’s 272 Divorce perspective. More speciﬁcally, the recognition of other people’s feelings and goals, a more sophisti- cated type of reciprocity, is closely intertwined with cognitive ability in perspective taking. As a result, a couple of common behavior manifestations present themselves during this period for school-age children of divorcing parents. School-age children often feel anxious out of concern over loyalty to their divorcing parents. Also common at this age are feelings of anger that come with the lack of control they have over their current situation. The initiation of school-home com- munication and newly presented homework responsi- bilities pose a unique and additional challenge for these children as they frequently move between both parents’ homes. Adolescent Age Adolescent children experience many of the same emotions that younger age groups do, but manifest them in different ways. One of the recognized adoles- cent milestones is the expression of a need for inde- pendence. Within the context of experiencing divorce within their families, adolescents may exhibit an effort to control their situation by demanding and then changing living arrangements with each parent. Because of the tendency toward risk-taking behavior in this age group, this can present challenges in poten- tial negative risk-taking behaviors. School Supports Families embroiled in high-conﬂict divorces as well as typical divorcing families may be overwhelmed with both logistic and psychological challenges asso- ciated with divorce. In this way, school person- nel educated about typical and age-speciﬁc divorce effects can support the detection of divorce effects and aid in intervention. Although all children experi- ence divorce differently and in their own time frame, as has been noted, there are typical divorce effects found in children from divorcing families. These effects include feelings of sadness, anger, and fear, which may manifest in behavior changes and/or emo- tional and behavioral problems, and it is common for such behavior to become evident in the school setting. School supports include adult and peer support and support of home-school communication. Adult sup- port can be provided in the form of school counselors or other trained professionals. These individuals can help children to understand the divorce process and develop coping skills. As divorce becomes a typical social stressor for school-age children, schools are more frequently providing peer-based programs for children from divorcing/divorced families. Facilitated peer support groups have the effect of normalizing the divorce process for children. This can help chil- dren to reestablish a sense of personal control. Addi- tionally, school personnel, including teachers, can support children from divorcing/divorced families in managing home-school communication. This type of support can be provided by way of considering bi- nuclear families’ special needs, such as when children go between two homes, as they pertain to home- school communication. This is a particularly impor- tant support to the child in the early stages of divorce, when levels of interparental conﬂict are typically higher and levels of positive interparental communi- cation are typically lower. Shannon Altenhofen and Zeynep Biringen See also Emotional Development; Family Inﬂuences; Self-Concept; Self-Esteem Further Readings Amato, P. R. (2001). Children of divorce in the 1990s: An update of the Amato and Keith (1991) meta-analysis. Journal of Family Psychology , 15 , 355–370. Amato, P. R., & Keith, B. (1991). Parental divorce and the well being of children: A meta-analysis. Psychological Bulletin , 10 , 26–46. Lewis, J. M., Johnson-Reitz, L., & Wallerstein, J. S. (2004). Communication in divorced and single-parent families. In A. L. Vangelisti (Ed.), Handbook of family communication (pp. 197–214). Mahwah, NJ: Lawrence Erlbaum. Sillars, A., Canary, D. J., & Tafoya, M. (2004). Communication, conﬂict, and the quality of family relationships. In A. L. Vangelisti (Ed.), Handbook of family communication (pp. 413–446). Mahwah, NJ: Lawrence Erlbaum. D OMESTIC V IOLENCE The ways in which domestic violence is deﬁned vary as much as the people who are the perpetrators and victims of domestic violence. Broadly speak- ing, domestic violence can refer to any verbally or Domestic Violence 273 physically aggressive act committed within the con- text of a close interpersonal or familial relationship. This deﬁnition would include violence perpetrated from a husband against a wife, an adult child toward his or her mother, or even aggression between sib- lings. However, domestic violence more commonly refers to physical or psychological aggression com- mitted by an intimate partner such as a husband, wife, girlfriend, or boyfriend against another intimate part- ner. Because of the prevalence of domestic violence in society, professionals are increasingly being con- fronted with the problem in schools, the legal system, and the workplace. Prevalence Estimates of the prevalence of domestic violence vary for a number of reasons. The violent acts that are fre- quently considered domestic violence can range from psychological abuse to se xual abuse. Psychological abuse typically refers to such things as insulting, swear- ing, or yelling at one’s partner; stomping out of a room; saying something to spite one’s partner; calling one’s partner names; destroying something that belongs to one’s partner; or threatening to hit a partner or throw something at him or her. Moderate levels of physical abuse can include actually t hrowing objects, twisting a partner’s arm or hair, pushing, shoving, grabbing, or slapping. Severe physical abuse is normally character- ized by use of a knife or gun, hitting with something that could hurt, choking, slamming against a wall, striking with a closed ﬁst, kicking, or sexually assault- ing a partner. The prevalence of domestic violence generally increases when less severe acts are included in the deﬁnition and decreases when only the most severe forms of domestic violence are included. Preva- lence estimates also can vary because of the people who are sampled. Domestic violence occurs more fre- quentlyincoupleswhoareunsatisﬁedintheirrelation- ship, couples who seek counseling, and among women seeking assistance at domestic violence shelters. Esti- mates also will vary depending on whether they are based on self-reports given over the phone, offered anonymously in a research setting, or based on actual crime statistics. As a result, estimates of the prevalence of domestic violence vary across different groups. About one quarter of women report experiencing some form of physical or sexual violence at the hands of a romantic partner at least once in their lifetime. Probably about 10 % of women will experience some form of severe violence, and women are more likely to be murdered by an intimate partner than by anyone else. Further- more, more than 10 % of women who are married or cohabiting report being physically abused annually, approximately 1 million each year. Of course, domes- tic violence is not only conﬁned to married or coha- biting couples. The majority of high school and college students report being involved in an aggres- sive or violent relationship. Domestic violence also is not only conﬁned to male-female relationships. Domestic violence occurs in heterosexual couples and homosexual couples, and evidence is increasingly suggesting that women also perpetrate domestic vio- lence against men. Although domestic violence is not conﬁned to heterosexual couples where the man is the perpetrator and the woman is the victim, most of the research focuses on these types of relationships. As a result, this discussion also primarily focuses on the male perpetration of domestic violence in heterosex- ual relationships unless expressly noted otherwise. No matter the precise ﬁgures regarding the preva- lence of domestic violence or even the nature of the relationship, it is clear that there are signiﬁcant societal costs associated with domestic violence. A signiﬁcant percentage of emergency room visits by women are the result of domestic violence, and women in abusive relationships are more likely to visit their family physi- cian for a host of physical complaints, many of which are directly related to the abuse. Domestic violence calls are among the most common job-related tasks for law enforcement ofﬁcers across the country. Men who abuse their partners also are more likely to abuse their children and in turn negatively affect their children’s socialization and academic performance. Nonetheless, domestic violence cuts across all occupations, races, and socioeconomic groups. No person is immune from being a victim of domestic violence. Risk Factors Although domestic violence cuts across different groups, there are factors that increase the risk for the perpetration of domestic violence. These risk factors can be grouped into demographic, psychological, and contextual variables. The most relevant demographic factors typically include variables such as age, socio- economic status, and race. In general, the younger the perpetrator of domestic violence is, the lower the risk for committing 274 Domestic Violence domestic violence. These age-related declines are even greater for more severe violence compared to moderate levels of domestic violence. Even though the wealthy, middle class, and poor are all victims and perpetrators of domestic violence, the lower one’s socioeconomic status, the greater the risk for domestic violence. This increased risk is normally related to the additional ﬁnancial and social pressures as well as the reduced social support and education more likely to occur in lower socioeconomic groups. The role of race and ethnicity has a complex relationship as a risk factor for domestic violence. Normally, perpetrators who are African American, Latino/Hispanic, or gener- ally of minority status are at greater risk to perpetrate domestic violence. However, it is important to exam- ine other factors that might be the cause of this rela- tionship. Speciﬁcally, socioeconomic status appears to be related to race and ethnicity and may be the real reason for the increased risk within many minority groups. It is not simply that many minority groups are more likely to perpetrate domestic violence, but that they are more likely to be unemployed, live in poverty, be less educated, and work in lower-status occupations that are all related to a reduced socioeco- nomic status. When socioeconomic status is factored into the equation, race is not related to the perpetra- tion of domestic violence. Another category of risk factors commonly identi- ﬁed for the perpetration of domestic violence is psy- chological risk factors. Obviously, men who are more hostile and angry are more likely to perpetrate domes- tic violence. Surprisingly, though, men who are less assertive are also more likely to be violent. Assertive- ness should not be confused with aggression. Asser- tiveness is the ability to appropriately express your feelings or ideas in a social situation, especially when those feelings or ideas may be met with resistance or are in the form of a request. Men who are more likely to perpetrate domestic violence have difﬁculty expres- sing themselves in an appropriately assertive manner and therefore often resort to violence or aggression out of the resentment they let build up. A lack of self- esteem is often related to poor assertiveness and in turn is also a risk factor for domestic violence perpetration. Another risk factor for domestic violence that will be examined more closely later is the need for power and control. Traditionally, treatment programs for domestic violence perpetrators focus on the need of the perpetra- tor to dominate and control his victim, and violence is one mechanism for him to do so. In addition to these less pathological psychologic al risk factors, there also is a relationship between domestic violence and partic- ular psychological disorders. Depression and other personality disorders, such as borderline personality disorder and antisocial personality disorder, have been consistently linked to domestic violence. An even stronger risk factor for domestic violence is the use and abuse of drugs and alcohol. Evidence suggests that not only are perpetrators of domestic violence more likely to suffer from a substance abuse disorder, but they are more likely to abuse alcohol or drugs immediately prior to the abuse itself. The ﬁnal category of risk factors related to domes- tic violence is the group of factors related to the rela- tionship or the environmental context in general. Overall, it is very clear that perpetrators of domestic violence are more likely to be dissatisﬁed in their romantic relationship and that relationship dissatisfac- tion may be one of those most signiﬁcant risk factors for domestic violence. This dissatisfaction may be evident in more disagreements or bickering or simply an emotional distance between the couple. Another variable that may be somewhat surpris- ingly related to an increase in the severity of domestic violence perpetration is pregnancy. There may be a host of reasons for this risk factor, including additional dependency of the mother on the father, additional stress and ﬁnancial commitments, and inse- curity on the part of the father because of the change in their relationship. Other signiﬁcant risk factors for the perpetration of domestic violence are related to childhood experiences. A child who is the victim of child abuse or witnesses domestic violence between his parents is at greater risk for the perpetration of domestic violence. This relationship is sometimes referred to as the intergenerational transmission of violence. The intergenerational transmission of vio- lence refers to the fact that children who live in abu- sive relationships are more likely to perpetrate abuse as they become adults, enter into their own relation- ships, and thereby expose their children to abuse, which continues the cycle of violence. Risk Assessment Identifying risk factors for domestic violence is important for the assessment, prediction, and preven- tion of domestic violence. The term risk assessment refers to the formal evaluation of the potential risk that a perpetrator of domestic violence poses to Domestic Violence 275 commit future domestic violence. Although risk assessmentsusedtobesatisﬁedwithpredictingthe probability of future domestic violence, they are now concerned with much more than just the likelihood of future violence. Risk assessments also should evaluate other aspects of the future violence, such as the poten- tial timing and severity of the violence. Risk assess- ments should rely on multiple sources to collect this information. It is not sufﬁcient to rely only on the per- petrator for information but instead legal records, wit- nesses to the violence, and mental health records should be consulted. Most importantly, the risk assessment should be victim informed. The victim should be an integral component of any risk assess- ment of the perpetrator because she is likely to have a perspective that no other single person can provide. Finally, risk assessments should focus not only on assessing risk but also on managing it. Risk manage- ment refers to the process by which an attempt is made to reduce or avoid domestic violence. For example, part of the risk management process may be to refer the victim to a domestic violence shelter or encourage the perpetrator to seek psychological treat- ment for his domestic violence problem. Treatment for both the perpetrator and the victim are central to effective risk management. Treatment and Intervention A variety of interventions have been designed to man- age or treat domestic violence. However, no single intervention will prevent all domestic violence or even most violent incidents. The best intervention is one that is multimodal or uses multiple approaches to solving the problem of domestic violence. Accord- ingly, the prevention and cessation of domestic vio- lence can be accomplished only through the use of psychoeducation, community involvement, and the criminal justice system. Psychoeducational Interventions Psychoeducational interve ntions tend to focus on the men as perpetrators or women as victims, or on couples. The more traditional psychoeducational approaches to domestic violence focus on men as per- petrators. Typically, these programs are either feminist oriented or cognitive-behavioral, or a combination of the two. Traditionally, treatment programs have had a feminist orientation that encourages men to examine their adoption of certain pa triarchal messages within society. For example, the feminist model suggests that the cause of domestic violence is the power differential between men and women that modern society supports. The approach argues that men commit domestic vio- lence in an attempt to dominate and control their female partners, as they have grown up in a society that encourages women to adopt a subservient role. The feminist model argues that only through recogni- tion of this role and a rejection of it can domestic vio- lence stop. The cognitive-behavioral model tends to focus on anger control and suggests that men perpetrate domestic violence largely b ecause of certain aggressive supportive thought patterns they exhibit. For example, a perpetrator may think that his wife never listens to him, and that he can either continue to be ignored or become violent so she listens to him. Cognitive- behavioral approaches get perpetrators to identify these errors in their thinking and teach them to replace the thinking errors with more appropriate thoughts that then reduce the likelihood of being aggressive. It is not currently clear that either one of these approaches is superior to the other, but this ﬁnding may be because few batterer programs are strictly feminist based or strictly cognitive-behavioral and instead are a combina- tion of the two. Batterer Typologies and Treatment As greater attention has focused on treatment inter- ventions for men who perpetrate domestic violence, researchers have increasingly concluded that there is no single type of batterer. The batterer literature gen- erally suggests that domestically violent men can be categorized into subgroups based on individual char- acteristics such as personality/pathology and the nature of their past violence. It has been suggested that these typologies could be useful in designing treatments and identifying the causes of domestic vio- lence. For example, scholars have speculated that batterers with antisocial personality disorder and a his- tory of generalized violence will be the least likely type of perpetrator to beneﬁt from existing forms of treatment. Consistent with this speculation is that bat- terers who drop out of treatment are more likely to have drug and alcohol problems, and antisocial or nar- cissistic tendencies. They are also more likely to have committed more severe levels of domestic violence, and their probability of reoffending is elevated. As a result, it is believed that treatment programs for 276 Domestic Violence men that focus on the speciﬁc needs of these different types of batterers are likely to improve treatment out- comes and increase the effectiveness of domestic vio- lence treatment for men. There are also psychoeducat ional programs designed to treat women, both as victims and as perpetrators. Traditional approaches focus on treating women as the victims by addressing issues related to self-esteem, removing any self-blame or guilt they might experience by incorrectly believing that they are the reason for the violence, and increasing their awareness about alterna- tives to the abusive relationship. Many people question why women remain in these v iolent relationships. The reasons are multiple and varied. Women in these relationships are frequently dependent on their partner for ﬁnancial reasons and unable or unclear how to pro- vide for themselves ﬁnancia lly. In addition, the woman may have the added responsibility of being the primary caregiver for the children and may not know where to turn for child care assistance even if she could ﬁnd employment. Perpetrators a lso attempt to isolate their victims away from their friends and family and there- fore make escaping the relationship even more difﬁcult. The psychological and physical abuse also takes a toll on the victims’ self-esteem and belief that there is anything or even anyone outside of the perpetrator for them. Battered Woman Syndrome Lenore Walker originally used the term battered woman syndrome to explain the abusive relationship and the reasons why many women have difﬁculty leaving their batterer. Based on her observations with battered women, Walker believed that the violence occurred in cycles of three stages. During the tension- building stage, the abuse is largely verbal or very mild physical violence. The victim may attempt to appease the abuser and minimize the seriousness of the abuse. The abuse escalates and becomes the most severe dur- ing the acute battering stage. The acute stage is fol- lowed by loving contrition. During this stage, the abuser is profoundly apologetic for his behavior. He may completely change his attitude, shower the vic- tim with attention and gifts, and promise never to be abusive toward her again. Walker believed that women who were repeatedly abused developed learned helplessness , based on the work of Martin Seligman. Seligman demonstrated that if dogs were shocked repeatedly without any way to escape the shocks, they would eventually no longer try to escape even if a way for them to escape the shocks became obvious. Walker believed that the uncontrollable cycle of violence was similar to the inescapable shocks for the dogs. However, besides Walker’s observations, there is very little support for the notion that all or even the majority of women in abusive relationships experience the cycle of violence or learned helplessness. Nonetheless, it remains a popular notion among domestic violence advocates, and bat- tered woman syndrome has been used in court as a defense for women who kill their abusers. Couple Treatment Two more controversial treatment approaches for domestic violence are trea ting couples and treating women as the perpetrators of domestic violence. In couples’ therapy, the partners focus on each of their contributions to the escalation of the violence when a discussion begins in a calm and rational manner. Although research has found this approach to be effec- tive in some instances, there are many reasons it remains controversial. Some argue that by focusing on each partner’s contributions to the violence, it removes responsibility from the real culprit, the perpetrator of the domestic violence, and places blame on the victim, further victimizing her. In addition, some believe that it is inappropriate to treat the perpetrator and the victim together because it encourages the violence and height- ens the risk to the victim because she may say some- thing in therapy that she is later punished for outside of the therapy session. Supporters of the approach reply that couples are not suitable for this intervention if there continues to be physical abuse in the relationship. Interventions that focus on the woman as the per- petrator of domestic violence are also increasingly being used. These treatment approaches typically are cognitive-behavioral in orientation and tend to focus on anger control and other issues, such as trauma, that may be unique to women who perpetrate domestic violence. These approaches obviously conﬂict with the traditional feminist approach to treatment that sug- gests that only men can be the perpetrators because of the power differential that exists in our society. The notion that women perpetrate domestic violence is based on more recent but consistent ﬁndings in the lit- erature that not only do some women perpetrate domestic violence, but also the perpetration rates between men and women may be equal and the Domestic Violence 277 causes of their domestic violence similar. However, critics argue that even if there are equal rates of per- petration of domestic violence, the violence is not equal in any other aspect. Many arguments exist that attempt to explain these equal rates of perpetration. First, critics argue that the equal perpetration rates are based largely on self-report data, and the research tends to suggest that men under- report their violence mor ethanwomen.Italsois argued that the violence typically perpetrated by women tends to be in self-defense. Women who act outinviolencedosobecausetheyarebeingabusedor are about to be abused, and they are attempting to retaliate while they are still physically capable. Another argument is that even if the frequency of the violence is equal, the severity of the violence is not. Men are more likely to perpetrate more severe violence that results in medical attention or greater physical injury because of their greater physical size and strength. Finally, there is a difference between the perpetration of domestic violence and battering. Critics argue that women may be able to perpetrate domestic violence, but they are not able to batte r. Battering is usually dis- tinguished from perpetration in terms of the severity of physical damage, the abilit y to socially and ﬁnancially isolate the victim, and the general difference in the ability to dominate and control the victim. The argu- ment is that men are able to batter women and that the negative effects of batteri ng go beyond physical abuse. Community-Level Interventions In addition to the psychoeducational interventions for men, women, and couples, it is also important to have community involvement. Community involve- ment normally focuses on the use of advocates, shel- ters, and safe homes. Advocates are professionals who may work for organizations such as the YWCA or local domestic violence councils, or as a part of local government such as a prosecutor or police. Advocates typically assist the victims of domestic violence in navigating the system. This process may mean supporting the victim emotionally and encour- aging her that she is doing the correct thing in seeking help for herself and her children, and in leaving her husband. It may mean talking to the victim about the difﬁculties that are likely to occur in ﬁling criminal charges and prosecuting her partner for assault or domestic assault. Advocates also help victims identify the resources available to them in the community for providing basic necessities and protection if they have left their abusers and were ﬁnancially dependent on them. One of those resources may include a safe house. Safe houses are places where women and their children can ﬁnd temporary shelter. They often stay with individual families who are willing to take in women or consist of houses in secret locations so that the batterer cannot ﬁnd the victim. Shelters tend to be more formalized programs that provide shelter and necessities for the victim and sometimes her children. Shelters may also provide psychological counseling and occupational counseling to assist the woman in living independently. Criminal Justice Interventions Another element that is important in preventing domestic violence is the criminal justice system. There are a number of ways in which the criminal justice sys- tem can take an active role in the prevention of domes- tic violence. First, law enforcement ofﬁcers are increasingly being train ed in the de-escalation of domestic violence and some of the subtleties involved in domestically violent relationships. Part of the inves- tigative aspect of domestic violence as a crime is the use of mandatory arrest polices. Mandatory arrest poli- cies are common in many major cities and counties. Mandatory arrest policies req uire an arrest if it appears an act of domestic violence has occurred. These poli- cies were met with initial enthusiasm. It was believed that they would allow for a separation of the perpetra- tor and victim, result in a cooling-off period, give the victim a chance to escape, and encourage the prosecu- tion of the perpetrator. However, research has failed to universally support the use of mandatory arrest poli- cies, and some research suggests that domestic vio- lence increases once the per petrator returns. Other policies that can be implemented by prosecutors and judges are the use of restr aining orders and no-drop policies. Restraining orders require perpetrators to refrain from any contact with the victim and to remain an identiﬁed distance away from the victim. No-drop policies mandate that the prosecution cannot drop the charges against the perpetrator and can even force the victim to participate, even when it frequently occurs that she is unwilling to participate after she has recon- ciled with the perpetrator. Matthew T. Huss See also Aggression; Child Abuse; Learned Helplessness 278 Domestic Violence Further Readings Archer, J. (2002). Sex differences in physically aggressive acts between heterosexual partners: A meta-analytic review. Aggression and Violent Behavior , 7 , 313–351. Babcock, J. C., Green, C. E., & Robie, C. (2004). Does batterers’ treatment work? A meta-analytic review of domestic violence treatment. Clinical Psychology Review , 23 , 1023–1053. Dutton, D. G. (1998). The abusive personality: Violence and control in intimate relationships. New York: Guilford. Holtzworth-Munroe, A., Meehan, J. C., Herron, K., Rehman, U., & Stuart, G. L. (2000). Testing the Holtzworth- Munroe and Stuart typology. Journal of Clinical and Consulting Psychology , 68 , 1000–1019. Holtzworth-Munroe, A., & Stuart, G. L. (1994). Typologies of male batterers: Three subtypes and the differences among them. Psychological Bulletin , 116 , 476–497. Huss, M. T., & Langhinrichsen-Rohling, J. (2000). The identiﬁcation of the psychopathic batterer: Clinical, legal, and policy implications. Aggression and Violent Behavior , 5 , 403–422. Langhinrichsen-Rohling, J. (2005). Top 10 greatest ‘‘hits’’: Important ﬁndings and future directions for intimate partner violence research. Journal of Interpersonal Violence , 20 , 108–118. Langhinrichsen-Rohling, J., Huss, M. T., & Ramsey, S. (2000). The clinical utility of batterer typologies. Journal of Family Violence , 15 , 37–53. Langhinrichsen-Rohling, J., Huss, M. T., & Rohling, M. (2006). Assessing violence in adults. In M. Hersen (Ed.), Clinician’s handbook of adult behavioral assessment (pp. 371–400). New York: Elsevier. Sartin, M., Hansen, D., & Huss, M. T. (2006). Recidivism and treatment response-related characteristics for domestic violence perpetrators. Aggression and Violent Behavior , 11 , 425–440. Straus, M. A., Hamby, S. L., Boney-McCoy, S., & Sugarman, D. B. (1996). The revised Conﬂict Tactics Scales (CTS2): Development and preliminary psychometric data. Journal of Family Issues , 17 , 283–231. D RUG A BUSE The deﬁnition of drug abuse has ﬂuctuated with changes in cultural and legal norms, and there is cur- rently no consensus on a standardized deﬁnition. However, drug abuse generally can be deﬁned as the harmful or risky use of legal or illegal drugs or the use of legal drugs in a manner or amount inconsistent with medical advice. Some organizations such as the American Psychiatric Association (APA) do not refer to the abuse of drugs per se, but rather to the abuse of substances in general. These two terms ( drug abuse and substance abuse ) are often considered synony- mous and are used synonymously in this entry. The abuse of drugs is frequently associated with a myriad of psychosocial issues, including violence, homicide, homelessness, premature death, psychopa- thology, and economic loss. For secondary school- aged and college-aged individuals in particular, drug abuse is also correlated with school failure, criminal activity, accidents, aggressiveness, unsafe sex, unplanned pregnancy, and suicide. Humankind has used alcohol and other drugs in one form or another since the beginning of recorded his- tory. Alcohol was consumed as early as the Paleolithic era, and other drugs such as cocaine, marijuana, and opium have all been used in the past for religious or medical purposes. Even today, the abuse of both legal and illegal drugs is relati vely commonplace despite moral implications and legal repercussions. Drug abuse is both a major public healt h issue and a highly perti- nent matter facing educators today. Given the reliable association between drug abuse and impaired academic performance (among other variables relevant to stu- dents), educators, researcher s, and practitioners of edu- cational psychology need to be acutely aware of the following in order to help maximize the performance and adjustment of individuals in educational settings: the costs of drug abuse, trends in drug abuse, gender differences, theories of drug abuse, risk factors for drug abuse, the diagnosis and assessment of drug abuse, treatment options, and issues in prevention. These topics are addressed in this entry. Costs and Trends of Substance Abuse Economic Costs The economic costs associated with alcohol and other drug abuse are staggering. According to the Ofﬁce of National Drug Control Policy (ONDCP), the overall cost of drug abuse other than alcohol in 2002 in the United States was in excess of $180 billion. The National Institute on Alcohol Abuse and Alcohol- ism (NIAAA) also estimated that, in 1998, the cost related to alcohol abuse alone was also in excess of $180 billion. In both of these cases, the majority of costs were attributed to lost productivity and health care costs. The ONDCP also reported that in the year 2000, Americans spent an estimated $36 billion on Drug Abuse 279 cocaine, $11 billion on marijuana, $10 billion on her- oin, $5.4 billion on methamphetamine, and $2.4 bil- lion on other illegal drugs. Trends in Use and Abuse The Substance Abuse and Mental Health Services Administration (SAMHSA) conducts an annual National Survey on Drug Use and Health (NSDUH) of Americans aged 12 years or older, and this is the primary source of information on the use of illicit drugs, alcohol, and tobacco in the civilian, noninstitu- tionalized population of the United States. According to the results of the 2005 NSDUH, an estimated 19.7 million Americans (or 8.1 % of the population) reported using an illicit drug during the month prior to the survey. The most commonly used illicit drug was marijuana (14.6 million users in the past month), followed by prescription drugs used nonmedically (6.4 million), cocaine (2.4 million), and hallucinogens (1.1 million). Slightly more than 50 % of Americans aged 12 years or older had consumed alcohol within the 30 days prior to the survey, which translates into about 126 million Americans. The prevalence of drug abuse in youth should be of special interest to the educational psychology pro- fessional, considering that the current rate of illicit drug use among youths aged 12 to 17 within the past 30 days is approximately 11 % , that approximately 28 % of individuals between the ages of 12 and 20 drank within the past month, and that nearly 19 % of them engaged in a binge-drinking pattern (deﬁned as at least ﬁve drinks in a day). Researchers at the Uni- versity of Michigan conduct an annual study on drug use trends among 8th-, 10th-, and 12th-grade students called the Monitoring the Future (MTF) study. Each year, the MTF study gathers self-report survey data from approximately 50,000 students to determine drug use rates and attitudes. According to the 2005 MTF study, alcohol is cited as the most commonly abused drug, followed by cigarettes and marijuana. This trend in alcohol abuse is especially troubling, considering that recent National Institutes of Health (NIH) studies have revealed that young people who began using alcohol before age 15 are four times more likely to develop alcohol dependence during their lifetime than those who began drinking at age 21 or later. Moreover, these youth are seven times more likely to report having been in an alcohol-related traf- ﬁc accident during adolescence and adulthood. Nevertheless, in 2006, the MTF study found a 23 % reduction in the number of adolescents using illegal drugs between 2001 and 2006, including decreases in the use of marijuana, methamphetamine, steroids, LSD, and ecstasy. The study also found that alcohol and tobacco use had declined 13 % and 29 % , respec- tively. Conversely, the study also found that prescrip- tion drug abuse among young people had increased substantially during the same 5-year period. For example, past-year use of oxycodone, a prescription opioid, for nonmedical purposes had almost doubled since 2002. This trend has also been observed by sev- eral recent studies in both Canada and the United States, which report that the use of prescription opioids has become the predominant form of illicit opioid use. Although alcohol, tobacco, and marijuana remain the most commonly abused drugs, prescription drug abuse is quickly rising. Gender Differences Based on the results of the 2005 NSDUH, men reported being current drinkers more frequently than women. However, among the 12–17 age group, rates of current alcohol consumption were actually slightly higher for female youth in comparison to male youth (17.2 % vs. 15.9 %, respectively). This ﬁnding is con- sistent with the 2005 MTF study, which found that although males generally have relatively higher rates of heavy drinking than females, this pattern was reversed for 8th-grade and 10th-grade students. In speaking speciﬁcally to alcohol use, women are more likely to be solitary drinkers and to drink in the home. It has also been consistently found that, on average, women tend to start drinking alcohol later in life, to drink alcohol less than men, and to have less adverse consequences related to alcohol use. How- ever, in general, the same amount of alcohol or another drug taken by a man and a woman will have a stronger effect on the woman. The main reason for this is the biological tendency for women to have a higher percentage of body fat and a lower percent- age of body water. Because women have proportion- ally more fat than water, there is less dilution of the drug while it is in the body of a woman. In addition, certain drugs bind selectively to fat cells in the body, which further contributes to their slower metabolism and elimination from the body of a woman. Based on the 2005 NSDUH (as well as the 2005 MTF survey), males age 12 and older were more 280 Drug Abuse likely to report current illegal drug use in comparison to females, particularly with respect to marijuana, whereas rates of using prescription-type drugs for nonmedical purposes were almost equal across gen- der. Among youth between the ages of 12 and 17, rates of illegal drug use were found to be very similar across gender, whereas the other two general trends still prevailed (i.e., male youth report more marijuana use, and abuse of prescription-type medications was approximately equal). According to the National Institute for Drug Abuse (NIDA), although men are more likely than women to ﬁnd themselves in situations where drugs are avail- able, given the opportunity to use drugs for the ﬁrst time, both are equally likely to do so. Men and women are also equally likely to have problems with cocaine, heroin, hallucinogens, tobacco, and inhalants. However, there appears to be gender differences in vulnerability to abusing speciﬁc substances. Women are more likely than men to have problems with seda- tives, hypnotic drugs, and drugs designed to alleviate anxiety, whereas men are more likely to abuse mari- juana and alcohol. Theories of Substance Abuse Although there is still widespread dispute about the cause of drug abuse, several models have gained prominence. The moral, disease, and biological mod- els argue that the cause of drug abuse originates from within the individual, whereas social learning theory, systems theory, and the sociocultural model view the social environment as most inﬂuential. The biopsy- chosocial model combines elements from several of these theories into a single, integrated approach. Individual Theories The moral model argues that drug abuse is a choice, and that individuals are personally and morally respon- sible for the problems that may result from drug abuse. Alternatively, the disease model postulates that drug abuse is a progressive and irr eversible disease with bio- logical origins and perhaps also psychological and spir- itual causes. This model is the foundation of many self-help groups such as Alcoholics Anonymous and Narcotics Anonymous. The biological model, which appears to be endorsed by the National Institute on Drug Abuse (NIDA), posits that drug abuse is largely a result of genetic and physiological processes. NIDA argues that although initial drug use may be voluntary, the ensuing abuse is often driven by neurological changes that affect behavior. Social Theories Social learning theory, ﬁrst proposed by Albert Bandura, when applied to drug abuse presumes that drug abuse results from complex learning, including modeling and other forms of observational learning, and is grounded in the interaction of the individual with his or her environment. In contrast, systems the- ory places greater primacy on familial processes, such as dysfunctional interaction patterns within a family system, that can lead to drug abuse. The sociocultural model proposes that drug abuse is a logical conse- quence of the particular social norms and laws of many subcultures and societies. Integrated Approaches The biopsychosocial model integrates three major domains known to inﬂuence behavior: biological, psy- chological, and social factors. The biopsychosocial model posits that each of these factors contributes in some interactional way to drug abuse. Although this model is more complex than the other major theories, many argue that it more accurately reﬂects the com- plexity of human experience. Another integrated approach developed by James Prochaska, John Norcross, and Carlo DiClemente is the transtheoretical model of change. It is an evi- dence-based model used to guide assessment, treat- ment, and policy, and is discussed in further detail in the diagnosis and assessment section. Risk Factors for Drug Abuse Although research has identiﬁed a number of risk fac- tors for drug abuse, there is no single, reliable predictor of who will abuse drugs and who will not. With this caveat in mind, the Center for Substance Abuse and Prevention, a branch of the Department of Health and Human Services’ SAMHSA, has organized risk factors for drug abuse into three groups: individual factors, fam- ily factors, and environmenta l factors. Individual risk factors include antisocial behavior (such as criminal activity and violence), social isolation, high need for independence, psychopat hology, positive attitudes toward drug use, poor impulse control, and thrill-seeking Drug Abuse 281 personality type. Family factors include parental drug use, poor family relationships, interpersonal conﬂict, and physical or sexual abuse. Environmental factors include peer inﬂuence, rejection or low acceptance, cultural or social norms, poverty, neighborhood disor- ganization, scholastic failure, low scholastic involve- ment, and negative school environment. Awareness of these risk factors can help in the early identiﬁcation of individuals likely to begin abusing or continue abus- ing drugs. Diagnosis and Assessment Diagnosing drug abuse is essential for the provision of treatment services, yet the abuse of drugs is often difﬁcult to assess. Many individuals who abuse drugs are not willing to disclose their habit, may be plagued by feelings of shame, or may fear legal retribution for their disclosure. Moreover, individuals who abuse drugs may deny the seriousness of their problem, both to themselves and to others. In light of these barriers to effective assessment, in the book Where to Start and What to Ask: An Assessment Handbook ,Susan Lukas has suggested that questions such as the follow- ing may be useful in helping determine whether an individual needs a formal assessment for drug abuse: What substances does the individual use? How recently has he or she used them? How much does he or she use? When does he or she use? What happens when he or she uses? Why does he or she use? What effect is the substance having on his or her life? Does he or she feel guilty about his or her use? Has the individual ever tried to cut down or stop using? How did he or she try? Did it work? After these types of questions have been answered, seeking a diagnosis may be useful in determining what type of treatment will be most beneﬁcial. The most widely used and accepted method of diagnostic classiﬁcation in Canada and the United States is the Diagnostic and Statistical Manual of Mental Disor- ders , (Fourth Edition, Text Revision) ( DSM-IV-TR ), published by the American Psychiatric Association. The use of DSM-IV-TR diagnostic terminology is use- ful because it offers standardized, descriptive criteria that can be used to ensure effective clinical communi- cation about drug abuse. According to the DSM-IV-TR , substance abuse is essentially characterized by clinically relevant impair- ment or distress as evidenced by at least one of the following symptoms for a 12-month time frame: (a) repeated failure to fulﬁll major work, school, or home obligations; (b) frequent use in physically haz- ardous circumstances (including driving under the inﬂuence of substances); © persistent substance- related legal troubles; or (d) recurrent use despite ongoing or repetitive social or interpersonal problems caused by or worsened by substance use. Categories of drugs that qualify for a diagnosis of substance abuse, according to the DSM-IV-TR , are alcohol; amphetamines; cannabis; cocaine; hallucinogens; inhalants; opioids; phencyclidine; and the category of drugs comprising sedatives, hypnotics, or anxiolytics (anxiety-reducing drugs). Drugs that do not ﬁt these categories can be classiﬁed as ‘‘other’’ (i.e., abuse of other substances). The DSM-IV-TR further distin- guishes between substance abuse and substance dependence, the latter of which is characterized by at least 12 months of the continued presence of three or more of the following symptoms: (a) drug tolerance; (b) drug withdrawal; © loss of control over use (in terms of amount or duration); (d) sustained desire or repeated unsuccessful attempts to stop or cut down; (e) substance-related preoccupation (e.g., most of one’s time is spent obtaining the substance, using the substance, or recovering from its effects); (f) reducing or eliminating important social, occupational, or rec- reational activities; and (g) continued use despite evi- dence that a physical or psychological problem is caused or aggravated by substance use. The diagnosis of substance dependence is further speciﬁed by the presence or lack of physiological dependence (i.e., evidence of tolerance or withdrawal symptoms). The International Statistical Classiﬁcation of Dis- eases and Related Health Problems, Version 10 (ICD- 10) is a diagnostic system developed by the World Health Organization that is used in many countries outside of Canada and the United States. The ICD-10 deﬁnes harmful substance use (similar to the DSM-IV- TR diagnosis of substance abuse) as a pattern of psy- choactive substance use that results in physical or psy- chological damage to one’s health. Like the diagnosis of substance dependence in the DSM-IV-TR ,theICD- 10 includes criteria for diagnosis of dependence syn- drome to describe drug addiction. Dependence syn- drome is deﬁned as a cluster of behavioral, cognitive, and physiological phenomena that develop after repeated substance use and that typically include (a) a strong desire to take the drug, (b) difﬁculties in controlling usage, © persistent use despite harmful consequences, (d) a prioritizing of drug use over other 282 Drug Abuse activities and commitments, (e) increased drug toler- ance, and (f) possible physical withdrawal symptoms. Many agencies in the United States and elsewhere have implemented Prochaska, Norcross, and DiCle- mente’s transtheoretical model as a method of assess- ment and treatment. It is an integrated, evidence-based model that describes a stage-based pattern of change based on an individual’s readiness to change. Accord- ing to the transtheoretical model, determining what stage of change an individual is in is essential to provid- ing appropriate and effective treatment. The individual who abuses drugs is assessed to determine what stage of change he or she is in, and treatment strategies geared to that particular stage of change are then imple- mented. The stages are as follows: • Precontemplation: The individual does not recognize the need for change and does not have any intention of changing his or her pattern of drug abuse. • Contemplation: The individual is seriously considering making a change. However, the individual does not have speciﬁc plans to stop abusing drugs in the near future. • Preparation: The individual is planning to stop abusing drugs within the next month, but may still be ambivalent about taking action. • Action: The individual has stopped abusing drugs but has done so for less than 6 months. • Maintenance: The individual has stopped abusing drugs for more than 6 months. • Relapse: The individual has returned to abusing drugs. Treatment Treatment Types and Settings Although some individuals who abuse drugs resolve their problem spontaneously without help, for- mal treatment has been shown to be helpful for many individuals. There is evidence that those who receive some type of professional help subsequently reduce their use of substances and show improvement in other areas of functioning. In addition, psychological treatments targeting signiﬁcant life problems also tend to improve substance abuse recovery outcomes. Reli- able evidence has been demonstrated for the effective- ness of a number of treatment approaches, including social skills training, self-control training, brief moti- vational counseling, behavioral marital therapy, stress management training, and community reinforcement approaches. Some evidence of positive effect has also been found for covert sensitization, behavioral con- tracting, the medication disulﬁram (brand name: Antabuse), and antidepressants. Treatment can be implemented in a variety of set- tings, which may include inpatient medical detoxiﬁ- cation and stabilization in acute care facilities, dual- diagnosis hospital inpatien t care, short- and long-term residential treatment, outpati ent full-day treatment, tem- porary transition

bundet

al residenti al treatment (halfway hous- ing), and intensive or noninte nsive outpatient programs. Best Practices Guidelines Both Health Canada and the NIDA have indepen- dently developed a series of research-driven best practices guidelines for drug abuse treatment and rehabilitation. Some highlights of these best practices include the following: • Pharmacotherapies such as methadone and disulﬁ- ram can be effective as supplemental treatments when used in a controlled setting. • Behavioral therapies such as relapse prevention pro- grams, behavioral self-control therapy, and behav- ioral contracting have been shown to be useful when administered either individually or in group settings. • In terms of alcohol abuse, a community reinforce- ment approach has been shown to be effective for those with few social resources and relatively severe use. • Marital therapy and social skills training are both well supported by research. • Stress management interventions have been shown to be useful as part of alcohol treatment programs. • Services should be ﬂexible and individualized, and guidelines for the selection of appropriate services are essential. No single treatment is appropriate for all individuals, and treatment needs will likely change as treatment progresses. • Group therapy is often preferable to individual treat- ment, unless otherwise contraindicated. • Although research generally supports the relative cost-effectiveness of outpatient treatment, some individuals may beneﬁt from both residential and outpatient or day programs. • Effective treatment combines interventions that address the multiple needs of the individual, not just his or her drug use. • Brief interventions of up to eight sessions have been shown to be especially effective for socially stable individuals with low to moderate alcohol dependence, Drug Abuse 283 and are usually as effective as treatments of a longer duration for this group of individuals. • Counseling provided by competent therapists with strong interpersonal skills is related to positive outcomes. • The majority of those who have drug abuse pro- blems do not seek help; therefore, more effort is required to increase awareness of specialized ser- vices to the general public as well as to health ser- vice providers. It is expected that widespread application of these guidelines in drug abuse treatment will contribute to increased positive outcomes for substance-abusing individuals seeking support. Prevention Many people believe efforts at preventing drug abuse are vastly underfunded in comparison to the funds put toward treatment. Prevention in the context of drug abuse refers to the avoidance or mitigation of drug abuse and problems associ ated with drug use. Drug abuse prevention can involve primary, secondary, or tertiary prevention. The goal of primary prevention is to prevent drug use or abuse from occurring in the ﬁrst place. Early education campaigns that encourage chil- dren to ‘‘just say no’’ would be an example of a primary prevention strategy. Secondary prevention involves interventions applied to those who are already in the early stages of using or abusing drugs in order to pre- vent the development of additional problems. An example of secondary prevention would be mandated alcohol education classes for those convicted of driving under the inﬂuence. Tertiary prevention involves reduc- ing or stopping further dete rioration among those with an established history of drug abuse. Harm reduction strategies designed to reduce harmful effects for those who continue to abuse drugs are seen as tertiary pre- vention strategies. An example of a harm reduction strategy is safe injection sites, such as those in Vancou- ver, British Columbia, Canada, that permit individuals to inject self-obtained illeg al drugs in a setting staffed by medical professionals in an effort to prevent over- doses and the spread of communicable diseases. Three major models of drug abuse prevention have emerged over the years, each with its own underlying philosophy and subsequent suggestions for prevention policies. The sociocultural model argues that social norms are the key factor in promoting the abuse of drugs. An example of the sociocultural model of pre- vention is social-norm education (as provided by many college health centers and college counseling centers), which seeks to counter common misperceptions about typical levels and patterns of drug usage. The con- sumption model argues that the prevalence of drug abuse is a direct function of the average levels of con- sumption in a given culture (e.g., the more the indivi- duals in a culture drink, the more individuals in that culture who will abuse alcohol) and seeks to minimize the negative consequences of drug use through the implementation of restrictions. Higher taxes and age minimums for legal alcohol consumption would fall within the consumption model of prevention. The pro- scriptive model goes one step further and argues that if the availability of drugs (pa rticularly alcohol) is com- pletely prohibited, those who continue to abuse drugs can be regarded as bad or immoral. Therefore, the pro- scriptive model of prevention advocates for prohibition of availability and complete abstinence. The American Alcohol Prohibition Era (1921 to 1932) is an example of the proscriptive model at work. In the past, several mass media campaigns have been aimed at youth and young adults in an effort to reduce drug abuse. Although these campaigns have been shown to increase public awareness and knowl- edge about drugs, their effectiveness at actually reduc- ing drug use and abuse has not been consistently demonstrated. A recent prevention strategy that has shown promise is resistance skills training, which helps youth develop their probl em-solving and decision- making skills. It also seeks to help youth develop cognitive skills for resisting media-based drug use mes- sages, increase self-awareness and self-esteem, learn nondrug coping strategies, and develop interpersonal communication and assertiveness skills. The most widely used program of thi s kind in the United States is the Drug Abuse Resistance Education (DARE) pro- gram. Unfortunately, research on its effectiveness has yielded mixed results. Robinder P. Bedi and Carlton T. Duff See also Diagnostic and Statistical Manual of Mental Disorders Further Readings American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed., Text rev.). Washington, DC: Author. 284 Drug Abuse Johnston, L. D., O’Malley, P. M., Bachman, J. G., & Schulenberg, J. E. (2006). Monitoring the future national results on adolescent drug use: Overview of key ﬁndings , 2005 (NIH Pub. No. 06–5882). Bethesda, MD: National Institute on Drug Abuse. Johnston, L. D., O’Malley, P. M., Bachman, J. G. & Schulenberg, J. E. (2006, December 21). Teen drug use continues down in 2006, particularly among older teens; but use of prescription-type drugs remains high. Retrieved January 14, 2007, from http://www.monitoringthefuture.org Lukas, S. (1993). Where to start and what to ask: An assessment handbook. New York: Norton. McLaughlin, T. F., & Vacha, E. F. (1993). Substance abuse prevention in the schools: Roles for the school counselor. Elementary School Guidance & Counseling, 28, 124–132. Migneault, J. P., Adams, T. B., & Read, J. P. (2005). Application of the transtheoretical model to substance abuse: Historical development and future directions. Drug and Alcohol Review , 24 , 437–448. Rubin, E. (2003). Integration of theory, research, and practice: A clinician’s perspective. In F. Rotgers, J. Morgenstern, & S. T. Walters (Eds.), Treating substance abuse: Theory and technique (2nd ed., pp. 343–363). New York: Guilford. Schydlower, M., Anglin, T. M., Fuller, P. G., Jr., Heyman, R. B., Jacobs, E. A., et al. (1995). The role of schools in combatting substance abuse. Pediatrics , 95 , 784–785. Terry-McElrath, Y. M., Johnston, L. D., O’Malley, P. M., & Yamaguchi, R. (2005). Substance abuse counseling services in secondary schools: A national study of schools and students, 1999–2003. Journal of School Health , 75 , 334–341. Thather, D. L., & Clark, D. B. (2006). Adolescent alcohol abuse and dependence: Development, diagnosis, treatment and outcomes. Current Psychiatry Reviews , 2 , 159–177. Tolan, P., Szapocznik, J., & Sambrano, S. (Eds.). (2007). Preventing youth substance abuse: Science-based programs for children and adolescents. Washington, DC: American Psychological Association. Vega, R. R., & Seligman, L. (2005). Diverse drug abusing populations. In R. H. Coombs (Ed.), Addiction counseling review (pp. 129–148). Mahwah, NJ: Lawrence Erlbaum. Web Sites Center for Substance Abuse Prevention: http://prevention.samhsa.gov/ Higher Education Center for Alcohol and Other Drug Abuse and Violence Prevention: http://www.higheredcenter.org Ofﬁce of Safe and Drug-Free Schools: http://www.ed.gov/about/ofﬁces/list/osdfs/ D YNAMICAL S YSTEMS Educational psychology focuses on theories of learn- ing that ultimately affect how students are taught. Behavioral learning theories inﬂuenced the teaching/ learning process for more than 50 years. In the 1960s, the information-processing approach brought the mind back into the learning process. The current emphasis on constructivism integrates the views of Jean Piaget, Lev Vygotsky, and cognitive p sychology. Additionally, recent scientiﬁc advances have allowed researchers to shift attention to biological processes in cognition. The problem is that these theories do not provide an inte- grated approach to understandi ng principles responsible for differences among students in cognitive develop- ment and learning ability. Dynamic systems theory offers a unifying theoretical framework to explain the wider context in which learning takes place and the processes involved in individual learning. Dynamic (or dynamical) systems theory is part of a paradigm shift involving the acceptance of chaos and complexity as theoretical frameworks in physics, biology, chemistry, engineering, ecology, and psy- chology. Its concepts can be applied to any systems that change over time. It emphasizes the complexity of learning and the students themselves. It recognizes the importance of context in change. It connects the physical with the mental. It allows teaching and learn- ing to be connected processes. Dynamical Systems Are Self-Organizing Dynamic implies synergistic, changing, and chaotic (i.e., underlying order that appears random). System denotes an assemblage of interacting components whose essential properties arise from the relationships between its parts. Students, teachers, classrooms, schools, and school districts make up dynamical sys- tems in education. Students and teachers are individuals made up of diverse systems—biological, affective, and cognitive. There is also diversity base d on race, ethnicity, gender, disability, and socioecono mic status—other systems that are an integral part of students and teachers. All of these systems contribute to individual differences in rate of learning, level of thinking, memory, and moti- vation. Pedagogically, teachers need to be aware of the dynamic complexity of their students and themselves Dynamical Systems 285 in order to more effectively understand what occurs in the teaching-learning proce ss. For example, an African American student who has lived in a rural town will perceive information differently from an African American student who has been raised in an inner-city ghetto. Even though both students are African Ameri- can, the differences in the systems that make up who they are will contribute to diverse outcomes. If both are learning the word ﬁeld, their understanding of the meaning of this word will reﬂect their different experi- ences. The same teaching strategy may not work for both of them. For one, a trip to a ﬁeld might be neces- sary whereas the other will have experience with ﬁelds and can easily make a connection. A view of students as dynamic systems emphasizes the individuality and complexity of all students. Each dynamic system, in addition to being ﬂuid and integrative, exists in a state space , which is an abstract construct depicting the range of behavior open to a sys- tem and constrained by the degrees of freedom avail- able to the elemental components of the system. Each student has his or her own state space or possible beha- viors. For example, a student whose family speaks Spanish at home is going to be constrained by English being a second language. His or her state space will be different from that of a student for whom English is a primary language. In order to be effective, a teacher needs to be sensitive to the different state spaces of his or her students. Some students may be incapable of car- rying out certain behaviors because of the limits of their state space. The student with Spanish as the primary language may be incapable of understanding certain English idioms until he or she has learned other words ﬁrst and changed his or her state space through self- organization. Where a system is located in state space is often determined through self-organization, which occurs whenasystemisattractedtoapreferredstateof being out of many potential states. The individual components of a system emerge into new patterns (states of being) without anyone or anything directing this change. Self-organization emerges from the con- ﬂuence of components within the system. In order for self-organization to occur, the system must be com- plex and open to changes in the environment. Self-organizing, nonlinear dynamic systems tend to migrate toward certain conditions or behaviors that are called attractors. Attractors have varying degrees of stability. Some are easily changed, such as the heart rate when exercising. Others are not easily changed, such as the stomach producing acid in response to food. An attractor state for a student might be his or her read- ing level, which may be stable for a long period of time. Systems will remain in a certain state space until a perturbation pushes the system or increases the sys- tem’s attraction to another state. Perturbation is a dis- turbance to the system. When disturbed, a system may move away from its present attractor and toward a new attractor, resulting in a phase shift. A phase shift is a new form that emerges from the loss of sta- bility of the existing forms. For example, the student whose reading level has been stable for a time period might change to a higher level because of an interest in a more difﬁcult book. The resulting phase shift might be observed as the student begins reading chap- ter books instead of picture books. There has been a phase shift in reading levels. From a dynamic systems approach, learning is a self-organizational process on the part of the indi- vidual. The student undergoes phase shifts (transi- tions) in which the cognitive system self-organizes and new patterns of understanding emerge. Students pass from one organized state of the system to another. Along with the cognitive system undergoing change, neuronal networks are strengthened. As these systems change, they affect the other systems that make up the individual student. Phase shifts can also be facilitated by a control parameter. A control parameter is a variable outside the system to which the system is sensitive and that moves the system through different states. Teachers use control parameters to perturb the attractor states of the students. In pedagogy, a control parameter is the teaching method. Some teaching methods are more successful than others. If successful, self-organi- zation (learning) occurs. If there is no immediate self- organization, then the control parameter perturbation may disturb the system so that at some later point in time, self-organization may occur. For example, if a teacher is focusing on addition in an elementary classroom, he or she will use methods to bring about an understanding of addition. When a student understands what addition is, he or she undergoes a transition. Not only has his or her cogni- tive system changed, but biologically, there are changes in the brain; emotionally, the student might feel satisfaction and pride about mastering something in school; and environmentally, the student might be able to use addition in new aspects of his or her life, such as shopping with parents. The student, as 286 Dynamical Systems a dynamic system, has self-organized and is no longer the individual he or she was prior to the new learning. One truth about learning is that it evolves over time. Therefore, learning does not occur in every student each time a topic is covered in class. What often occurs is a perturbation of the attractor state. There can be many small perturbations without a change in the cognitive system. It is when the system (student) self-organizes that learning takes place. For example, a teacher may introduce addition to students in a number of different ways—direct instruc tion, small group activities, indi- vidual worksheets. The actual comprehension of what addition means will occur in individual ways. Some students may understand addition from the ﬁrst activ- ity, and therefore will self-organize, move to a new attractor state in which being able to add is the norm, and be able to demonstrate an understanding of addi- tion. Other students may require all three strategies before meaning is created. Each activity perturbs the attractor state of these students, but no self-organization occurs until all activiti es have been experienced. Dynamical Systems Are Nonlinear Besides self-organizing, dynamic systems are also non- linear , that is, output is not proportional to input. Tea- chers learn early that sometimes the best lesson plans do not bring about the learning that was sought. Pedagogi- cally, there is not always a direct relationship between teaching and learning. Som etimes, a teacher does not have direct control over the speciﬁc learning that goes on, such as in a cooperative learning group, where stu- dents can learn from other students without the teacher’s involvement. Most of the ti me, the teacher has to use a number of strategies to perturb the systems (students) until ﬁnally self-organization (learning) occurs. All Systems Have a History Dynamic systems theory espouses that all systems have a history that affects their states in the present. As the student acts, that action becomes part of his or her dynamical history. This history will then inﬂuence future actions. Fritjof Capra states that living structure is always a record of previous development. The his- tory of a system includes its tendencies and con- straints. Self-organization taking place in the present is constrained by self-organization of the past. The system’s history will affect its present state space, attractors, phase shifts, and control parameters. So, besides viewing students as dynamical sys- tems, teachers must be aware that each of these sys- tems (students) has a history that will affect his or her ability to learn. Some students have a history of doing well in school, understanding academic sub- jects, and having friends and supportive parents. Unless severely perturbed, these students will con- tinue to do well in school throughout their school lives and respond well to teaching strategies. Other students do not have such a positive experience in their pasts. They may have problems being in school, may have difﬁculties learning academic subjects, and do not have supportive parents. These students may be harder to reach and require larger perturbations to their systems before learning can occur. Their histories may interfere with success in school. These are often the students who present the challenge to teachers. Besides the students and te acher being systems with a history, the classroom community, too, is a system that has an ongoing, ever-changing history—a history of interactions within the enclosed walls of the class- room itself. No two days are alike in the classroom; indeed, no two moments in time are alike. The setup of the classroom—temperatur e, luminosity, desk orien- tation, ambient noise, odor s—deﬁnes its state space. Within that broader framework, each member of the classroom community, each student and teacher, is an independent, complex, nonlinear system with a unique state space of his or her own and his or her own unique and constantly changing history. The variability and unpredictability of the classroom environmental system keep it in constant ﬂux. The environment also constrains the degrees of freedom available to individual students and teachers. For example, students learn to raise their hands to speak, speak softly or not at all while working, and get into line in the proper order. All of these constrain the behaviors of the students from what they might be if students did not have certain norms. Some students learn from this history of classroom behavior and automatically apply it in subsequent grades so that by the time the students reach later elementary years, the attractor state for classroom behavior is stabilized. Understanding Dynamical Systems Within the Context of the Whole Because a number of systems make up an individual, all of them, together, provide the essence of the Dynamical Systems 287 individual. Unlike the behaviorist reductionist view, which requires studying parts of the whole and then generalizing across the whole, dynamic systems the- ory purports that the whole is always different from the mere sum of its parts. Therefore, the parts must be studied and understood within the context of the larger whole. This holistic thinking moves the focus of research from objects to relationships. Studying learning in a classroom setting did not begin until the 1960s, yet this is where the majority of children’s aca- demic studies take place. Students are taught within groups of students, yet learning is a very individual activity. It is important for the teacher to know the history of each student in order to understand what attractors are present and what control parameters might facili- tate change. However, this is difﬁcult to do because teachers are involved with groups of students in such a way that time and energy prohibit study of the vari- ous systems that make the student who he or she is. So instead, teachers use a variety of learning techni- ques in order to bring about learning in the most stu- dents possible. Besides the students being made up of different systems, the teacher also is a network of systems with his or her attractor states and state space. This will affect what types of pedagogical practices he or she will use in a classroom setting. For some teachers, teacher-centered strategies are what they are comfort- able using, and despite information to the contrary, they will continue in that attractor state because of its stability. Jane L. Abraham See also Continuity and Discontinuity in Learning; Piaget’s Theory of Cognitive Development Further Readings Capra, F. (1996). The web of life: A new scientiﬁc understanding of living systems. New York: Anchor. Edelman, G. M. (1992). Bright air, brilliant ﬁre: On the matter of the mind. New York: Basic Books. Gagne, E. D. (1985). The cognitive psychology of school learning. Boston: Little, Brown. Gleick, J. (1987). Chaos. New York: Penguin. Kelso, J. A. S. (1995). Dynamic patterns: The self- organization of brain and behavior. Cambridge: MIT Press. Moore, D. S. (2001). The dependent gene: The fallacy of ‘‘nature vs. nurture.’’ New York: Henry Holt. Robertson, R., & Combs, A. (Eds.). (1995). Chaos theory in psychology and the life sciences. Mahwah, NJ: Lawrence Erlbaum. Thelen, E., & Smith, L. B. (1994). A dynamic systems approach to the development of cognition and action. Cambridge: MIT Press. Thelen, E., & Smith, L. B. (1998). Dynamic systems theories. In R. M. Lerner (Ed.), Handbook of child psychology: Vol. 1. Theoretical models of human development (5th ed., pp. 563–634). New York: Wiley. von Glaserfeld, E. (1984). An introduction to radical constructivism. In P. Watzlawick (Ed.), The invented reality (pp. 17–40). New York: Norton. D YSLEXIA Dyslexia is one of several types of learning disabilities that occurs in children who, despite strengths in other academic and cognitive abilities, experience extreme difﬁculty in learning to decode and spell printed words. This problem at the level of the single word impedes their ability to ﬂuently read and comprehend connected text. Importantly, their reading difﬁculties do not stem from lack of educational opportunity, sensory acuity deﬁcits, or socioeconomic disadvan- tage, although educational opportunity and socioeco- nomic status may interact with dyslexia to either reduce or exacerbate its severity. The International Dyslexia Association deﬁnes dyslexia as follows: A speciﬁc learning disability that is neurological in origin. It is characterized by difﬁculties with accu- rate and/or ﬂuent word recognition and by poor spelling and decoding abilities. These difﬁculties typically result from a deﬁcit in the phonological component of language that is often unexpected in relation to other cognitive abilities and the provi- sion of effective classroom instruction. Secondary consequences may include problems in reading comprehension and reduced reading experience that can impede the growth of vocabulary and back- ground knowledge. Estimates suggest that dyslexia occurs in 6 % to 17 % of the school-age population depending on how it is deﬁned. Regardless of prevalence estimates, chil- dren with dyslexia comprise the bulk of children receiving special education services in the United States for students with learning disabilities. Although 288 Dyslexia dyslexia manifests in childhood with the onset of for- mal reading instruction, it has deﬁnable precursors that permit early detection before formal schooling. In the absence of targeted intervention, the deﬁciencies observed in childhood continue to be evident in the same individuals well into adulthood. Dyslexia may also occur concomitantly wit h other conditions, includ- ing other learning disabilities involving mathematics (dyscalculia) and written expression (dysgraphia), oral language disorders, and attention deﬁcit disorder with or without hyperactivity. These co-occurrences are usu- ally comorbid, meaning that the child has more than one problem. Scientiﬁc understanding of dyslexia has dramati- cally increased in the past four decades. It is now widely accepted that dyslexia occurs on a continuum in much the same way as obesity or high blood pres- sure. What this means in practice is that dyslexia is not an all-or-nothing categorical disability. Instead, it occurs in degrees of severity. Establishing the cut point on the continuum at which word reading difﬁ- culties constitute a disability is not well established and accounts for the variability in prevalence esti- mates. Current classiﬁcation schemes vary by state and by program type. In the United States, children can receive services for dyslexia as part of special education under the Learning Disabilities (LD) cate- gory in the Individuals with Disabilities in Education Act (IDEA), where problems with basic reading skills are one of the eight domains in which LD can occur. A few states, such as Texas and Louisiana, also pro- vide dyslexia services outside of special education. In most states, qualiﬁcation for dyslexia services under the LD category would be based on an achievement/ IQ test discrepancy, with a number of discrepancy models in use from state to state. In the recent reauthorization of IDEA, states were also allowed to use response-to-intervention (RTI) as a mechanism for identifying learning disabilities including dyslexia as well as models based on discrepancies in achieve- ment relative to age. Regulations permitting the use of RTI for identiﬁcation are just emerging from different states. Historical Roots and Theories Over the years, a number of other theories and result- ing treatments have gained and lost prominence in the ﬁeld of dyslexia. A few of the most prominent theo- ries are brieﬂy reviewed below. Deficits in Visual Perception Dyslexia was ﬁrst described more than 100 years ago. By 1900, the condition was referred to as congeni- tal word blindness and was believed to be caused by difﬁculty in storing visual impressions of words. Build- ing on the assumption that the underlying causes of observed reading difﬁculties were based in deﬁcits in visual processing, Samuel O rton outlined the ﬁrst fully developed theory of dyslexia, which he called strepho- symbolia (twisted symbols). His theory suggested that children were experiencing d ifﬁculty in establishing hemispheric dominance within the brain, resulting in an inability to suppress mirror image counterparts, which was presumed to cause optic reversibility in visual perception that resulted in seeing symbols as reversed images (e.g., b as d;or was as saw). Although the basic tenets of Orton’s theory have not proved to be correct, they have been hugely inﬂu- ential in driving the focus of subsequent theories and treatments of dyslexia even to the present time. It is from Orton’s theory of dyslexia that the widely held belief that the treatment of dy slexia requires multisen- sory methods of instruction stems. The underlying assumption being that by activating the auditory, tac- tile, and kinesthetic modal ities of learni ng, students are able to compensate for inherent weakness in the visual domain. In fact, the Orton–Gillingham method for teaching reading, or one of many derivatives of this method, is pervasive in the treatment of dyslexia even today. However, empirical support for these methods is mixed. Likewise, there is no indication that the multi- sensory aspects of this inst ruction are actually the salient aspects of the instruction. The content of these programs focuses on teaching alphabetic decoding, and this focus likely accounts for any effects achieved. Interventions that do not actu ally include multisensory aspects but do carefully teach alphabetic decoding have also achieved very positive r esults with this population. The view that dyslexia was caused by dysfunction in the visual perception system dominated the ﬁeld until it was systematically evaluated in the 1970s and 1980s. Outcomes from these studies clearly demonstrated that the visual perception ability of dyslexic and normal readers was not different, a nd that visual perception ability does not predict performance of reading ability. Low-Level Visual Deficits Dyslexia has also been attributed to visual tracking problems assumed to be caused by ocular motor Dyslexia 289 deﬁciencies; visual masking effects associated with deﬁcits in the transient visual system; and scotopic sensitivity syndrome (SSS) involving excess sensitiv- ity of the retina to particular frequencies of light, causing the brain to distort information. Of these theo- ries, SSS currently has the most prominence in prac- tice. The interventions recommended for SSS involve placing colored overlays over text or using tinted lenses designed to selectively ﬁlter out problem fre- quencies and make the text visually stable. The visual tracking theory of dyslexia has long been discredited by well-controlled eye movement studies ﬁnding no differences between poor and normal read- ers. Similarly, the evidence to support the theory of visual masking effects has been weakened by the ﬁnd- ing that signiﬁcant numbers of normal readers have similar transient system deﬁcits. Likewise, independent reviews of the results of interventions based on SSS theory have not found speciﬁc associations of reading, dyslexia, and other disabilities. Perceptual-Motor and Cerebellar Deficits In the 1960s and 1970s, theories commonly attrib- uted the cause of dyslexia to perceptual-motor deﬁ- cits. Although the speciﬁcs of each theory differed, they shared the common belief that a child must have adequate visual-motor functioning as a prerequisite for academic learning, and that motorical treatment was needed to reorganize neurological functioning to allow adequate visual-perceptional ability. The treat- ments aligned with these the ories included such things as having children practice creeping and crawling, walking on balance beams, standing on balance boards, and completing eye-tracking exercises. Although these theories and their accompanying treatments were very popular, they did little to improve the academic out- comes for children and have largely become extinct in practice. Despite these results, there has recently been some resurgence of this approach to treating dyslexia and other learning disabilities, despite the lack of scientiﬁc evidence for effectiveness. This is most apparent in the cerebellar theory of dyslexia proposed by Roder- ick Nicolson, Angela Fawcett, and Paul Dean. The hypothesis is that children with dyslexia fail to autom- atize reading and other cognitive and motor skills mediated by the cerebellum. There is little evidence that supports this hypothesis or the recommended interventions. Low-Level Auditory Deficits Another theory that has attracted attention more recently is put forth by Paula Tallal, who theorized that children with dyslexia are fundamentally impaired in processing acoustic stimuli characterized by spectral parameters that change rapidly in intensity. Although originally based on childre nwithorallanguagedisor- ders, Tallal expanded this hy pothesis to children with dyslexia, suggesting that dyslexia is caused by lower- level auditory problems interfering with the processing of sounds with rapidly changing properties, which in turn impairs speech percepti on and thus the acquisition of phonological awareness and phonological decoding. Early empirical evidence provided support for this the- ory, but more recent investigations have not found spe- ciﬁc associations of these perceptual problems with dyslexia. The treatments that have emerged from this theory, which involve using synthetic speech to slow down the acoustic stimuli, have not been found to have a major impact on reading skills in randomized, con- trolled experiments. Phonological Coding Deficits Currently, the theory that dyslexia is the result of weak phonological coding has accumulated substan- tial and converging scientiﬁc evidence to support it. Phonological coding is the ability to use speech codes to represent words and parts of words. Weakness in this domain results in poor phonemic awareness and letter-to-sound mapping, resulting in poorly speciﬁed phonological representation of words. These coding deﬁcits result in difﬁculty in storing and retrieving words as unitized orthographic representations, and difﬁculty in processing alphabetic information in working memory. The theory suggests that difﬁculties in storage and retrieval impair the child’s ability to form necessary connective bonds between spoken and written words, which in turn impedes the storage of fully speciﬁed representations of word spellings and thus impedes ﬂuency of word recognition. Evidence to support this theory comes from two sources. First, a relation between phonological coding and dyslexia can be inferred because children with dyslexia have consistently been found to perform sig- niﬁcantly below normal readers on different assess- ments of phonological processing, Likewise, a causal link can be inferred because intervention studies directly addressing phonological coding deﬁcits have 290 Dyslexia repeatedly demonstrated positive outcomes on the reading outcomes of children with dyslexia. There is controversy over the exact manifestations and contri- butions of different phonological processing domains, but the link of word reading and phonological proces- sing, and the extrapolation to dyslexia, is widely rec- ognized as a major scientiﬁc discovery. Neurobiological Correlates Dyslexia has always been assumed to be neurobiolo- gically based. However, only recently have the neuro- logical and biological causes of dyslexia been able to be examined directly rather than just inferred. Genetics Studies of the heritability of dyslexia show that there is a strong genetic link for reading and reading disability. For example, a child whose parents had reading problems is eight times more likely to experi- ence a reading problem; 25 % to 60% of parents of children who are dyslexic also experienced signiﬁcant reading difﬁculties; and the rate of concurrent dys- lexia among identical twins is above 80 % , but below 50 % for fraternal twins. The estimates of the genetic contribution ranges from 50 % to 80 % depending on age, schooling, and other sample characteristics. Fur- thermore, recent studies have identiﬁed a constellation of speciﬁc genes involved in dyslexia. Multiple researchers have identiﬁed an area on chromosome 6, and chromosome 15 has been identiﬁed by several researchers. Potential markers on chromosome 1 and 2 have also been reported but not replicated. Even though there is a clear genetic link to dys- lexia, these studies do not indicate that the genetic links are speciﬁc to dyslexia, but instead are linked to reading and the variability in reading skills that char- acterizes any population. In addition, the same body of research demonstrates that the environment plays an important role in determining reading outcomes for individual children. Whether or not signiﬁcant reading problems will develop in a child with a genetic predisposition for dyslexia also depends on what types of reading experiences that child is provided in his or her home and school environment. Even if heritability is strong, the genetic contribution does not mean that the reading problem is immutable to intervention, although more intense and targeted instruction may be needed. Brain Function The evidence that dyslexia is greatly inﬂuenced by environmental factors is supported in recent neuroi- maging studies of brain function in students with and without dyslexia. In these studies, various neuroima- ging techniques, such as positron emission tomogra- phy, functional magnetic resonance imaging, and magnetic source imaging, are used to assess the brain’s response to cognitive challenges. The ﬁndings from studies using these techniques converge to show that tasks requiring reading are associated with increased activation with the basal surface of the tem- poral lobe, the posterior position of the superior, the middle temporal gyri, and the inferior frontal lobe. Magnetic source imaging studies, which allow time sequences within the brain to also be mapped, demon- strate that in normal readers, the occipital areas of the brain that support primary visual processing are acti- vated ﬁrst, followed by regions in the basal temporal areas in both right and left hemispheres. This is fol- lowed by simultaneous activation in three areas of the temporal and parietal areas corresponding to the supe- rior temporal gyrus, Wernicke’s area, and the angular gyrus, often more predominantly in the left hemi- sphere. Students with dyslexia activate the same regions of the brain, but there is often much less left hemisphere activation and differences in the temporal sequences of brain activation. More recently, a series of studies has been con- ducted to determine the impact of carefully designed instruction on phonological coding on the brain acti- vation patterns of children with or at risk for dyslexia. In each of these studies, the brain activation patterns of children at risk for dyslexia (i.e., 5- and 6-year- olds) or identiﬁed as dyslexic (i.e., 7- to 17-year-olds) show predominantly normalizing patterns after well- designed, intense interventions. Importantly, this ﬁnd- ing has been found among both young readers prior to the onset of reading difﬁculties (i.e., intervention in ﬁrst grade) and older children and adults who have experienced serious reading difﬁculties. These studies indicate that the neural systems that mediate word recognition and dyslexia are malleable and responsive to intervention. Effective Treatment Since the early 1990s, a number of studies have care- fully evaluated interventions designed to prevent or Dyslexia 291 remediate dyslexia. From this body of research, we now know much about what constitutes effective intervention for these children. Perhaps the most important ﬁnding is that the needs of children with dyslexia are not unique to only children with dyslexia. The same type of instruction that is effective with these children is also highly effective for other chil- dren who experience reading difﬁculties for other rea- sons, such as economic disadvantage. Likewise, the critical components of this instruction are the same for even normally developing children, although the level of intensity and amount of repetition needed will be greater for children with dyslexia. This critical content includes explicit and strategic instruction to ensure that children develop high levels of phonemic awareness; in-depth knowledge of letter- sound correspondence, including the many spelling variations; acquisition of accurate, quick, and ﬂexible word recognition skills moving beyond the single syl- lable; smooth, ﬂuent oral reading through adequate practice reading increasingly more complex text; and strategies for the deep processing of text. For the treatment of dyslexia, the most crucial component of instruction is the inclusion of explicit instruction in ﬂuent word recognition that includes phonological recoding (i.e., sounding out words) as a word recogni- tion strategy. Phonological recoding appears to account for individual differences in word recognition in both children and adults and is at the heart of phonological coding problems. When instruction is sufﬁciently intensive and integrates these various components into daily instruction that cumulatively becomes increasingly more complex, children with dyslexia improve considerably in not only accuracy of their word recognition skills, but in their overall reading ability. Particularly striking results are apparent among young children who have not yet experienced reading difﬁculties, but who have risk characteristics of dys- lexia. In multiple studies, the occurrence of reading problems among students at risk for dyslexia and other reading problems has been reduced to below 1.5 % of the total population. One of the most exciting developments in read- ing research is dramatic growth in researchers’ under- standing of which skills predict a phonological processing core deﬁcit. Today, researchers can conﬁ- dently predict which children are most at risk for developing dyslexia and other reading problems as young as kindergarten age. Thus, it is now possible to identify risk for dyslexia early, provide high-quality intervention before failure has occurred, and in most cases normalize reading ability. Early literacy skills that have been demonstrated to accurately predict risk in young children include (a) phonemic awareness; (b) knowledge of letter names and sounds; and © speed of lexical retrieval measured through the rapid naming of objects, colors, digits, or letters. For children who are not identiﬁed early, the out- look is not as positive, with reading problems becom- ing more difﬁcult to remediate by the end of third grade. Older children require more intense interven- tions, occurring for longer periods of time, than do younger children. Although the impact of early pre- ventive and later remedial approaches are comparable, older children are usually so far behind that it is difﬁ- cult to provide the intensity and reading experience that will make them completely proﬁcient readers. Although the outcomes for these groups of children can be very impressive, major concerns remain about the development of ﬂuent reading ability among older students even after intervention, partly because of lack of reading experience. Likewise, these children often have persistent deﬁcits in vocabulary and comprehen- sion that also may reﬂect an earlier inability to access print, as well as co-occurring problems with oral language development that affect listening and read- ing comprehension independently of phonological processing. Instructional Programming Programming to prevent or treat dyslexia and other reading difﬁculties has proven a great challenge within the public schools. Current proposals recom- mend a multitiered model of reading intervention. In most of the proposed multitiered models, Tier 1 is improved classroom-level general education core reading instruction so that critical content is taught well from the beginning. Children who experience difﬁculty in spite of receiving quality classroom-level instruction move into more intense, small group inter- vention (Tier 2) provided in addition to their core (Tier 1) instruction. The fo cus is not on labeling chil- dren, but rather on providing services to children at risk for reading failure f or any reason. Only after a child fails to respond adequately to the ﬁrst two levels of instruction would a child be considered dyslexic, requiring Tier 3, or ongoing, support. Tier 3 interven- tion is typically described as having greater intensity and duration than Tier 2 intervention. Different models 292 Dyslexia vary in the point at which special education eligibility and services would be provided. Understanding Dyslexia In the past few decades, much progress has been made in understanding both the causes and treatment of dyslexia. It is now understood that dyslexia is a neurobiologically based disorder of phonological core processing ability that causes individuals to experience severe difﬁculty in reading and spelling at the level of the single word. Furthermore, it is now known that although genetics plays a large role in determining if a child has a predisposition for devel- oping dyslexia, the environment also plays a large role in determining the level of dyslexia expressed in any one individual. Environments that provide repeated and careful opportunities to practice phono- logical coding will result in a decreased expression of dyslexia. Furthermore, dyslexia is treatable, even among older children, although outcomes are gener- ally better for younger children. However, this is sim- ply because younger children have not yet fallen behind and thus don’t have as much ground to cover in order to catch up. Patricia G. Mathes and Jack M. Fletcher See also Learning; Learning Style; Reading Comprehension Strategies; Special Education Further Readings Aylward, E. H., Richards, T. L., Berninger, V. W., Nagy, W. E.,Field,K.M.,Grimme,A.C.,etal.(2003).Instructional treatment associated with changes in brain activation in children with dyslexia. Neurology, 22 , 212–219. Eden, G. F., Jones, K. M., Cappell, K., Gareau, L., Wood, F. B., Zefﬁreo, T. A., et al. (2004). Neural changes following remediation in adult developmental dyslexia. Neuron , 44 , 411–422. Fletcher, J. M., Lyon, G. R., Fuchs, L. S., & Barnes, M. A. (2007). Learning disabilities: From identiﬁcation to intervention. New York: Guilford. Mathes, P. G., Denton, C. A., Fletcher, J. M., Anthony, J. L., Francis, D. J., & Schatschneider, C. (2005). The effects of theoretically different instruction and student characteristics on the skills of struggling readers. Reading Research Quarterly , 40 (2), 148–182. Orton, S. (1928). Speciﬁc reading disability- strephosymbolia. Journal of the American Medical Association , 90 , 1095–1099. Pakorni, J. L., Worthington, C. K., & Jamison, P. J. (2004). Phonological awareness intervention: Comparison of Fast For Word, Earobics, and LiPS. Journal of Educational Research , 97 (3), 147–157. Schatschneider, C., Francis, D. J., Carlson, C. D., Fletcher, J. M., & Foorman, B. R. (2004). Kindergarten prediction of reading skills: A longitudinal comparative analysis. Journal of Educational Psychology , 96 (2), 265–282. Shaywitz, B. A., Shaywitz, S. E., Blachman, B. A., Pugh, K. R., Fulbright, R. K., Skudlarski, P., et al. (2004). Development of left occipito-temporal systems for skilled reading in children after a phonologically-based intervention. Biological Psychiatry , 55 , 926–933. Simos, P. G., Fletcher, J. M., Sarkari, S., Billingsley- Marshall, R. L., Denton, C. A., & Papanicolaou, A. C. (2007). Intensive instruction affects brain magnetic activity associated with oral word reading in children with persistent reading disabilities. Journal of Learning Disabilities , 40 (1), 37–48. Stanly, G., Smith, G. A., & Howell, E. A. (1983). Eye movements and sequential tracking in dyslexic and control children. British Journal of Psychology , 74 , 181–187. Torgesen, J. K., Wagner, R. K., Rashotte, C. K., Rose, E., Lindamood, P., Conway, T., & Garvan, C. (1999). Preventing reading failure in young children with phonological processing disabilities: Group and individual response to instruction. Journal of Educational Psychology , 91 , 579–593. Vaughn, S. R., Wanzek, J., Woodruff, A. L., & Linan-Thompson, S. (in press). A three-tier model for preventing reading difﬁculties and early identiﬁcation of students with reading disabilities. In D. H. Haager, S. Vaughn, & J. K. Klingner (Eds.), Validated reading practices for three tiers of intervention. Cambridge: MIT Press. Vellutino, F. R., Fletcher, J. M., Scanlon, D. M., & Snowling, M. J. (2004). Speciﬁc reading disability (dyslexia): What have we learned in the past four decades? Journal of Child Psychiatry and Psychology , 45 , 2–40. Web Sites The International Dyslexia Association: http://www.interdys.org Dyslexia 293 E A master can tell you what he expects of you. A teacher, though, awakens your own expectations. —Patricia Neal E ARLY C HILD C ARE AND E DUCATION Early child care and education is deﬁned as any care on a regular basis by someone other than a child’s immediate family members. Infant and toddler care refers to this type of care for children from birth to age 3 years. Early care and education are important to educational psychology because they are associated with later cognitive and socioemotional outcomes for children in educational set tings. In addition, with the historical changes that resul tedinparentsworkingout- side of the home, increases in wraparound child care to include hours before and/or after the school day have become normative for school-age children, with implications for educational psychology. This review ﬁrst deﬁnes the topic of early child care and education and outlines the different settings in which care takes place. This is followed by an explanation of the impor- tance of early care and education environments to child development outcomes. Finally, the effect of family contexts in early care and education as they relate to child development outcomes is presented. Types of Early Child Care and Education Three main types of early care and education exist for infant and toddler groups. These are in-home care, services in child care homes, and services in child care centers. In-home care refers to care when an individual comes into the family’s home to provide care. Child care homes and centers are out-of-home services where children receive care in another indivi- dual’s home or at a location other than someone’s home,suchasachildcarefacility. Importance of Early Child Care and Education Environments The impact of physical environments and subsequent early experiences on early brain development makes consideration of early care and education environ- ments important. Given the primary importance of the family to early child development, child care has been found to make a unique contribution in the area of cognition. This unique contribution is moderated by three known variables: the amount of time children spend in care, the quality of care, and the type of care. Speciﬁcally, the incidence of problem behavior and minor illness is higher in children who spend more than 30 hours per week in care. Regarding quality, infants and toddlers involved in high-quality child care have been shown to have better social cognition and better reading and math skills compared with children in low-quality settings. Last, regarding type of care, center-based care, compared with other types of care, is associated with better language, social skills, and pre-academic skills with respect to letters and numbers. 295 Models Two important models of early child care and educa- tion exist that encompass both regulatory and process benchmarks for early care and education. The ﬁrst is the Early Head Start program, administered by the U.S. Department of Health and Human Services, Administration for Children and Families, which is aimed at providing services to families with infants or toddlers living below the federal poverty level. The second is the military model of child care, instituted by the U.S. Department of Defense, aimed at providing early care and education services to military families. These models share the philosophy that incorporat- ing both child- and family-centered practices is inte- gral to positive child outcomes. It is clear that the incorporation of both child- and family-centered prac- tices is important from evaluation of the effects of child care in the lives of infants and toddlers from these populations. Speciﬁcally, it is clear from evalua- tion of the Early Head Start model, in particular, that over time children do better when parents have higher levels of education and income, when mothers have fewer symptoms of depression, and when families incorporate learning activities into their home, such as books and play materials, and are involved in their young children’s play activities. The Early Head Start Program Model The Early Head Start program model is built on a framework encompassing four cornerstones to ensure best practices in delivering services to infants and toddlers and their families. These cornerstones include child development, family development, com- munity building, and staff development. Within the cornerstone of child development, which includes child care services, program design incorporates many objectives related to quality child care. Speciﬁcally incorporated are the objectives of positive child health and development, education and early childhood development, child health and safety, good nutrition, and good child mental health. Within the objective to promote positive child health and development is the identiﬁcation of activities that will foster children’s physical, cognitive, and socioemotional growth in a child care setting. Because of the infant/toddler age of the children enrolled in these programs, emotionally secure parent–child as well as child care provider–child relationships are seen as an integral component of fos- tering these areas of development. Thus, in addition to developmentally appropriate early care and educa- tion services, parental supports are in place to build strong parent–infant emotional connections. Supports include activities such as center- or home-based par- ent education as well as parental involvement in the child care program. Community building is a component of the Early Head Start framework that stems from ecological theory, which recognizes the important interaction between the individual and larger systems. For fami- lies with infants or toddlers and limited resources, the Early Head Start programs have aimed to increase access to resources in the community. The compre- hensive nature of the program has been shown to be importanttofamilieswithlimitedresourceswhohave infants or toddlers. Staff development is a last important cornerstone to the Early Head Start programs that is universally important to child care. Teachers with more advanced training and education are also more likely to under- stand and use developmentally appropriate practices in the classroom. In fact, it has been established that developmentally appropriate behaviors in child care staff will increase directly as the number of hours of training received increases. Training, supervision, and mentoring in understanding and developing child socioemotional development are integral activities implemented in the Early Head Start program model to achieve the goal of staff development for the larger purpose of enhancing positive child outcomes. The Military Model of Child Care The U.S. military has developed a model of child care that exempliﬁes the way intensive reform can dras- tically improve a service such as child care. Before the Military Child Care Act of 1989, the military model of child care was very similar to, and plagued by, the same struggles as current civilian child care. The military model of child care came about as a result of a demo- graphic shift in military personnel in the 1980s, as more men and women with families chose the military as a career. The low-quality chil d care arrangements avail- able to military families before 1989, such as unsafe conditions, poor and unenforced standards, and extremely high staff turnover rates, hampered military readiness. For the military, such issues implied the need for an 296 Early Child Care and Education improved child care system. This need was addressed and accomplished by creating a systematic approach to improving its child care system. Today, the U.S. military has set in place a coordi- nated system for all of its branches. The key compo- nents of the system aim to improve quality through enforced standards, accredited programs, well-trained and well-compensated staff, and an increase in family- identiﬁed goals, such as affordability. The military model of child care systematically addresses universal needs for child care. The military model of child care has improved its program quality by creatin g ﬁrm standards in all areas of care, including health, saf ety, staff–child ratios, and staff training. These standards exceed some state stan- dards. Certiﬁcation is done annually, and regulations are enforced through quarterly, unannounced inspec- tions of child care programs. Meaningful sanctions are in place for when programs are found to be noncompli- ant with standards. Inspectors are given the latitude to deem a program necessary to be ﬁxed, waived, or closed, reinforcing the intolerance for unsafe programs to remain open. The civilian child care community would beneﬁt greatly from strict enforcement of quality standards as exempliﬁed in the military model. The military model incor porates a single point of entryapproachtochildcare . This addresses the differ- ing needs and wants of families as it pertains to care for their child(ren). Child care centers, family child care homes, and individual pro viders are maintained in one, current database that ma kes it easier for families to choose what is best for their family. This single point of entry method has two additional, positive con- sequences. First, it is easier for accreditation and moni- toring to take place within a universal system. Second, resource and referral services are important to families choosing child care, and a universal system can be cost-effective to this import ant ﬁrst step to ﬁnding child care for families. In civilian child care, some states have incorporated resource and referral services, yet many families are not aware of this service. Public information campaigns addres s this issue. Additionally, a statewide resource and referral system that links pro- gram accreditation and monitoring is a cost-effective way to address many issues simultaneously, such as family need for child care av ailability information and tracking of program accreditation and monitoring. The National Association for the Education of Young Children (NAEYC) is an agency that rewards child care programs for going beyond mandatory licensing requirements throu gh an accreditation system. In the military system, NAEYC provides ﬁnancial assistance to child care prog rams. This accreditation standard in the military system has led 99 % of centers to be accredited. Moreover,halfofchildreninmilitarychildcareare under 3 years old. As a result of the large number of infants and toddlers in child care, improvement for this vulnerable population has been a priority in military reform. Within this system, children are able to enter at 6 weeks old and for up to 12 hours per day, as this is what is needed for many military families. An addi- tional need, for many military families, is child care services provided during ‘‘off’’ hours, such as during evenings or on weekends. As the economic environ- ment changes, civilian families face circumstances sim- ilar to those of military families; for example, extended family may not be in the same vicinity. Thus, the need to rely on professional support for child care is a reality for both military and civilian famil

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ies. The military model of child care has foc used reform on providing ﬂexible care schedules to families. To address the needs of infants and toddlers, mili- tary child care policy has also instituted primary caregiver assignments of one child care provider to a child. Additionally, infants are allowed individual sleeping and feeding schedules and sleep in cribs with the rest of the group, rather than in a separate sleeping room. Policy has also emphasized safety and sanita- tion for this age group. Child care centers have incor- porated building design that decreases the spread of germs and reduces child accident rates through exit- ways from infant and toddler classrooms to outdoor play areas designated speciﬁcally for different age groups. The military model of child care incorporates poli- cies above and beyond state licensing requirements. Policies such as standard use of surveillance cameras in the classrooms and a diaper- changing rotation among staff (so that no one individual is responsible for diaper- ing) can decrease the incidence of child abuse. Last, within the military model, parents are seen as constituents and are, thus, involved in programs—for example, through their presence in the centers and through their decision-making capacity. Programs are designed to be family-friendly and support infant and toddler health outcom es by providing rooms for mothers to nurse their infants and toddlers. Parents also Early Child Care and Education 297 participate in advisory councils as well as serve on inspection teams to monitor ch ild care quality standards. The military model of child care emphasizes staff training and compensation. The system requires that all employees receive basic preservice training. Addi- tionally, child care personnel begin with higher- than-average wages, and they are also rewarded with increased wages for achieving training milestones. State Licensing, Monitoring, and Optional Accreditation In general, states regulate early child care and educa- tion through licensing standards and monitoring prac- tices. Many programs choose not only to incorporate standards that meet the required state licensing standards but also to adopt standards above and beyond minimal state standards. One organization, the NAEYC, is widely used by child care programs and is the largest organization serving on behalf of infants and children through age 8 in child care. The network was founded in 1926 with the mission of helping pro- grams optimize child outcomes and to help families identify high-quality child care programs. It has an alliance of local, regional, national, and international afﬁliates. To be accredited by NAEYC, a program must involve itself in (a) self-study, through which staff identify areas for improvement; (b) validation, in which program information is veriﬁed during a site visit by a team of trained volunteers; and © a review by recognized experts who judge whether the pro- gram is in compliance with the accreditation criteria. Programs are granted accreditation for 3 years with agreement to improve areas in which they are only marginally compliant. Annual reports are required to document continued compliance and improvement. Regulated and Process Variables in Early Child Care and Education Both the U.S. Department of Defense and the Early Head Start programs are large-scale models with sys- tematically incorporated standards above and beyond many state standards for infant and toddler early care and education. Many of the standards associated with these two programs come from NAEYC, the National Association for Family Child Care, or both. Two types of variables are discussed in relation to early child care and education monitoring and evaluation: regulated variables and process variables. Regulated variables encompass health and safety sys- tem variables, including adult-to-child ratios, group size, and staff education levels. Regulated variables matter to infant and toddler care in that they uniquely predict child development outcomes separate from other variables. Process variables relate to develop- mental outcomes in early care and education, both cognitive and socioemotional, which come from the relationship between providers of early care and edu- cation and the children in their care. Regulated variables are predictive of process out- comes, which are related to child development out- comes. Thus, early care and education programs that have smaller adult-to-child ratios, smaller group sizes, and providers with higher education levels predict more positive provider-to-child social interactions. This, in turn, positively affects children’s cognitive and socioemotional development. Thus, the most effective early care and education programs incorpo- rate both highly regulated and process variables into services for infants and toddlers. Family Contexts in Early Child Care and Education Family features have been found to be the most pre- dictive determinants to child development outcomes for children in early care and education settings. From these ﬁndings, models of early care and education have been established that emphasize the components of positive family features that can be replicated in early care and education settings. These process vari- ables are associated with cognitive and socioemo- tional development by building secure relationships between early care and education providers and the infants and toddlers in their care. They include dis- creet aspects of emotional connections between care providers and infants and toddlers. To develop emotional connections between care providers and the children in their care, the physical as well as interpersonal environment needs to be consid- ered. Regarding the physical environment, standards call for a more home-like than school-like environment for infants and toddlers. To meet the needs of infants and toddlers, physical environments that replicate home environments often include primary caregiver assignments of one child care provider to a child. Additionally, infants are often allowed individual feed- ing and sleeping schedules and sleep in cribs among the rest of the group, rather than in separate sleeping 298 Early Child Care and Education rooms. Children’s work is displayed in the classroom and at child eye level to build a sense of ownership and belonging. Equipment, such as tables and chairs, is child-sized, and soft surfaces exist for children to rest and relax on during the day. A variety of materials exist, especially dramatic play materials, for toddler- age children to foster socioemotional and social skills development through role-playing behavior. Also, pro- viders interact with the physical environment in ways that promote prosocial behavior, such as engaging in dramatic play activities and modeling and facilitating prosocial behavior between children. Last, a predictable environment with few changes to the setting is sup- portive of a child’s emotional security. In addition to the physical environment, socioemo- tional development in early care and education is also supported by way of emotional connections through caregiver–child interactions. An essential aspect of preparing child care providers to foster socioemotional development in the child is to learn about how to form emotionally availab le and securely attached relationships. Attachment and Emotional Availability in Relationships in Child Care Traditionally, attachment is viewed as a quality of parent–child relationships; however, children may also develop attachments with ad ult caregivers other than parents. Whereas approximately 70 % of children form secure attachments with their parents, estimates indi- cate less than half of children in child care form secure attachments with their child care providers. The pres- ence of caregiver sensitivity, appropriate structuring, nonintrusiveness, and nonhostility, which are qualities of emotional availability, are important, and research indicates that these qualities are predictive of secure attachments and children’s emotional availability. According to Zeynep Biringen, caregiver sensitivity in the context of early child care and education includes both nonverbal and verbal behaviors. Nonverbal beha- viors include physical affection, affect, awareness of timing, creativity during p lay, prompt and accurate responsiveness, and respectful behavior. Verbal beha- viors include the provider mirroring what the child is doing, singing, and speaking to the child respectfully. Caregiver structuring behaviors that are nonverbal include not restricting the child in equipment such as a high chair longer than needed (or to the point where the child’s patience runs out) and setting up individual and group activities. Verbal behaviors include talking to the child in passing, talking during meals and snacks, talking when picking up the infant to take to an activity (diapering), and verbally framing the transition from one activity to another. Caregiver nonintrusive- ness behaviors that are nonverbal include picking up a child in a gentle way, limiting the number of physical interventions, reserving abrupt behavior for emergen- cies, not introducing all of the play toys, and playing with the child by focusing on an object that interests the child. Verbal behaviors include using language that is not intrusive, using a gentle and calming voice, and reserving language that can be jarring for emergencies. Caregiver nonhostile, nonverbal behaviors include attempts to be engaged with children rather than show- ing boredom and using coping mechanisms to limit stress. Verbal behaviors inc lude limiting negative talk and refraining from complaining. Last, caregiver awareness of the child’s contribution to interactions is evidenced by caregiver behaviors such as realizing that the child’s emotions are linked with child–provider interactions; showing awareness that a child who is blandinfacialexpressio ns but causes no trouble and is undemanding is not a prefe rable presentation; and knowing that when a child is acting out, it is a commu- nication mechanism. These nonverbal and verbal caregiver behaviors discreetly inﬂuence child socioe- motional outcomes for infants and toddlers, speciﬁcally secure attachments, in the early care and education set- ting. Children with secure attachments are more likely to experience positive long-term outcomes throughout their lives. For that reason, children need caregivers who are emotionally available to them. Some of the beneﬁts children may experience from emotionally available relationships are secure attachment, less aggressive behavior, less victimization, better peer rela- tionships, more attentivene ss at school, and better rela- tionships with teachers. Ear ly care providers must take into account the emotional and relational needs of infants and toddlers and facil itate emotionally available and secure relationships. Despite the importance of the early child care con- text, new research ﬁndings from the National Institute of Child Health and Human Development (NICHD) Study of Early Child and Youth Development indi- cates only a small-magnitude linkage between child care and child development and that the family is more crucial than early care professionals in a child’s development. Because child care has become an important resource and a way of life for working Early Child Care and Education 299 mothers and fathers, it was important to conduct a deﬁnitive study to understand the impact of child care on children. For 15 years, a multisite investiga- tion at 10 U.S. sites were examined, following the development of 1,000 healthy children and their fami- lies, beginning with a child’s birth. Ethnically diverse families, with some 80 % two-parent households, were initiated into the NICHD project. These children were in child care for close to 30 hours per week from birth to almost school age, thus including a sample of parti- cipants who had a high dose of child care in their infancy and preschool years. Most began in home- based situations with relatives or nonrelative care- givers and then progressed to center-based facilities. An important ﬁnding from this multisite investiga- tion is that children do better when parents are more educated; when income for the family is higher; when mothers are low on symptoms for depression; and when families have routines, rituals, books, and other learning and play materials. The children in the study had better outcomes if mothers were sensitive, and mothers were more likely to be so if they had more socioeconomically advantaged lives. These parent or family qualities were up to three times more strongly associated with child development than child care fea- tures, although when child care features were exam- ined, qualities such as higher-quality care (with small child-to-provider ratios, good play materials, etc.) were found to be important. Those children who experienced high-quality care were more likely to have better social and cognitive (reading, math) skills than those who experienced low-quality care. To bring a different perspective into focus, research on attachment has indicated that sensitive mothers are sometimes in relationship with insecure infants and toddlers. In such mismatched situations, ‘‘marginal’’ child care has been found to be a part of the equation. In a study conducted in Israel using the full spectrum of socioeconomic levels, infant attach- ment was assessed using the well-known Strange Situation procedure, and maternal sensitivity was assessed using the Emotional Availability Scales. Results showed that the hypothesized link between infant secure attachment and maternal sensitivity was found only for infants in individual care at home and not for infants at centers of low quality. It is possible to hypothesize that extensive experience in an early care environment that is not in tune with an infant’s needs and that misses important cues for interaction and relationship may be akin to small doses of trauma. When an infant spends whole days where he orsheisnotrespondedtoinanappropriatefashion and where engagement is lacking (on both the side of the professional and the side of the infant)—that is, where there is no real relationship—the infant may take back into the home setting behaviors that create insecure attachments to the primary caregivers as well. Thus, for children in child care, it is crucial to focus on both family and child care providers as agents of socialization. In summary, emphasis on child care research should be to include parents as the primary socialization agents in their children’s lives. Intervention science, however, should not abandon child care professionals as agents of socialization. Shannon Altenhofen, Brooke Davy, and Zeynep Biringen See also Attachment; Emotional Development; Family Inﬂuences; Head Start; Parenting Styles; Social Development Further Readings Aviezer, O., & Sagi-Schwartz, A. (2003). Ecological constraints on the formation of infant-mother attachment relations: When maternal sensitivity becomes ineffective. Infant Behavior & Development , 26 , 285–299. Biringen, Z. (2000). Emotional availability: Conceptualization and research ﬁndings. American Journal of Orthopsychiatry , 70 , 104–114. Bredekamp, S., & Copple, C. (Eds.). (1997). Developmentally appropriate practice in early childhood programs (Rev. ed.). Washington, DC: NAEYC. Howes, C., Galinsky, E., & Kontos, S. (1998). Child care caregiver sensitivity and attachment. Social Development , 7 (1), 25–36. Howes, C., Whitebook, M., & Philips, D. A. (1992). Teacher characteristics and effective teaching in child care: Findings from the National Child Care Stafﬁng Study. Child and Youth Care Forum , 21 , 399–414. National Institute of Child Health and Human Development. (2006). The NICHD Study of Early Child Care and Youth Development (SECCYD): Findings for children up to age 4½ years (NIH Publication No. 05-4318). Washington, DC: U.S. Government Printing Ofﬁce. Web Sites Early Head Start National Resource Center (EHS NRC): http://www.ehsnrc.org 300 Early Child Care and Education National Association for the Education of Young Children (NAEYC): http://www.naeyc.org Zero to Three: http://www.zerotothree.org E ARLY I NTERVENTION P ROGRAMS The term early intervention (EI) programs refers to a mosaic of services and programs created for young children and their families to meet educational, social, and health needs and promote enhanced learning, social, and communication outcomes. EI programs are provided before a child starts school, sometimes beginning before birth and continuing to school age. A goal of EI programs is to reduce gaps in child development that are due to one or more of the fol- lowing: poverty or welfare status, family violence, child abuse, lack of family housing or ability to par- ent, poor health, single parenthood, teen parenthood, low maternal education, lack of proﬁciency in the English language, disabilities, developmental delays, poor language or emergent literacy, and the presence of a variety of at-risk conditions. EI programs incor- porate a range of approaches, including child-focused interventions, dyadic interventions between an infant and parent, and family interventions that include sib- lings, parents, and even grandparents. The Division of Early Childhood for the Council of Exceptional Chil- dren identiﬁed a list of 1,606 recommended EI prac- tices based upon a review of empirical research in 48 journals of effective early intervention programs or approaches. Over the past 35 years, three major areas of inter- est have evolved in the ﬁeld of EI programs: 1. Longitudinal experimental research of the efﬁcacy of programs for children from birth to 3 years and preschool age 2. The national establishment of programs to achieve ‘‘equity’’ in education for children in poverty (e.g., Early Head Start and Head Start) and children with special health care needs or disabilities (e.g., Early Intervention Programs for Infants and Toddlers with Disabilities under Part C of the Individuals with Disabilities Education Act [IDEA] and Preschool programs under Section 619 of Part B, IDEA) 3. Concerns for quality and accountability prompted by legislative mandates This entry will brieﬂy highlight recent research in each of these interest areas and provide additional background information on modes of service delivery in health settings, homes, and centers and the eco- nomic advantages provided by intervention services. Prevention Efforts Early intervention programs may have features that are universal or are intended for a broad population. All young children are in need of a medical home that will provide continuity of medical care with developmental screening and preventive health care in a family-centered context. Model programs such as Healthy Steps, a pedi atric care intervention, provide anticipatory guidance through child devel- opmental surveillance, promote positive health practices, and encourage parents to ask questions and express any concerns they may have regarding their child’s development. This program has proven successful in increasing a child’s access to well- baby care, because participating families tend to remain with a practice for longer periods, and in reducing negative parenting practices and allowing depressed mothers a safe environment to discuss their distress. Prevention approaches can begin even before the birth of a child in the form of preventing or ameliorating the effects of conditions that may be caused by environmental, lifestyle choices, or other addressable conditions. A number of early interven- tion programs have been developed that target women in the neonatal period, particularly women with conditions that requir e extended hospitaliza- tions. The Newborn Individualized Developmental Care and Assessment Program (NIDCAP), devel- oped by Heidelese Als and others, has fostered new approaches to neonatal care, especially among pre- mature infants. The NIDCA P approach trains neo- natal staff to support premature infant regulation and appropriate development through individual- ized observation. Because of recent technological advances, very low birth weight (VLBW) premature infants have an improved survival rate but are at higher risk for adverse health problems and devel- opmental delays; neonatal i ntervention approaches like NIDCAP address these issues. As the rate of premature births continues to climb, the develop- ment of effective interventions for the medically fragile premature infant is of increasing concern. Early Intervention Programs 301 Longitudinal Research Studies in Early Intervention The U.S. Department of Education’s Institute for Edu- cational Sciences promotes experimental, randomized, clinical trials as the desirable method to determine efﬁ- cacy in education. EI research has beneﬁted from a history of longitudinal studies in which the infants, toddlers, and preschoolers receiving intervention ser- vices are now adults. The Caro lina Abecedarian Project is a classic example of an EI study that demonstrates high methodological rigor, random assignment to inter- vention and control groups, and low attrition rates. This study of a model program, spanning 8 years, was designed to close the academic gap between young children from poor families and their more economi- cally advantaged peers. In the ﬁrst phase, full-day center-based services were provided to the intervention group from infancy to kindergarten entry, augmented by a developmental curriculum and an emphasis on language acquisition. From kindergarten to second grade, a home resource teacher supported and encour- aged parents to work with their children at home. Parti- cipants continued to show consistent cognitive and academic gains compared with controls when assessed at 12-to-54 months and 12, 15, and 21 years of age. Participants in the prescho ol intervention had fewer retentions, were less likely to require special education services,and,byage21,hadcompletedsigniﬁcantly more years of education than controls. Long-term follow-up programs contribute substan- tially to the ﬁeld of early intervention, providing essential information on the types of developmental outcomes resulting from the application of models of intervention that vary based on format, content, intensity, and population served. Programs such as Chicago Child-Parent Centers and the Perry Preschool Project have yielded positive long-term outcomes through a combination of center-based and home- based parent-directed programs. In the case of the Perry Preschool Project, although signiﬁcant gains on cognitive measures were not retained over time, real- life beneﬁts included higher graduation rates and col- lege attendance, improved rates of gainful employ- ment, and reduced crime and teen pregnancy. Studies of speciﬁc populations, such as children exposed to cocaine, provide additional support for the beneﬁcial effects of center-based programs in combination with home visits. A new area of promising research is the state implementation of universal prekindergarten programs for 4-year-olds, such as the efforts under- way in Oklahoma, which provide encouraging ﬁnd- ings of enhanced school readiness with signiﬁcant gains in areas of math and language achievement. Finally, any mention of longitudinal intervention efforts must include a discussion of Head Start, the most widely offered early childhood program for pre- school-age children living in poverty. Given the breadth and impact of Head Start and its companion program for children from birth to age 3, Early Head Start, each of these programs will be discussed in more detail in later sections of this entry. Looking toward the future, the Early Childhood Longitudinal Studies-Birth Cohort, a nationally repre- sentative sample of 10,688 infants born in 2001, provides a prospective opportunity to study child development from infancy to kindergarten. In addition to comprehensive data about child health, family health and circumstances, and direct measures of a child’s mental, motor, and social behavior, informa- tion about the provision of early intervention services and day care is also available. Eventually, analyses of these data could provide information that is relevant for national policies on children and EI programs. Home-Based Programs Within the ﬁeld of EI, family-centered services are viewed as an integral component of successful pro- grams. Offering services within a home-based setting has been found to contribute to a family-centered approach, as the child is treated within the family sys- tem, and caregivers have the opportunity to view and participate in the intervention activity. However, despite the extensive use of home-based services, little research has been done to evaluate the efﬁcacy of this mode of service delivery for children with develop- mental disabilities. The ﬁeld has not yet reached a con- sensus regarding the effectiveness of a home-based model of services, and some studies question the feasi- bility of implementing a home-based model within early intervention. In particular, concerns exist regard- ing the training and background of personnel, large provider caseloads, and the cultural mismatch between providers and participating families. To date, few studies of home-based services docu- ment signiﬁcant differences in participant versus control outcomes. For example, group differences were not found in home-based interve ntions aimed at improving parent–child interaction and positive parenting practices, 302 Early Intervention Programs promoting child development, and preventing neglect and abuse. However, the negative ﬁndings must be placed in perspective, because to impact child outcomes over the long term, it is necessary to work directly with parents and primary caregivers to improve their ability to take better care of their children. In this regard, home- based services targeting parents and parents-to-be have proven to be effective. For example, research by Olds and colleagues as part of the Elmira Prenatal/Early Infancy Program provides evidence that home-based interventions lead to improvement in pregnancy out- comes, child health and development, and families’ eco- nomic self-sufﬁciency. In sum, given the inconsistent ﬁndings within the literature, the efﬁcacy of home-based services has not yet been conﬁrmed. However, the research has pro- vided valuable information regarding some of the factors that limit program effectiveness, including infrequent home visits (i.e., due to cancellation or missed appointments), high attrition rates, urgent fam- ily needs that may interfere with program implemen- tation, low parent engagement, heavy service provider caseloads, inadequate training of service providers, and a cultural mismatch between participants and service providers. Disability: Birth to Three In 1986, with the passage of Public Law (P.L.) 99–457, Education of the Handicapped Act (EHA), later renamed Individuals with Disabilities Education Act (IDEA), U.S. states had the option of establishing systems of early intervention services for infants and toddlers (i.e., from birth through age 2) with disabil- ities. All states and territories participate in this pro- gram and are asked to establish a coordinated and comprehensive system of services along with a method to ensure payment for early intervention services. EI services are multidisciplinary and uniquely designed to fully involve the child’s family in the decision-making process through the development of the Individual Family Services Plan. The central focus on families is a distinct part of EI services both from a policy per- spective and a programmatic stance. Thus, it is no sur- prise that most families receive services in the home, with speech, occupational, and physical therapies; spe- cial instruction; and developmental monitoring cited as the most frequent services delivered. The median amount of time for weekly services scheduled per child during the ﬁrst 6 months in EI is 1.5 hours. Children with diagnosed disabilities (such as Down syndrome) are automatically eligible for services, but states have discretion in the adoption of a deﬁnition of developmental delay and whether or not to serve children who are considered at risk for developmental delay. Variation in the eligibility criteria employed by individual states has resulted in variability in the per- centage of infants and toddlers served in each state. In 2002, the most recently reported national count of children participating in Part C services ranged from 1 % of the population to 9.38 % with the overall aver- age being 2.2 % . Child characteristics are strongly related to the age at which children enter early inter- vention. Depending on eligibility criteria established within each state, children with speciﬁc diagnosed conditions and those considered at risk for develop- mental delay may automatically qualify for EI ser- vices and therefore, on average, are enrolled earlier than children with developmental delays. The low rate of early entry for children with developmental delays, including speech and language disorders, suggests the challenges of early identiﬁcation of these disabilities. National Early Intervention Longitudinal Study The National Early Intervention Longitudinal Study (NEILS) is a longitudinal study of a nationally repre- sentative sample of the children and their families participating in early intervention services of Part C of IDEA. Beginning in 1997, data collection occurred at entry to EI through kindergarten; the data consist of family interviews, service record, and service pro- vider, program director, and kindergarten teacher sur- veys. Recognizing the importance of family outcomes for young children with disabilities, NEILS found that families were highly satisﬁed with EI services, and nearly all families felt they were equipped to help their child learn and develop and believed they could advocate on their child’s behalf. Although most fami- lies had positive experiences, ethnic minorities and families with children in poor health were more than twice as likely to have less positive outcomes. In terms of child outcomes, NEILS found that chil- dren in EI vary widely in terms of their age-at-entry, health status, reason for eligibility, and pattern and level of developmental skills. Children identiﬁed as at risk and those with diagnosed conditions were found to enter much earlier than children identiﬁed with developmental delay. NEILS has shown that EI Early Intervention Programs 303 entrants vary greatly in their developmental strengths and needs, reinforcing the importance of an individu- alized approach. As of kindergarten entry, one third of EI participants were no longer involved in special education and were not identiﬁed as having a disabil- ity. This ﬁnding suggests that a sizeable percentage of children enter EI with developmental problems, but given the appropriate support and intervention ser- vices, these children may avoid long-term involve- ment in special education. However, the majority of EI participants continue to require supportive inter- ventions through preschool and/or school-age special education programs. Disability: Preschool P.L. 99–457, in 1986, also contained provisions in Section 619 to extend a free appropriate education to children with disabilities from the age of 3 to 5. Pre- school-age children with disabilities are given the same services as older children in special education, includ- ing an Individualized Education Program. However, eligibility criteria for entrance into preschool special education often differ from the criteria established for EI. A challenge for states is to ensure that children in EI programs who need to continue receiving special services are not lost in the transition from the EI sys- tem to the school system. In addition, a major research question for the preschool population relates to the rel- ative beneﬁts of providing services in inclusive envir- onments as opposed to segregated programs set up solely for children with disabilities. The preschool pro- grams for children receiving special education from age 3 to age 5 can be in an array of settings, including public schools, Head Start, and other inclusive environ- ments. In the 2002 child count of the preschool popu- lation under Section 619, about 30 % of children were in inclusive early childhood settings, 39 % in an early childhood or special education setting, 6 % at home, 13 % part-time in both early childhood and special edu- cation settings, 1 % in a residential setting, 5 % in a sep- arate school, and the rest receiving itinerant services, and reverse mainstreaming. Pre-Elementary Educational Longitudinal Study (PEELS) The Pre-Elementary Educational Longitudinal Study (PEELS) was commissioned by the U.S. Department of Education to describe the school experiences, developmental characteristics, and educational pro- grams of 3- to 5-year-old children participating in Section 619 preschool special education services. Preliminary study ﬁndings suggest that males are disproportionately represented, whereas the ethnic composition of preschoolers with disabilities tends to closely reﬂect the racial representation of the general population. Parental education level corresponds to that of the general U.S. population; however, a larger pro- portion of participants were reportedly living in pov- erty. Within the PEELS sample, approximately 50 % of participants were eligible for services because of speech and language difﬁculties, with an additional 25 % identiﬁed with developmental delay. PEELS found that approximately 25 % of preschoolers with disabilities were born prematurely. On average, chil- dren in PEELS scored within one standard deviation of the mean on standardized measures of school readi- ness. However, wide variability was found across dis- ability classiﬁcations. Children with mental retardation scored lowest on measures of verbal skills, whereas children with autism had more pronounced difﬁculties on measures of social skills and behavioral problems. Poverty Interventions Head Start The Head Start program, administered through the U.S. Department of Health and Human Services, is a nationwide program targeting low-income families and their preschool-age children. In its four decades of existence, Head Start has provided child develop- ment and related services to over 23 million children. It offers a comprehensive array of services, including educational interventions, parental involvement, and medical services such as dental care and nutrition planning. Congress recently commissioned a study through the Department of Health and Human Ser- vices to document the population served in Head Start and determine Head Start’s impact on school readi- ness and the conditions under which the program was optimally effective. The study sample consisted of approximately 5,000 children between the ages 3 and 4 from 84 nationally representative grantee or delegate agencies. At the time of service entry, parti- cipants were randomly assigned to either a control group (non–Head Start, receiving non–Head Start related services) or a Head Start program through which families and their children would receive Head 304 Early Intervention Programs Start related services. Data collection started in the fall of 2002, and children were followed through the spring of their ﬁrst-grade year. Findings reported at the end of the ﬁrst year of data collection suggest a small-to-moderate impact of Head Start participa- tion for both 3- and 4-year-olds. Across the four con- tent areas examined (i.e., cognitive development, socioemotional development, health, and parenting practices) children with special needs showed improved outcomes in the areas of parent-reported child health status and receipt of dental care. Early Head Start Early Head Start is a program for low-income pregnant women and families with infants and tod- dlers up to the age of 3 years old. The program was designed by the Administration on Children, Youth and Families in 1994, and the ﬁrst funds were received in 1995 and 1996. Early Head Start serves a wide array of families, operating in 664 communi- ties and serving approximately 55,000 children. The program targets low-income families that include pregnant women, infants, or toddlers and aims to enhance the health and development of participants while strengthening community and family partner- ships. In addition, since 1998, 10 % of Early Head Start programs’ funded enrollment opportunities must be offered to children with disabilities. Overall ﬁndings of the Early Head Start Impact Report suggest that in the areas of language, cognitive, and social development, participants experienced a pos- itive program impact compared with children in the control group. Participants were less likely to have delays in cognitive and language functioning and sig- niﬁcantly more likely to receive Part C EI services than were control group children. However, this latter ﬁnding is contentious as some studies have shown that certain Early Head Start families were actually less likely to receive Part C services depending on family demographic characteristics, including ethnicity, lin- guistic background (i.e., non-English-speaking fami- lies), socioeconomic status (i.e., very low-income), and lower educational levels. Despite such ﬁndings, there is still wide-ranging support for the pivotal role that Early Head Start plays in connecting families with much needed services, such as those provided by Part C. Several studies have reported on Early Head Start service providers’ efforts to assist families in learning how to navigate the system in order to access services. In addition, Early Head Start staff offers guidance and recommendations to families with children with sus- pected delays or developmental disabilities. Although much of the research on Early Head Start home-visiting practices has focused on typically devel- oping children, the recent Early Head Start national study documents positive outcomes for young children with special needs. One explanation for the success of home-based services offered through Early Head Start may be tied to service individualization. By following Head Start performance standards that mandate weekly home-visits and bimonthly socialization, Early Head Start home-based services are tailored to meet each family’s unique needs. When necessary, home-visitors provide additional comprehensive services and help to coordinate family service referrals. Positive parental outcomes included greater knowledge of child devel- opment, less parenting stress, ability of parents to pro- vide a more stimulating environment at home, and more bedtime reading. In addition, families participat- ing in Early Head Start home-based services were more likely to be involved in education and training activities. With respect to child outcomes, children receiving home-based services had better vocabulary development and were more engaged in playing with their parents or primary caregivers. Raikes and collea- gues have noted three primary factors related to the success of home-based services on child outcomes: quantity (i.e., number of visits), quality (i.e., quality of engagement) and child focus (i.e., how much time was spent directly in child development-related activities). When comparing home-based services to other ser- vice delivery options, it is important to bear in mind the complexities inherent in this form of service deliv- ery. Vulnerable families living under stressful condi- tions are more likely to choose a home-based service option. This poses greater challenges for home-visitors, as some families have had prior unpleasant experiences with the service system. Families receiving home- based services are more likely to live in poverty and to consist of working and single parent families; in addi- tion, young parents are overrepresented. Each of these factors potentially limits the time and effort that fami- lies are able to devote to early intervention activities. One study examining the impact of demographic risk factors on Early Head Start outcomes found that the program was less effective for families with more than three risk factors and that those families with the high- est number of risk factors often receive home-based or mixed-approach services. Early Intervention Programs 305 Standards for Evaluating Effectiveness New federal and state accountability initiatives require that program expenditures be justiﬁed based on student educational gains. Early intervention pro- grams, including those administered through Head Start, Maternal and Child Health, and the Department of Education, are not exempt from this scrutiny. Both Part C and Section 619 services of IDEA failed to demonstrate results under these Government Per- formance and Results Act requirements and were required to develop new outcome measures. The Early Childhood Outcomes (ECO) Center has assisted the U.S. Department of Education in adopting a func- tional outcome approach that will ultimately yield outcome indicators on three functional skill areas for each state over time. Developing valid and reliable outcome measures is a challenging yet fundamental task necessary for the accurate appraisal of program results. The ECO notes that misuses of data can result when overly narrow outcome measures are chosen, when additional outside information is not taken into account, or when data are misinterpreted. Another way to judge the effectiveness of a pro- gram is to consider its costs relative to its beneﬁts. Evidence is increasingly available supporting the cost-effectiveness of EI programs, highlighting their direct and indirect beneﬁts to society. Some of the longitudinal programs that have been found to be cost-effective include Perry Preschool, the Abecedar- ian Project, the Chicago Child-Parent Center, and the Elmira Prenatal/Early Infancy Program. The returns from these programs range from $3 to $17 for every dollar invested. In addition, children in intervention groups were more likely to continue in regular educa- tion classrooms rather than special education, ﬁnish high school, and be gainfully employed. Implications To better understand the implications of successful EI longitudinal studies, it would be helpful to examine those interventions that have not produced the intended results. For example, the Early Head Start studies report that infants in families who beneﬁt the most are those with no more than three risk factors (the neediest families would be among those with three to ﬁve risk factors). Shonkoff and others note that EI programs may need to be targeted more for children and families with complex social needs, including child abuse. This same reasoning can per- haps be applied to the very high risk populations being served by Early Head Start. The Infant Health and Development Program, an experimental study of premature infants, offered well- structured center-based interventions that did not yield the expected results. When infants were divided into high and low birth weight groups, more robust gains were found in the cognitive outcomes of those infants considered low birth weight compared with the infants who were considered very low birth weight. These ﬁndings are of concern, as the early fragile medical sta- tus of very low birth weight infants puts them at high risk for long-term disabilities . Successful intervention efforts may need to be more intensive and individual- ized to positively impact this group. In addition to tak- ing a more individualized a pproach to interventions, current best practice within EI includes consideration of broader issues, such as addressing the needs of the family within the context of the community. To be effective, EI programs must be designed to address the needs of the population served. Three cur- rent trends impacting intervention services are the increasing rates of preterm births, child poverty, and a broadening of cultural diversity within the United States. To respond to these needs, broad-based pro- grams are required to promote health prevention efforts focusing on early identiﬁcation and interven- tion targeting prematurity and other risky health con- ditions. All EI programs are faced with changing cultural groups and the responsibility to tailor inter- ventions to the needs of diverse linguistic, cultural, and sometimes national backgrounds. In European countries, tax structures and transfers have been shown to lower child rates of poverty; however, within the United States, poverty rates still exceed 20 % , with increases noted in 2002 following a 9-year period of declining poverty rates. EI programs have been built on the success of well-designed longitudinal studies. Going forward, all federal programs, including Head Start, Early Head Start, and Part C and Section 619 of IDEA, will be expected to produce clear developmental outcomes among children and families served in order to meet accountability standards. The complexities of child development and family issues may be difﬁcult to capture in traditional government accountability pro- cesses. In addition, based upon the longitudinal stud- ies from the past, it would be wise to examine 306 Early Intervention Programs development and child and family impacts over the entire early childhood period. For example, a study that combined Early Head Start and Head Start experiences over time would be fruitful. Looking at outcomes of children with disabilities throughout the early childhood period (e.g., combining Part C and Section 619 of IDEA) would be a more meaningful picture of child readiness for school. Carole W. Brown, Joneen M. Schuster, and Doyna Illmer See also Child Abuse; Cognitive Development and School Readiness; Disabilities; Early Child Care and Education; Head Start; Individualized Education Program; Individuals with Disabilities Education Act; Measurement of Cognitive Development; Poverty; Risk Factors and Development; School Readiness; Special Education Further Readings Barnett, W. S., & Belﬁed, C. R. (2006). Early childhood development and social mobility. The Future of Children: Opportunity in America , 16 (2), 73–98. Brooks-Gunn, J., Fuligni, A. S., & Berlin, L. J. (2003). Early child development in the 21st century: Proﬁles of current research initiatives. New York: Teachers College Press. Gormley, W. T., Jr., Gayer, T., Phillips, D., & Dawson, B. (2005). The effects of universal pre-K on cognitive development. Developmental Psychology , 41 (6), 872–884. Hebbeler, K., Spiker, D., Bailey, D., Scarborough, A., Mallik, S., Simeonsson, R., et al. (2007). Final report of the National Early Intervention Longitudinal Study (NEILS). Menlo Park, CA: SRI. Minkovitz, C. S., Hughart, N., Strobino, D., Scharfstein, D., Grason, H., Hou, W., et al. (2003). A practice-based intervention to enhance quality of care in the ﬁrst 3 years of life: The Healthy Steps for Young Children Program. JAMA , 290 (23), 3081–3091. Ofﬁce of Special Education Programs. (2006, July). Twenty- sixth annual report to Congress on the implementation of the Individuals with Disabilities Education Act. Retrieved March 28, 2007, from http://www.ed.gov/about/reports/ annual/osep/2004/index.html O’Neill, J., & Korenman, S. (2004, December). Child poverty and welfare reform: Stay the course. Retrieved April 1, 2007, from http://www.manhattan-institute.org/ html/cr_44.htm U.S. Department of Health and Human Services, Administration for Children and Families. (2005, June). Head Start impact study: First year ﬁndings. Retrieved March 21, 2007, from http://www.acf.hhs.gov/programs/ opre/hs/impact_study/index.html Wall, S. (2002). Opportunities and challenges in providing services to children with disabilities within Early Head Start. In Administration on Children, Youth and Families, Making a difference in the lives of infants and toddlers: The impacts of Early Head Start (Vol. 1: Final technical report). Washington, DC: U.S. Department of Health and Human Services. Westrup, B. (2007). Newborn Individualized Developmental Care and Assessment Program (NIDCAP): Family- centered developmentally supportive care. Early Human Development , 83 (7), 443–449. E ATING D ISORDERS Eating disorders are psychological syndromes charac- terized by severe disturbances in eating behavior, typi- cally in conjunction with intense fears of weight gain, distortion in one’s perception of one’s body shape and weight, and/or having a self-evaluation that is unduly inﬂuenced by body shape and weight. Eating disorders are of particular concern to educational psychologists because they typically onset in mid-to-late adolescence, and also because sociocultural and normative factors are strongly implicated in t heir etiology. In addition, some researchers believe that eating disorders may be best ameliorated through pre vention programs targeted toward high-risk adolescents and delivered in educa- tional settings. In this entry, the symptoms and diagnos- ticcriteriaforthetwomain eating disorder diagnoses— anorexia nervosa and bulimia nervosa—are presented ﬁrst, followed by a description of the prevalence of, and gender differences in, these disorders and a description of a miscellaneous eating dis orders diagnosis: eating disorder not otherwise speciﬁed. Next, the history, course, causes, prevention, and treatment of these disor- ders are reviewed. Finally, other eating disorder diagno- ses are discussed, including tentative diagnoses that need further research, such as binge eating disorder, as well as feeding disorders of infancy and childhood. Anorexia Nervosa According to the Diagnostic and Statistical Manual of Mental Disorders (FourthEdition,TextRevision) ( DSM-IV-TR ), the psychiatric diagnostic classiﬁcation system most frequently used by clinicians and researchers in the United States, to receive a diagnosis of anorexia nervosa (AN), an individual must main- tain a body weight that is signiﬁcantly less than nor- mal. The DSM-IV-TR speciﬁcally states than an individual with AN must weigh less than 85 % of the Eating Disorders 307 weight considered normal for the individual’s age and height; however, the DSM-IV-TR does not refer clini- cians to a speciﬁc source to establish normal weight and, in fact, encourages clinicians to consider normal weight in light of individual factors such as body build. The current International Classiﬁcation of Dis- eases (ICD-10), an alternative diagnostic classiﬁcation system, speciﬁes a more stringent standard for abnor- mally low body weight in AN; speciﬁcally, a body massindexof17.5orless. To receive a diagnosis of AN according to DSM-IV- TR criteria, in addition to low body weight, an individ- ual must also display an inte nse fear of gaining weight or becoming fat and a disturbance of certain weight- and shape-related thoughts. For example, an individual with AN may misperceive her body shape or size (believing she is larger than she really is), may use her weight as the only or the most important criterion against which she evaluates her self-worth, or may deny the seriousness or dangerousness of her low weight. For women old enough to menstruate, the DSM- IV-TR also requires amenorrhea (absence of menstrua- tion over several menstrual cycles) to make a diagno- sis of AN. The reason for including amenorrhea as a criterion is that women who are abnormally thin or who have an abnormally low percentage of body fat frequently stop menstruating. However, because many women take hormonal birth control medications that cause regular menstruation regardless of body compo- sition, this criterion can be difﬁcult for clinicians to assess. Research also suggests that some women, even at very low weights, continue to menstruate, and sev- eral studies have found that deleting amenorrhea from the criteria does not reduce the quality of the AN diagnosis. For this reason, many researchers believe that amenorrhea will no longer be a requirement for a diagnosis of AN in the future. After deciding that a patient meets criteria for AN, clinicians using the DSM-IV-TR for an eating disorder diagnosis must assign the individual to a subtype of AN. There are two subtypes: a restricting subtype and a binge-eating/purging subtype. Individuals who fall into the binge-eating/purging subtype of AN regularly engage in either binge-eating behavior, purging beha- viors, or both (described more fully in the next sec- tion). Individuals with the restricting subtype of AN do not engage in such behaviors. Some people believe that anyone who engages in binge-eating or purging behaviors must have bulimia nervosa (BN), but this is not the case. The main feature distinguishing someone with AN from someone with BN is body weight, not behavior; individuals with AN are abnormally thin, whereas individuals with BN are normal weight or overweight. Bulimia Nervosa BN is characterized by recurrent episodes of binge eating, followed by inappropriate compensatory beha- viors designed to prevent weight gain, such as self- induced vomiting, misuse of laxatives or other drugs, periods of fasting, or excessive exercising. In the DSM-IV-TR , binge eating is deﬁned as eating in a dis- crete period of time (e.g., a 2-hour period) an amount of food that is deﬁnitely larger than what most people would eat under similar circumstances and feeling a lack of control over eating during the binge episode. Some researchers call this deﬁnition an ‘‘objective binge’’ because the amount of food being consumed is objectively large, such as eating a half-gallon of ice cream or an entire extra-large pizza at a sitting. How- ever, people with BN are more likely than objective raters to rate any given eating episode as a ‘‘binge.’’ Researchers have also observed that the type of food consumed (e.g., foods perceived to be high calorie or ‘‘sinful,’’ such as potato chips) and the individual’s mood while eating are more predictive of whether an eating episode will be described as a binge than the actual amount of food consumed. Thus, some researchers believe the subjective aspects of a binge— the feelings of loss of contro l and negative emotions— may be more important to a diagnosis of BN than the ‘‘objectively large’’ binge criterion. However, other researchers maintain that t he presence of objectively large binges has diagnostic signiﬁcance. In addition to binging, to receive a diagnosis of BN, an individual must engage in recurrent and inap- propriate compensatory behaviors designed to prevent weight gain. Many people are aware of self-induced vomiting and laxative abuse as examples of compen- satory behaviors engaged in by individuals with BN, but individuals with BN may also misuse other drugs, such as diuretics, diet pills, or enemas, or they may engage in periods of fasting, or they may simply exer- cise excessively. Exercise is considered ‘‘excessive’’ when it interferes with other important activities, such as schoolwork or relationships; when it occurs at inap- propriate times and places; or when the individual continues to exercise despite injury. Individuals must engage in both binges and compensatory behaviors, 308 Eating Disorders on average, twice a week or more for 3 months to receive a diagnosis of BN. In addition, similarly to individuals with AN, individuals with BN must be unduly inﬂuenced by their shape and weight in evalu- ating themselves. As with AN, BN is divided into two subtypes: a purging subtype, where the individual engages in self-induced vomiting or the misuse of drugs to pre- vent weight gain; and a nonpurging subtype, where the ways that the person has tried to prevent weight gain have included only other methods, such as fasting or exercise. Some people may believe that someone who does not use laxatives or self-induce vomiting cannot have BN, but this is not the case. Gender Differences, Prevalence, and Subthreshold Cases Both AN and BN affect women disproportionately; 90 % of people who meet criteria for either diagnosis are female (hence the convention in this entry to refer to individuals as ‘‘she’’). Men do acquire eating disor- ders, however, and men and women with eating disor- ders appear to have similar symptoms, similar risk factors prior to developing the eating disorder, and similar co-occurring disorders (such as depression). Compared to women with the disorder, men may have a later onset of their eating disorder symptoms and may be more likely to have engaged in a sport where weight control was emphasized or to have been over- weight prior to the onset of the disorder. Some researchers believe that eating disorder rates in men may be increasing as sociocultural pressures on men to be thin and athletic-looking increase. Even in women, AN is relatively rare, with a life- time prevalence among women of 0.5 % .Bulimianer- vosa is somewhat more common, with a lifetime prevalence among women of 1 % to 3%.However, these may be underestimates of the true prevalence of eating disorder pathology. One serious criticism of the DSM-IV-TR classiﬁcation of eating disorders is that the majority of patients seen in clinics who pres- ent with eating disorder symptoms do not actually meet full criteria for either AN or BN. People who have serious eating disorder symptoms, but who do not meet full criteria for either AN or BN, are usually diagnosed with eating disorder not otherwise speciﬁed (EDNOS), a miscellaneous diagnostic category that includes people with a wide variety of eating disor- ders symptoms and symptom severity. Little is known about how people with EDNOS differ from people with AN or BN, but they can have symptoms equally as severe as those who meet criteria for the full disor- der. In one study of hundreds of patients who had sought treatment at eating disorder specialty clinics in several states, the percentage of patients who were diagnosed with EDNOS instead of AN or BN ranged from 49 % to 71% . In other words, the relatively low prevalence of AN and BN may not reﬂect the true number of people who are troubled by serious eating disorder symptoms. History of Eating Disorders As far back as the Middle Ages, writers have described occasional cases of individuals, often young women, deliberately engaging in self-starvation, typically as part of religious devotion. In 1689, the physician Richard Morton described two cases wherein a young person (he described both a male and a female patient) under signiﬁcant psychological stress refused to eat and became abnormally thin. His medical inter- ventions with these patients were apparently of little beneﬁt, and his female patient died (it is unknown what happened to his male patient following treat- ment). However, these early cases, however much they may resemble AN, lack the preoccupation with weight, shape, and avoidance of fatness that is the hallmark of the modern disorder. A description of the disorder in its contemporary form, including the asso- ciation between self-starvation and fears of fatness or disturbed body image, as well as psychological dis- tress, began to appear in accounts of the disorder at the beginning of the 20th century. BN, in contrast, has a much shorter history. Although there exist a small handful of case reports of binge-eating and compensatory vomiting or laxative abuse as early as the 1940s, the disorder was not named until Gerald Russell described it as a variant of AN in 1979. At that point, there were sufﬁcient cases to mount a research program on the disorder, but it seems clear that BN largely appeared as a new disorder in the lat- ter half of the 20th century. Course of Eating Disorders and Relations Between Disorders Eating disorders are often medically serious and can become chronic, although in some cases they also Eating Disorders 309 remit, with or without treatment. The onset of both AN and BN is typically in mid-to-late adolescence, although AN usually begins slightly earlier than BN, and an onset for either disorder in early adulthood is also not uncommon. With respect to AN, a total recov- ery, with normal body weight, normal body image, and no intense fears of weight gain, is rare. Fewer than 50 % of individuals with AN achieve recovery, deﬁned as normal or near-normal body weight, resumption of normal menstruation, and ea ting patterns free of severe dietary restriction, binging, or purging. Even among these ‘‘recovered’’ individuals, however, distorted body image, ongoing fears of weight gain, and other psycho- logical symptoms of eating disorders often continue. Although treatment for AN can be lifesaving in the short term, long-term recovery rates are not markedly improved for treated versus untreated individuals. About one third of individuals wi

bundet

th AN can be expected to improve somewhat, while still displaying serious eating disorder symptoms, whereas about 20 % continue to meet full criteria for AN even years later. The mortality rate for individuals diagnosed with AN is extremely high: about 5 % per decade of follow-up, higher than for any other mental disorder except heroin dependence. Most deaths associated with AN are either the result of suicide or medical abnormalities that arise as a consequence of starvation. Suicide risk for indivi- duals with AN is higher than that for any other mental disorder. The prognosis for an individual with BN is overall more encouraging, although the course of BN also is frequently chronic. Between one third and one half of individuals with BN continue to meet full or partial criteria for BN in long-term follow-up studies, although effective treatment (discussed in more detail later in this entry) appears to improve the course of BN. Less is known about the course of EDNOS; one study that followed individuals who met partial but not full criteria for eating disorders found that most still struggled with symptoms 3 years later. In fact, nearly half of these participants went on to develop either AN or BN by the end of the study. In other words, the EDNOS category includes individuals who do not necessarily have a less severe eating disorder and who may go on to develop either AN or BN. As this discussion makes clear, moving between eating disorder diagnoses is common; people initially diagnosed with AN frequently go on to develop BN, although an individual with BN subsequently devel- oping AN is somewhat less common. Also, many individuals with AN or BN improve somewhat while still retaining signiﬁcant eating disorder symptoms, thus meeting criteria for a subthreshold eating disor- der, often classiﬁed as EDNOS. Causes of Eating Disorders Genetic Influences Twin studies estimate the degree to which genes inﬂuence the development of disorders by comparing monozygotic (or identical) twins with dizygotic (or fraternal) twins to see if both members of the twin pair have a history of the disorder. When both mem- bers of a twin pair have (or do not have) a disorder, this is called concordance. If monozygotic twins are more likely than dizygotic twins to be concordant for a disorder, researchers consider this to be evidence that the disorder has a genetic component, because both monozygotic and dizygotic twins presumably share a family environment, but only monozygotic twins also share all of their genes. Twin studies in eat- ing disorders ﬁnd that concordance rates for monozy- gotic twins are higher than rates for dizygotic twins in AN, suggesting that vulnerability to AN is heritable. However, monozygotic and dizygotic twins have sim- ilar concordance rates in studies of BN, suggesting that a speciﬁc vulnerability to BN is probably not heritable. Family studies, where researchers look for evidence that a given problem runs in families by researching the relatives of people who have a given disorder, have revealed that eating disorders run in families, such that families with one person who has AN are more likely to have other members who also have AN, BN, or other eating disorder pathology. In addition, in the case of individuals with either AN or the binge-purge sub- type of BN, family members are more likely to suffer from substance abuse or dependence, as well as depres- sion. Viewed as a whole, the family and twin studies of eating disorders suggest that there may be a speciﬁc genetic vulnerability for AN and a more general genetic vulnerability to psychopathology that inﬂuences a range of psychological problems, including BN. Family Influences Certain speciﬁc aspects of a child’s upbringing or life experiences prior to developing an eating disorder have been implicated as risk factors in eating disorders. 310 Eating Disorders These include some eating and appearance-related fac- tors, such as having parents who are themselves dieting or who are critical of the child’s appearance. In addi- tion, family risk factors less obviously related to appearance or food have also been identiﬁed, including parents who are frequently absent or underinvolved in the child’s life, parents with high expectations for the child or who frequently criticize the child, and discord or conﬂict between the parents. Experiences of abuse have also been implicated as risk factors for eating disorders; sexual abuse has been most frequently researched as a risk factor, but physical abuse and neglect of a child also appear to be important. Dieting Interestingly, the practice of dieting may contribute to eating disorders, speciﬁcally by increasing the risk of symptoms of binging and purging. Early indications that dietary restriction co uldleadtoeatingdisorder symptomatology came from a famous study conducted by physician Ancel Keys and his colleagues during World War II. The goal of the study was to understand how to best treat starvation in war victims, and the research was conducted on 40 men who had been pre- screened for exceptional physical and psychological health. During the study, these men underwent a 24- week period of semi-starvation. Many of the men developed severe psychological symptoms and abnor- mal eating patterns during t he course of study, includ- ing binge-eating, food stealing and hoarding, severe depression, and even psychotic symptoms. A remark- able 50-year follow-up found that fully 25 of the original 40 participants (all who consented to be inter- viewed) reported ongoing abnormal eating behaviors and ruminations related to food that had persisted even a half-century later. The role of dieting in abnormal eating behaviors is further supported by experimental studies, which have demonstrated that when dieters are given a high-calorie food, they tend to consume more of it than do nondi- eters. They also fail to regulate their food consumption in an experimental setting; whereas nondieters will eat less of a high-calorie food if they have eaten a high- calorie food earlier, dieters eat more of the high-calorie food than nondieters do on both occasions. Such research suggests that dietary restriction under some circumstances may encourage binge behavior, which then may encourage purging. Several longitudinal stud- ies have provided support for this view by establishing that dieting behavior predicts later onset of eating dis- orders, particularly BN. Sociocultural Factors One major factor implicated in the etiology of eat- ing disorders is a cultural emphasis on the ‘‘thin ideal,’’ or an unattainably slender ﬁgure as a standard of beauty (especially female beauty, although many researchers believe that cultural pressures on men to meet an unattainable physical ideal are also increas- ing). Eating disorders are rare or unknown in cultures that do not place an emphasis on thinness as a virtue or a standard of beauty; research suggests that eating disorders increase in prevalence when cultures begin to adopt a thin ideal or among individuals migrating from a culture that does not endorse the thin ideal to one that does. Eating disorders also appear to have increased dramatically in prevalence in Western coun- tries as thinness has increased as a cultural ideal. For example, examining the weight and body size of both Miss America winners and Playboy centerfolds reveals a trend for decreasing weight over the past 50 years in women featured in these venues. Weight loss articles published in magazines have also increased over the same time frame, as has the prevalence of eating disor- ders. Some researchers believe that BN, not described until 1979, is more causally linked to sociocultural pressures than is AN, which has appeared in some form in many time periods and cultures and which appears to be more strongly heritable. Experimental research varying participants’ exposure to the thin ideal (by having some participants look at pictures of thin models or receive fashion magazine subscriptions) also suggests that participants’ body dissatisfaction and internalization of the thin ideal (as well as feelings of depression) increase with exposure to thin ideal media images. Longitudinal research shows that body dissat- isfaction and thin-ideal internalization, in turn, are related to increased eating disorder symptoms. Many researchers, however, have observed that whatever the overall inﬂuence of sociocultural pres- sures on eating disorder prevalence and symptoms, exposure to social pressures to be thin is not sufﬁcient to cause eating disorders. If it was, most people exposed to such pressures—most people living in Western cultures—would hav e eating disorders. This is not the case. Researchers therefore have developed several integrative causal models of eating disorders that typically combine biological inﬂuences, individual Eating Disorders 311 characteristics, familial and social pressures, and diet- ing behaviors to predict the acquisition of an eating disorder. Researcher Eric Stice and his colleagues, for example, developed an inﬂuential dual-pathway model of BN that posits that bulimic symptoms are caused by dieting, negative emotions, and the interaction between them, which in turn are caused by body dissatisfaction caused by pressures to be thin and the degree to which one has internalized the thin ideal. Other inﬂuential models emphasize biological and genetic characteris- tics, personality characteris tics (such as perfectionism or need for control), or cognitions related to weight and shape. Prevention and Treatment Eating disorders are difﬁcult to treat. Although inpa- tient treatment of AN does result in temporary weight gain as a result of refeeding of patients while they are hospitalized, no treatment, medical or psychological, has deﬁnitive proof of efﬁcacy in treating AN long term. A new form of family therapy for AN, the Maudsley approach, has shown a great deal of initial promise as an efﬁcacious treatment for adolescents with AN, with as many as 90 % of adolescents treated with this approach achieving long-term recovery from the disorder in clinical trials. However, as the treat- ment focuses primarily on empowering parents to work with their children in stopping the disorder, it may not be suitable for adults with AN, and research on this approach is still ongoing. In contrast to AN, several treatment approaches are known to be efﬁcacious in addressing BN. Speciﬁ- cally, both cognitive-behavioral therapy (CBT) and interpersonal psychotherapy (IPT) have good empiri- cal support as efﬁcacious treatments for the disorder. In CBT, clinicians focus on altering eating disorder behaviors and cognitions through challenging irratio- nal beliefs related to shape and weight and through monitoring and changing binging and purging beha- viors using behavioral techniques. In IPT, clinicians focus not on the eating disorder behaviors per se, but instead on helping patients identify and modify their current interpersonal problems. Both CBT and IPT appear to be equally efﬁcacious in treating BN, although patients receiving CBT appear to improve more quickly, and CBT has been more extensively researched. Although both therapies are superior to other treatments for BN (such as antidepressant medi- cation) for the average patient, only about half of the patients treated with these treatments cease binging and purging. Thus, there remains a great need for fur- ther research to identify treatments that will help those who do not improve. Because eating disorders can be so serious, and the currently available treatments are so limited, many researchers have focused attention on preventing instead of treating them. Prevention programs vary in their effectiveness. Ineffective prevention programs are primarily those which are shorter in duration (e.g., only one session in length), which present material in a didactic (rather than interactive) style, or which focus on educating participants about the disorders. More effective programs, in contrast, target indivi- duals who are at high risk for the disorders, last lon- ger than one session, and use interactive teaching methods. In addition, effective programs focus on helping participants change their level of body dissat- isfaction or internalization of the thin ideal or other factors thought to cause the disorders, rather than merely providing participants with information about the disorders. Some of the most effective prevention programs actually do not describe themselves as eat- ing disorder prevention programs at all but instead are described as body acceptance programs, emphasizing the focus on underlying causes of eating disorders. One promising and effective approach to prevention focuses on increasing participants’ discomfort with the thin ideal by asking them to dissuade others from adopting this ideal. Although prevention approaches must be carefully designed to be effective, they show great promise in decreasing eating disorders. Many researchers believe that persuading media outlets to adopt a more realistic ideal of beauty might be the most effective means of prevention of all. Other Eating Disorders Although AN, BN, and EDNOS represent prototypical eating disorders, other problems related to eating have been identiﬁed. These include both DSM-IV-TR disor- ders, such as the eating disorders of infancy and early childhood, and disorders that have been designated as deserving of further study, such as binge eating disor- der (BED). BED consists of recurrent and frequent epi- sodes of binge eating as in BN. In BED, these episodes of binging are related to feelings of distress and other problems in living, such as obesity, but unlike in BN, the individual does not engage in any compensatory behaviors to prevent weight gain and may not 312 Eating Disorders experience any distortions of body image or fears of fatness that are central to t he other eating disorders. Little is known about BED compared with the other eating disorders, but there are important differences between BED and the other eating disorders. Indivi- duals presenting for treatm ent of BED tend to be older than those with AN or BN (in middle age rather than adolescence) and are more frequently male (as many as 25 % are male). In addition, although BED seems to be associated both with obesity and feelings of depres- sion, the distress and risk associated with the disorder may be less acute than in AN or BN. In addition, it is not clear how individuals with BED who seek treat- ment differ from individuals who routinely overeat but do not experience distress related to overeating. Even more distinct and unrelated to the prototypical eating disorders are the eating and feeding disorders of early childhood, which include pica, rumination, and feeding disorder of infancy or early childhood. Pica consists of repeatedly inge sting inedible substances, such as paint, plaster, sand, or soil, in a fashion that is inappropriate to the person’s developmental level and culture. Rumination consists of repeatedly regurgitat- ing and rechewing food after feedings. Feeding disor- der of infancy or early childhood consists of a child younger than age 6 failing to eat adequately and con- sequently losing weight or failing to gain weight. None of these disorders is associated with fears of fatness or concerns about body image. In most cases, these disorders are associated with mental retardation or developmental delays, a lack of an appropriately enriching or nurturing environment, or child abuse or neglect. Margit I. Berman See also Diagnostic and Statistical Manual of Mental Disorders ; Malnutrition and Development; Obesity Further Readings Dingemans, A. E., Bruna, M. J., & van Furth, E. F. (2002). Binge eating disorder: A review. International Journal of Obesity , 2 , 299–307. Harris, E. C., & Barraclough, B. (1997). Suicide as an outcome for mental disorders: A meta-analysis. British Journal of Psychiatry , 170 , 205–228. Herzog, D. B., Hopkins, J. D., & Burns, C. D. (1993). A follow-up study of 33 subdiagnostic eating disordered women. International Journal of Eating Disorders , 14 , 261–267. Keys, A., Brozek, J., Henschel, A., Mickelsen, O., & Taylor, H. L. (1950). The biology of human starvation. Minneapolis: University of Minnesota Press. Mitchell, J. E., Cook-Myers, T., & Wonderlich, S. A. (2005). Diagnostic criteria for anorexia nervosa: Looking ahead to DSM-V. International Journal of Eating Disorders , 37 , 95–97. Polivy, J., & Herman, C. P. (2002). Causes of eating disorders. Annual Review of Psychology , 53 , 187–213. Silverman J. A. (1997). Anorexia nervosa: Historical perspectives on treatment. In D. M. Garner & P. E. Garﬁnkel (Eds.), Handbook of treatment for eating disorders (2nd ed., pp. 3–10). New York: Guilford Press. Stice, E. (2001). A prospective test of the dual-pathway model of bulimic pathology: Mediating effects of dieting and negative affect. Journal of Abnormal Psychology , 110 , 124–135. Stice, E., & Shaw, H. (2004). Eating disorder prevention programs: A meta-analytic review. Psychological Bulletin , 130 , 206–227. Wilson, G. T. (1997). Cognitive behavioral treatment of bulimia nervosa. The Clinical Psychologist , 50 , 10–12. Woodside, D. B., Garﬁnkel, P. E., Lin, E., Goering, P., Kaplan, A. S., Goldbloom, D. S., et al. (2001). Comparisons of men with full or partial eating disorders, men without eating disorders, and women with eating disorders in the community. American Journal of Psychiatry , 158 , 570–574. E DUCATIONAL T ECHNOLOGY Educational technology can be thought of as the hard- ware, software, and ‘‘thinkware’’ of learning, as well as related research theory that guides these efforts. This entry ﬁrst deﬁnes what educational technology is. Next, it presents a short history of the ﬁeld. Then it presents highlights of the hardware, software, and audiovisual technologies used by educational technol- ogists; processes and theories used by educational technologists; and research in educational technology. What Is Educational Technology? Educational technology is ‘‘the study and ethical prac- tice of facilitating learning and improving perfor- mance by creating, using, and managing appropriate technological processes and resources,’’ according to the Association for Educational Communications and Technology (AECT), the largest professional society focused solely on educational technology. Educational Technology 313 In practice, that encompasses several distinct areas of effort. One is planning and installation of technol- ogy for education. Since the mid-1970s, this technol- ogy has increasingly meant the computers used to teach and manage learning and related activities, but it also includes other hardware and operating technol- ogies, from ﬁlm and audio equipment to LCD projec- tors and other sophisticated projection systems. A second area of focus for educational technologists is educational software. Some educational technolo- gists develop learning programs that can be taken on a computer. These programs can be synchronous (occur when learner and instructor are both online at the same time, such as in a chat) or asynchronous (instructor or learner are not online at the same time, such as in a self-study tutorial). Other educational tech- nologists develop software tools that are used to develop these learning programs, such as virtual class- room software (like WebEx and Centra), used to pro- vide synchronous learning experiences, and software for creating tutorials, called authoring tools (such as Dreamweaver Course Builder and Authorware). This software focus is reﬂected in the deﬁnition of educa- tional technology offered by the International Technol- ogy Education Association (ISTE): ‘‘Using multimedia technologies or audiovisual aids as a tool to enhance the teaching and learning process.’’ A third focus of educational technologists is the processes and products used to design instruction. In these applications, technology refers to the sequence of activities and the applications of cognitive psychol- ogy to the design of instruction, rather than a physical hardware or a type of software. These activities are known as instructional-design ,asphrasedbyCharles M. Reigeluth. In terms of academic study, educational technology is available as an academic degree from universities in nearly every U.S. state, as well as in Australia, Canada, the United Kingdom, and several countries in the Mid- dle East and Asia. In its most academic form, educa- tional technology explores the following: the models and processes used to analyze, design, develop, deliver, implement, and evaluate instruction; the technology used to support these processes—both analogue and computer-based—in order to deliver learning materi- als, facilitate communication, and provide assessment and feedback; the policies associated with these prac- tices; and the research that informs practice. The academic study of educational technology explores learning throughout the life cycle, from preschool through retirement education. Similarly, because educational technology encompasses technol- ogy, learning, and design, it is an interdisciplinary ﬁeld that draws upon other ﬁelds such as educational psychology, developmental psychology, early child- hood and elementary education, higher education, adult education, computer science, ergonomics, soci- ology, and communications studies. History Educational technology emerged as a ﬁeld in its own right in the 1920s, though some point to the initial development of human communications as one of the ﬁrst developments in educational technology, because these facilitated the exchange of knowledge between members of tribes and from generation to generation. The invention of writing and writing instruments, such as papyrus and pens, further facilitated that process. Modern educational technology charts its roots to the advances in media occurring in the late 19th cen- tury, such as inventions of visual and audio recording and playback devices. Soon afterward, each found its way into education, as educational ﬁlms (the ﬁrst appeared in the early 20th century), educational records, and the use of photographs in textbooks. During the 1920s and through the 1940s, with advances in other media, such as audio recordings, radio, and motion pictures, th e focus shifted from visual instruction to audiovisual instruction. This trend contin- ued through the 1950s with the advancement of televi- sion. At this point in time, educational technology focused primarily on the use of instructional media, and the ﬁeld was commonly known as instructional technol- ogy. In the 1950s, and most notably in the 1960s and 1970s, educational technology became more and more complex. It grew from a discip line concerned primarily with instruction using audiovisual aids to one concerned with systematic instructional design. At the same time, the ﬁeld of education began to see instructional technol- ogy as a process that looks at instructional problems and explores solutions to these problems. As technological advances exploded with the com- puter revolution, educational technology became a complex, integrated process that became increasingly professionalized. The AECT developed a new deﬁni- tion of the ﬁeld in 1977 that included the importance of the planning and analysis phases of instructional design. This deﬁnition also included a list of learning resources and clariﬁed terms such as learning problems 314 Educational Technology and solutions. This new deﬁnition emphasized that instructional technologists were interested in more than just the development and use of media. The discipline began to attract individuals from various disciplines. With the growth of the microcomputer, Internet, interactive video, and other communication technolo- gies, educational technology has become accessible to the general public and to most organizations. In addi- tion, behavioral learning theories, which previously served as the basis of instructional design, gave way to cognitive and constructivist theories. These develop- ments led to a growing interest in the development of instructional strategies that incorporated these new developments. As a result, in the mid-1990s, a new deﬁnition of educational technology emphasized the main areas of study and practice in the ﬁeld; design, development, utilization, management, and evaluation. The interrelationship of these domains emphasizes the link between teacher, learner, and instructional method. The profession is now more concerned with the appli- cation of a variety of instructional techniques, ranging from traditional lecture approaches to open-ended dis- tance learning environments. In the new millennium, the ﬁeld has continued to grow and change as society and learners evolve. The number of universities and the expansion of mass edu- cation along with the inadequate funding provided by governments, as well as the increasingly heterogeneous background of learners, are just some of the challenges. Increasing numbers of knowledge workers are seeking jobs that correspond to new job requirements. With the Internet, there has been an explosion in the volume of information and potential knowledge available. All of theseadvanceshaveledtoamoreindividualizedtype of education that is geared to speciﬁc needs, an educa- tion that is sometimes distance-oriented but primarily subject-speciﬁc. As technol ogy becomes increasingly complex, there is a greater need for professionals who are able to train and help users become adept and skill- ful in the use of the new technologies. Although many in the ﬁeld continue to work on media and tasks related to th e instructional process, many work in processes that are inﬂuencing the world as a whole. As the world outside the university changes dramatically, there is an increased demand for highly skilled workers, who need to be continually learning and improving their professional technical skills. As a result, educational technologists have been paying more attention to improving workplace performance and knowledge management. As the academic world gradually adapts to the real world of technological and societal changes and lifelong learning becomes critical to economic growth and development, the ﬁeld of edu- cational technology responds. There is an increased emphasis on independent learning, on developing social skills and teamwork, on adapting to change, and on developing thinking and problem-solving skills. As the volume of available information expands, it has become increasingly important to develop systems that can help people get at and process this information. Educational technologists are active in all these various areas. Hardware, Software, and Audiovisual Technologies One area of focus within educational technology is the applications of technology in learning. Technolo- gies generally fall into these categories: • Technologies for teaching and learning • Technologies for facilitating communication among participants in the learning process • Technologies for facilitating evaluation • Technologies for managing learning activities Because standardization of technology is essential to the smooth integration of technology in education, any discussion of technology also addresses standards. Technologies for Creating Learning Materials Some argue that the ﬁrst educational technologies include writing systems, papyrus, and the writing instruments on which to place characters on the papy- rus. One of the purposes of ancient documents was to record history and key lessons so that future genera- tions might learn from them. But the modern practice of educational technology begins with the introduction of audiovisual technol- ogy in the late 19th and early 20th centuries. The technologies can be categorized as follows: Technologies for designing and developing the mate- rials. Most of these technologies were developed for assisting with the creation of content. One of the earli- est technologies was the typewriter, which enabled people to create content faster, more legibly, and more consistently. Later versions of typewriters included the ability to correct errors, change the look of the typeface, and save content, so revisions would not require retyping. The advent of computers brought Educational Technology 315 about word processing, software that lets authors write, change, revise, and print text; desktop publish- ing, which allowed the low-cost production of high- quality educational materials (before that, material was prepared by hand with highly skilled labor); and software for publishing materials online, including the HTML standard that lets Internet browsers like Mozilla Firefox and Internet Explorer display content produced from a variety of sources. Whereas none of these technologies was speciﬁcally produced for edu- cational purposes, there was one that was: the author- ing system, which is used to create online learning programs for people with little or no knowledge of computer programming. This software lets authors not only create the content but also determine what it looks like and test learners’ understanding of the con- tent. One of the ﬁrst major authoring systems was PLATO; it appeared in the late 1960s and was intended for mainframe computers. In the mid-1980s, several key authoring systems for microcomputers emerged, including the Hypercard for the Apple com- puter, which also had other purposes and was intended for people with limited computer literacy, and Authorware, which was more sophisticated. Technologies for producing the materials. This cate- gory includes equipment for recording visual images (photography, ﬁlm, and video cameras, as well as related lighting) and audio (sound recorders, micro- phones). It also includes equipment for developing photographs and editing visuals and sounds together into a single, coherent product. In the past, this equip- ment worked with analog technology. Since the early 1980s, recording and production have converted to digital technologies. Note that these technologies were not developed speciﬁcally for use by educational tech- nologists. However, the price consciousness of many educational technology departments provided incen- tives to manufacturers to develop more modestly priced versions of this equipment. Technologies for reproducing the learning materials, which involves making copies of audiotapes, ﬁlms, books, articles, and similar materials. These technol- ogies were not developed speciﬁcally for educational technologists, and many educational technologists use outside companies to handle these tasks (and, there- fore, have limited exposure to them). Technologies for playing the recordings or using the content, which involves the use of specialized projectors and similar playback equipment that often cost thousands of dollars. For audio, playback equip- ment includes record, tape, CD, and MP3 players. For visual recordings, playback equipment includes ﬁlm- strip and slide projectors. For combinations of audio and visual recordings, playback equipment includes ﬁlm projectors and screens and video players and monitors. Audio and visual recordings have also been synchronized, such as slide-sound shows in which a slide projector automatically advances a slide show when it hears a special sound from a tape recorder. More recently, playback is available on computers, personal DVD players, and personal digital assistants, like PalmPilots and iPaqs. Playback equipment also includes equipment for projecting these visual images so large audiences can see them. Projection equipment includes screens, LCD projectors, large screen moni- tors, and rear-projection systems. Although none of these technologies was developed speciﬁcally for the educational environment, versions of the products were adapted speciﬁcally for educational environments. Most of the technologies for creating learning materials require specialized knowledge. As a result, the curricula of many academic programs in educa- tional technology programs include components on the use and operation of this equipment. Technologies for Facilitating Communication Among Participants in the Learning Process A second group of educational technologies is intended to facilitate communication between instruc- tors and learners. These technologies can be catego- rized as follows: Technologies for facilitating communication among the participants in the learning process. In the late 19th and early 20th century, these technologies pri- marily included mail and telephone. Both types of communication were intended for person-to-person communication. With the advent of computer-based technologies, several new options emerged. Some provided for person-to-person communication, includ- ing electronic mail (e-mail), Internet telephony, and instant messaging (IM). Other options offered by the computer included group-based communication. Early options included discussion lists (also called listservs, which are ongoing e-mail exchanges among a group of registered participants) and discussion boards, 316 Educational Technology programs that manage discussions on a class of topics. With the advent of social computing on the Web are wikis, which allow a group to rapidly create a work product together online, and blogs (short for ‘‘web logs’’), which are like online columns from a newspaper or diaries, and to which readers can leave comments. Technologies for replicating the classroom through technology. These technologies allow students to par- ticipate in class when they might not otherwise be able to, because of physical condition, time con- straints, or geographic constraints. Early technologies for replicating the classroom include radio (such as the bush radio used in Australia) and conference calls by telephone. By the mid-20th century, television classrooms emerged (in fact, the use of television for learning was one of the reasons for establishing the U.S.-based Public Broadcasting System, as well as several academic educational technology programs, like the one at Concordia University in Montreal, Canada. Although some uses of television were based on public broadcast, private, closed circuit television systems also were used, such as the University of Minnesota’s UNITE system and IBM’s Interactive Satellite Education Network. Most closed circuit net- works had two-way communication ability, which means that not only could students see and hear the instructor, but the instructor could see and hear the students. By the mid-1990s, software had been devel- oped that allowed educators to create a classroom-like environment online. Called virtual classroom soft- ware, this software lets instructors speak, show images, and interact with students in large and small groups and lets students interact with their instructors. Technologies for Facilitating Evaluation A third group of educational technologies is intended to facilitate the process of evaluating the learning process. A technology from the latter half of the 20th century is Scantron, which lets instructors automatically grade exams with objective questions (true/false, multiple choice) by having students ﬁll out a form that can be read by the grading machine. Most of the developments in this area of educational technology occurred after computers came into com- mon use. Some of these technologies focus on grading a particular assignment. One is software that conducts entire tests online. Original versions of this software limited educational technologists to objective ques- tions, but later technologies have allowed instructors to ask open questions (like e ssay questions) online. In most instances, instructor s need to grade those answers themselves. Although som e software has been devel- oped to grade open questions, it is not yet in common use. A related technology lets instructors assess the likelihood that an essay or si milar written assignment is plagiarized. Other computer-based technologies for evaluating learning focus on broader issues. Portfolio software lets learners create a process portfolio, which allows them to include a class assignment and comment on what they learned from the assignment. An instructor, advisor, parent, or peer can review the assignment and reﬂections and offer feedback. Another is analyt- ics software, which lets an administrator or manager compile statistics from a variety of computer-based sources, such as information about students, enroll- ment, and grades, and identify larger trends in the operation. Some of these analyses are presented as dashboards (e.g., the analysis of the American Society for Training and Development), which look like the dashboard of a car with a large number of indicators. When a problem seems to be arising in one of the indicators, the system visually signals the manager by turning that indicator red or orange. Technologies for Managing Learning Activities A fourth group of educational technologies is intended to manage learning activities. These technolo- gies assist with the management of class activities as well as broader activities o f the organizations that sponsor learning. Technologies for managing learning activities include learning management systems, course management systems, and learning content manage- ment systems. Learning management systems. Learning manage- ment systems (LMSs), which act as electronic regis- trars, perform some or all of the following tasks for both online and classroom courses: • Registration • Tracking of participation (classroom attendance, sign-ons and sign-offs of online courses) • Tracking of completions (including ﬁnal scores or grades) • Testing • Providing aggregated reports, such as the numbers of people registered for particular courses Educational Technology 317 • Sharing information with other systems, such as human resource information systems • Suggesting curricula for learners • Tracking skills of individuals and groups of people within an organization • Providing learners with a one-stop shop for their learning needs (especially online programs) and per- sonalized information, such as a customized learn- ing page that includes recommended paths through learning material Examples of LMSs include Saba, Plateau, and NetDimensions EKP. Course management systems. Course management systems (CMSs) were originally designed to support classroom learning in academic settings, such as uni- versities and high schools. CMSs provide instructors with the ability to do the following: • Place course materials online. Most CMSs provide preprogrammed buttons for the course syllabus, course schedule, and course materials linked to spe- ciﬁc lessons, such as copies of readings and Power- Point slides from lectures. • Track student progress, through assessment features (which let instructors give quizzes and tests online) and an online gradebook, where instructors can post student grades. • Discuss readings with students and continue class discussions between formal class sessions, through the use of a discussion board. • Send announcements to classes and communicate individually with students. • Provide a lock box for students, where students can store class materials (e.g., a presentation to give later in class). • Track course statistics, such as who used the course site and when. Examples of CMSs include the commercial pro- ducts Blackboard and WebCT and the open source system Moodle. Learning content management systems. Learning content management systems (LCMSs) are software for creating, storing, retrieving, changing, and reusing material intended for use in an online learning pro- gram. LCMSs also store test questions and can be used to track activities in developing material. Finally, LCMSs can format the same content for presentation online and in print, and with a number of word pro- cesses. Examples of LCMSs include Eedo Force 10 and OutStart. Note that many LCMSs also have the registration and management functions of an LMS. Standards for Learning Technology Standards refer to rules that have been set up by various professional and trade organizations to address a variety of aspects of the development and production of learning content, so that content pro- duced in one organization and on one brand of equip- ment can be easily used in another organization on another brand of equipment. Although all types of learning technologies involve the use of standards (e.g., how to take a photograph and ensure that the slide projector plays it), standards have only become a signiﬁcant concern to educational technologists with the advent of online learning. In technology for learning, a standard represents the last phase in a series of milestones intended to develop an idea for coordinating interactions among software and devices. The ﬁrst phase results after someone or a group of people recognize a situation in which some coordination of efforts wil l result in more efﬁcient or economical interactions among programs or some simi- lar beneﬁt to users. In many ways, this idea is similar to that proposed by Geary Rummler and Alan Brache for human performance technology. They note that efﬁciencies and improvements are often achieved by examining and reengineering the interactions among groups within and across organizations. Processes and Theories The ﬁeld of educational technology is guided by a family of processes that form the core of most aca- demic programs and are widely acknowledged by most practitioners. These processes are also part of introductory training to people who work in the ﬁeld but do not have academic backgrounds in the ﬁeld. The core process followed by educational technol- ogists is known as instructional systems design ,which is the recommended process used to design, develop, and implement learning programs. Although more than 40 versions of this process exist, the core of each is the same and is known as ADDIE, for analysis, design, development, implementation, and evaluation, Analysis. To identify the desired outcomes, the current performance, and the reason that the gap between current and desired performance exists. Analysis also identiﬁes the intended learners, as well as the 318 Educational Technology conditions that affect the design, development, and delivery of the course, such a s a tight deadline and a pref- erence for learning in a particular format. The products of the analysis process are a set of behavioral objectives, which deﬁne the learning outcomes, and a test or similar assessment, which can be us ed to determine the extent to which learners have mastered those objectives. Design. To turn the requirements into a learning pro- gram. During design, the educational technologist determines the medium of instruction—such as class- room or computer-based tutorial—and the format of the course. The educational technologist also deter- mines the learning strategy to apply—that is, the approach to presenting and reinforcing the learning content, such as a mastery or discovery approach to learning. In many organizations, educational technolo- gists also prepare storyboards (initial drafts) of learn- ing materials at this time. Development. To convert the design intentions into a working learning program. The actual activities vary, depending on the type of course, but usually include preparing several drafts of the content and obtaining reviews by subject-matter experts and editors and other educational technologists, and piloting tests (i.e., trial uses of the content) with intended learners. Implementation. To make the learning program avail- able to its intended learners. The actual activities vary, but they usually include announcement of the avail- ability of the program, registration, and offering of the learning program. Implementation also encompasses the activities involved in operating a learning program, such as setting up a classroom or providing technical support for computers on which tutorials are taken. Evaluation. To determine the extent to which the learning program achieved its objectives. Although some refer to ADDIE as a model, it is neither descriptive nor predictive of actual practice. Several empirical studies suggest, instead, that although ADDIE is an ideal process, practicing pro- fessionals do not follow it. Rather, ADDIE is pre- scriptive of ideal practice in the ﬁeld. Guiding each phase of ADDIE are additional pro- cesses, theories, and methods. For example, guiding the development of objective s are approaches popular- ized by Bob Mager in the 1960s. There are a number of approaches that guide design. Some pertain to the use of—and choice of—media, best characterized by the debate between Richard Clark and Robert Kozma on the role of media in instruction. Some approaches focus on appropriate strategies for designing instruc- tion. Among the most popular (but certainly not an exhaustive list) are Robert Gagne’s nine events of instruc- tion; John Keller’s attention, relevance, conﬁdence, and satisfaction (ARCS) model; and problem-based learning (D. H. Jonassen). Guiding the development of learning programs are such approaches as advance organizers, theories of document and information design, and even the appropriate use of audio and visual cues. Different approaches guide evaluation, depending on the level of education. Guiding most of them is the belief that assessment should focus on the extent to which learners can accomplish the learning objectives (known as crite- rion-referenced testing ). Although high-stakes testing— that is, standardized tests to assess the performance at a particular grade level—is the type of assessment best known in primary and secondary education, using portfolios to help both learners and teachers evaluate learning is gaining much interest among educational technologists. In terms of evaluating training, Donald Kirkpatrick’s four-level approach is the most dominant. It evaluates satisfaction, learning, transfer of learning to on-the-job behavior, and the impact of the learning on the organization. In addition, some educational technologists are guided in their work by the principles of human per- formance technology (HPT). HPT frames most issues addressed by its practitioners as performance pro- blems. Such problems might result from a lack of knowledge and skills and can be solved by learning programs. But performance problems might also emerge from a lack of resources (e.g., receiving train- ing on a new software program but not having access to that program) or motivation (e.g., fearing the loss of a job resulting from new technology). Learning programs will not solve problems resulting from a lack of resources or motivation; these problems require different types of interventions. HPT emerges from the workplace. Although its advocates claim that HPT applies to all of the environments that educational technologists address, the overwhelming body of evi- dence is focused on the workplace. Research and Theory Research in educationa l technology has four key streams. The ﬁrst stream of research focuses on the design ofinstruction.Earlyresearchtendedtofocuson Educational Technology 319 the design of individual lesso ns and courses. Some stud- ies focused on validating a pa rticular design strategy. For example, studies in the 1950s and 1960s focused on applications of programmed instruction, a type of instruction that breaks learning down to its smallest tasks and involves teaching a topic one micro task at a time. Other studies compared instruction in different media, such as online versus classroom instruction. The dominant research methods used for both types of studies was experimental (either control group or quasi- experimental). In many cases, researchers present expe- rience reports, that is, reports and some research results based on their own classroom experience. More recently, research in this area has focused on learning sciences, which, as deﬁned by the International Society on Learn- ing Sciences, uses ‘‘empirical investigation of learning as it exists in real-world se ttings and how learning may be facilitated both with and without technology.’’ Stud- ies explore issues of learning, teaching, and design and often employ qualitativ e research techniques. The second stream of research is similar to the ﬁrst but focuses on applications of hardware and software technology to learning. In the earliest days of the ﬁeld, the research focused on the use of ﬁlm and audio recordings for learning. As television came into wider use, research focused on its use. In fact, the use of tele- vision for learning gave a boost to the ﬁeld, because many governments wanted to use television in teaching at all levels. Since the 1980s, most of the research has focused almost exclusively on uses of computer tech- nology in learning. Some of the research attempts to provide proof-of-concept for speciﬁc technologies in well-deﬁned learning contexts, such as uses of intelli- gent tutoring in mathematics and classroom response monitoring systems (in which students are provided with a key pad to type in responses to multiple-choice and similar questions) in large classes. Some of the research explores ways to use technologies, such as some of the recent research on mobile learning (learn- ing using personal digital a ssistants, like PalmPilots) and podcasting (use of audio and video recordings broadcast on MP3 players like an iPod). Some of the research focuses on the technology used to manage learning, such as LMSs, which are widely used in the workplace to help workers enroll in and take courses, and CMSs, which are widely used in universities to help extend the classroom experience online by provid- ing a place where instructor s can distribute syllabi, assignments, and readings, as well as hold ongoing dis- cussions with learners. This research often takes the form of experimental and qua si-experimental studies, but similar to research on the design of instruction, it increasingly incorporates qualitative techniques. The third stream of research focuses on resources that complement the learning process. Often, these studies explore phenomena that are both a type of learning program and a type of software. For exam- ple, according to David Wiley, one area of great inter- est in the ﬁrst half of the 2000 decade is reusable learning objects, which are materials designed for learning in one context but available for use in others. Also of great interest are portfolios, especially elec- tronic ones, which, as mentioned earlier, are used for evaluation of learning. The last stream of research focuses on the practice of educational technology. Most of this research focuses on the practice of instructional design. Some studies focus on which skills instructional designers use on the job; others focus on how extensively instructional designers practice ADDIE. Most of these studies are survey-based, but some of the more extensive ones use methodologies like developing a curriculum (DACUM) and are the basis of certiﬁcations in the ﬁeld. In addi- tion, some recent studies partially or completely employ qualitative techniques to compile rich description of the environmental factors affe cting the design of learning. Regardless of the stream of research, most research in educational technology tends to have a ‘‘micro’’ focus, that is, a focus on individual learning situa- tions, such as a comparison of a course taught in two different environments or the application of a particu- lar technology to a particular learning problem, such as the design of an intelligent tutoring system for solving a particular type of mathematical problem. The early use of the expe rimental technique in research on educational tec hnology is representative of the ﬁeld’s roots in behaviorism. Indeed, many of the early researchers in educational technology, such as Tom Gilbert and Robert Gagne, had worked with B. F. Skinner. But the ﬁeld has inc reasingly embraced cogni- tivism and constructivism, as researchers become aware of the situational nature of learning and want to ﬁnd stronger ways to reﬂect that in the research. One of the many responses to this shift is design research, which attempts to study the development of a course and use the research to inform its ongoing development. Saul Carliner, Ofelia Ribiero, and Gary Boyd See also Assessment; Curriculum Development; Learning 320 Educational Technology

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L LEARNING LEARNING COMMUNITIES LEARNING DISABILITIES LEARNING OBJECTIVES LEARNING STRATEGIES LEARNING STYLE LEAST RESTRICTIVE PLACEMENT LIFELONG LEARNING LITERACY LONGITUDINAL RESEARCH LONG-TERM MEMORY helplessness include the failure to initiate action, failure to learn, and emotional problems such as depression. There are several ways that teachers can inﬂuence stu- dents’ outlooks on learning, including attribution retrain- ing, encouragement, and focusing on mastery goals. Research Seligman and colleagues were the ﬁrst to manipulate learning deﬁcits by exposing animals to inescapable aversive stimuli. Their phrase learned helplessness was used both as a description and a theoretical expla- nation of the observed learning deﬁcits. In typical learned helplessness laboratory studies, researchers would ﬁrst expose dogs to a series of inescapable electric shocks. Up to 24 hours later, the researchers put the dogs in the same situation except that they could now avoid or terminate the shocks by simply stepping over a small fence into another part of the training box. If the dog did not terminate or try to escape from the shock, Seligman and colleagues des- ignated it as exhibiting learned helplessness; they believed the dog had learned that nothing it could do would matter. Researchers extended this animal model of learned helplessness to humans, although the experiments were considerably less aversive. Experiments with humans would present irritating noises instead of electrical shock, but the results were still similar to the results with dogs. In one classic study, researchers exposed participants to a loud noise. During the ﬁrst set of trials, the participants in the contingent control group could stop the noise with the simple pressing of a button; in contrast, participants in the noncontin- gent ‘‘helpless’’ group could not stop the noise. In the second set of trials, both groups could move a knob to avoid a signaled noise. Despite the change in contingencies, the participants previously exposed to the uncontrollable noise sat passively and did not attempt escape. In contrast, participants from the response contingent control group and an additional no-noise control group quickly learned to escape the noise by simply moving the knob. Seligman and colleagues concluded that humans, like dogs, develop learned helplessness when exposed to uncontrollable aversive stimuli. Further research on learned help- lessness in humans shifted to using unsolvable prob- lems or puzzles as the uncontr ollable aversive stimuli. Researchers have subsequently found remarkable individual differences in children’s responses to unavoidable failure on cognitive tasks, which has led to the educationally important question of why some succumb to learned helplessness and others do not. Attributions and Learned Helplessness Two children, each of equal ability, are given a puzzle to solve. As long as they are successful, both appear to be motivated and energetic in their approach. But, if this ﬂow of success is interrupted with a set of very difﬁcult or unsolvable tasks, two divergent motiva- tional patterns might be seen. Some children face and recover from failure in a manner that is highly resilient. They appear emotionally unaffected by their experience of failure, simply using failure as an additional source of information. Their performance quickly rebounds once given solvable problems. In contrast, other children appear to crumble in response to perceived or even anticipated failure. These nonre- silient children may regress to a lower level of skill than they began at, exhibit negative affect, and con- clude that they lack ability. What causes one child to respond resiliently to failure while another gives up? One explanation is attribution theory; differences in susceptibility to learned helplessness are the result of the causal attributions persons make for the aversive situation. An attribution is the causal explanation one makes to explain events. Attribution theory’s explana- tion of learned helplessness asserts that when persons perceive noncontingency, they search for a causal attribution to explain it; this attribution then mediates their response. For example, if failure is attributed to a lack of effort, the response will be resilient. If fail- ure is attributed to lack of ability, then learned help- lessness will result. After considerable research on learned helplessness in humans, Lyn Abramson, Seligman, and John Teas- dale reformulated the animal-based model of learned helplessness. This reformulated model, drawn from attribution theory, uses three dimensions of attribution to explain the generalization and impact of perceived failure on performance. The ﬁrst dimension is locus on control , which deﬁnes the cause of an outcome as being either internal or external to the individual. For example, the teacher behavior would be an external cause of success or failure, but individual ability would be an internal cause. The second dimension of Learned Helplessness 571 attribution theory is stability. Some causes of success or failure are assumed to be stable, whereas other causes can change. External causes such as luck are generally believed to be unstable, but internal causes such as ability are often believed to be very stable. The stability dimension is linked to success expec- tancy. If success is attributed to unstable causes (i.e., luck), then students may believe that their chance of success is unlikely. Globality is the third dimension of attribution theory. A student may attribute failure to a global cause (‘‘I’m just not good at math’’) or to a speciﬁc cause (‘‘I only failed because I was too sick to come to class!’’). Global attributions assume help- lessness will occur in a broad number of situations, thus implying that helpless situations are unavoidable. In contrast, speciﬁc attributions conﬁne helplessness to very speciﬁc situations, thus implying that success is possible with only small situational modiﬁcations. Attribution theory posits that the causal attributions (internal or external, stable or unstable, global or speciﬁc) persons make about aversive situations deter- mine susceptibility to learned helplessness. Motiva- tional deﬁcits associated with learned helplessness include task withdrawal or avoidance. Emotional deﬁ- cits associated with learned helplessness include sad- ness, fear, frustration, anxiety, and depression. For example, global and stable attributions generalize learned helplessness across tasks and time. In contrast, speciﬁc and unstable attributions limit the generaliza- tion of learned helplessness. Stable and global attribu- tions for failure often contribute to helpless behavior, but internal attributions for failure can go either way. For example, effort is an internal attribute, but because it is also unstable (you can apply it, or not), blaming failure on a lack of effort does not tend to lead to helplessness. Interestingly, stable, global, and internal attributions for success increase resiliency to subsequent failure. Seligman, Alloy, Abramson, Teasdale, and others have developed a learned helplessness theory of clini- cal depression based on attribution theory. This theory suggests that persons who tend to make stable, inter- nal, and global attributions for negative events are vulnerable to depression. Depressed individuals often believe that they have little control over either nega- tive or positive events in their lives. In sum, the attri- butional theory of learned helplessness asserts that individual differences in vulnerability to helplessness, and even depression, are the result of individual dif- ferences in attributional style. Current Perspectives on Learned Helplessness The learned helplessness explanation of performance deﬁcits following perceived failure focuses on beliefs about the contingency of behavior and outcomes; in plainer words, ‘‘I have not succeeded because it is not possible for me to succeed . . . therefore I give up.’’ This, however, is too simplistic an explanation of differ- ences in achievement resili ency. Consider the boy who, after studying hard, fails a t his ﬁrst math test of the year, then consequently refuses to study for the next test. Is learned helplessness the best explanation for this motivational change? A signiﬁcant body of thinking and research has argued that ego threat, not perceived noncontingency, is the real motivator. From this ego threat perspective, the need to protect one’s sense of self-worth from displays of low ability can motivate a variety of behaviors, including the task withdrawal described by learned helplessness researchers. Recent research in educational psychology has found ego or self-worth maintenance to b e a more fertile approach to achievement motivation and failure resiliency than just learned helplessness. Attribution theory and learned helplessness are integral aspects of current achievement motivation theories, but they are not adequate stand- alone explanations. Another interpretation of helpless- ness is physiological rather than cognitive. That is, when inescapable shock is presented, there is a decline in the neurotransmitter norepinephrine. This decline has been associated with helplessness behavior. Learned Helplessness in Students With Learning Problems Research has found that susceptibility to learned help- lessness varies considerably from individual to indi- vidual. Learned helplessness is related to a variety of individual characteristics: anxiety, depression, low self-efﬁcacy, low mastery and high performance orien- tations, low self-worth, extrinsic motivational orienta- tion, and need for structure, to name a few. Students with learning problems, however, may be particularly vulnerable for learned helplessness. Students who repeatedly encounter academic difﬁculties come to expect failure, which generalizes to low self-efﬁcacy, which inhibits effort, which guarantees further aca- demic failure, which, by reinforcing failure expecta- tions and low self-efﬁcacy, returns the student to the beginning of this vicious cycle. Even when success is 572 Learned Helplessness experienced, these students may attribute it to external causes, for example, believing that they succeeded at a math problem because it was easy, because they received help, or because they were simply lucky. However, not all students with learning problems dis- play helplessness; some are quite resilient. The fre- quency of failure may be an important factor: Students who fail in multiple domains may be more susceptible to developing learned helplessness. In addition, reading difﬁculties are especially important, as reading skills determine success in many other domains of competence. What Can Educators Do? Teachers can provide students with feedback on the attributions they make about the causes of their suc- cess and failure, and they can model healthy attribu- tions. Progress toward goals and success should be attributed to internal attributes such as effort and abil- ity, but failure should be attributed to internal unstable attributes such as effort. In addition, teachers should provide moderate difﬁculty tasks that students are able to accomplish with effort. Success on tasks that are too easy does not produce healthy ability or effort attributions, and failure on tasks that are too difﬁcult usually results in unhealthy, low ability attributions. Teachers can help students by explaining the role that attributions play in the learning process. For exam- ple, students can be encourag ed to focus on controllable factors such as effort and st rategies, rather than uncon- trollable factors such luck or mood. Students can be taught to consider other causes of success and failure. Students experience difﬁculties in class for several rea- sons. For example, these reasons may include not using appropriate learning strategies, or lacking prior knowl- edge. These factors are often controllable, and students should recognize that many failures may be attributable to these changeable factors. Research shows that attri- bution retraining is an effective intervention for learned helplessness. By increasing students’ awareness of the attributions they make, their self-esteem, self-efﬁcacy, and learning can be improved, and their anxiety and frustration can be reduced. Another approach is to encourage children to focus on mastery goals, or learn- ing for its own sake. Mastery goals increase actual com- petence, which in turn increases self-worth and achievement motivation. Focusing on grades, the approval of others, and competition are performance goals. Performance goals work ﬁne as long as the student is winning; however, failure at a performance goal can produce ego-protec tive maneuvers that inter- fere with learning. Over time, performance goals make learners susceptible to learned helplessness. Jennie K. Gill and Joan M. Martin See also Failure, Effects of; Learning; Motivation; Self- Efﬁcacy; Self-Esteem Further Readings Abramson, L. Y., Seligman, M. E. P., & Teasdale, J. D. (1978). Learned helplessness in humans: Critique and reformulation. Journal of Abnormal Psychology , 87, 49–74. Alloy, L. B., & Abramson, L. V. (1982). Learned helplessness, depression and the illusion of control. Journal of Personality and Social Psychology , 42 , 1114–1126. Buchannan. B. M., & Seligman, M. E. P. (Eds.). (1995). Explanatory style. Mahwah, NJ: Lawrence Erlbaum. Maier, S. F., & Seligman, M. E. P. (1976). Learned helplessness: Theory and evidence. Journal of Experimental Psychology: General , 105 , 3–46. Seligman, M. E. P. (1975). Helplessness: On depression, development, and death. San Francisco: Freeman. L EARNING Human learning has been the focus of organized study for many decades, and the results of this work have become ever more important as societies intervene on so many levels to promote and inﬂuence learning. Today there is no one single way to deﬁne learning. Rather, what is found is a range of explanations, each of which provides an important frame of reference for thinking about learning as a human endeavor. Gener- ally speaking, over the past 60 years, three major con- ceptual frameworks have emerged, and these three will be the focus of this entry. The ﬁrst of these frameworks looks at learning in terms of observable behavior. In simple terms, learn- ing is deﬁned as any relatively permanent change in behavior that is not the result of normal growth or maturation. There is no limit to the range of behaviors that might be considered or the contexts in which they occur. When people drive automobiles or operate machinery, perform school tasks such as writing and calculating, or engage in social activities with others, generally their behaviors are fairly complex behaviors that have been acquired over time and with much Learning 573 practice. People who study learning from a behavioral perspective want to know how these complex behav- iors are acquired and how they change over time. The second framework, which began to appear in the late 1960s and early 1970s, deliberately moved away from behavioral explanations, focusing instead on the information-processing activities that occur in the human brain. This movement, known as the cognitive revolution in human learning, developed largely around questions about memory and meaning. For example, when a person listens to people talk—or reads from text—how does he or she process and store what was heard or seen? How does the person represent informa- tion in memory for later use, and how does he or she gain access to the large amount of stored data? These and other related questions have dominated the study of learning for many decades, and they continue to be pro- minent in researchers’ thinking about learning. Thus, viewing learning as a cognitive activity, it can be deﬁned as the acquisition of knowledge and the ability to use knowledge to solve problems. A third framework for investigating human learn- ing began to be noticed during the early 1990s. In contrast to the cognitive point of view, in which learn- ing is deﬁned in terms of an individual’s computation of information, this framework focuses more on how people work and learn in cultural settings. Here learn- ing is deﬁned not as the acquisition of knowledge but as participation in meaningful social practices. Exam- ples of cultural practices naturally include a broad range of activities, such as child rearing, ofﬁce work, professional endeavors, trades, hobbies and the like. As people participate in social practices, they develop roles relevant to their particular type of participation, and as these roles develop, people acquire identities as legitimate practitioners. One important distinction between this framework and the cognitive viewpoint is that in this framework, learning from a social per- spective is never separated from doing. When looking across this history of progress in learning research, there is a natural temptation to sim- ply focus on the latest prominent explanation that may be enjoying most attention. Certainly today there is very little discussion of behaviorism as a viable framework for understanding learning. In fact, the intention and purpose of the cognitive revolution was not simply to modify behaviorism but to replace it altogether. It can be argued, however, that each of the three frameworks outlined here provides an important window on learning and allows us to see human learning as the rich and multifaceted phenomenon it really is. Learning as Behavior Change Learning from a behavioral perspective involves exam- ining the relationship between what animals or humans do (i.e., their responses) and what the environment does (i.e., various stimulus events). When behavior changes systematically in relation to environmental stimuli, behaviorists refer to such learning in terms of a conditioning process. A modest complexity in this is that two types of conditioning are possible, and they are based on different l earning principles. Classical Conditioning Based on the work of Ivan Pavlov, the classical or Pavlovian model is rooted in simple reﬂexive behavior. The basis for this model lies in the range of relatively permanent and unlearned reﬂexes that nearly all members of a species possess. Examples include our automatic reactions to hot surfaces, food smells, and a whole range of stimuli tha t may cause fear, anxiety, ﬂight, or a sense of well-being. These automatic reﬂexes are composed of two elements: an uncondi- tional stimulus and an unconditional response. Again, no learning is required for these responses to take place. Where the learning, or conditioning, comes in is when another neutral stimulus is introduced in just the right way when these automatic reﬂexes are occurring. The classic experiments from Pavlov’s laboratory involved his work with the digestive process in dogs. As the story goes, Pavlov noticed that not only would dogs salivate in the presence of food (this is the uncon- ditional stimulus-unconditional response reﬂex), they also would initiate the salivary secretions even before the food arrived. This curious phenomenon set Pavlov on a course of experiments in which he discovered that various neutral stimuli, such as the sound of the atten- dant carrying the food or the sight of the food bowl, were enough to induce the dogs to salivate. This learn- ing process simply required that the neutral stimuli occur in some close relationship with the food itself. Essentially then, the event s just prior to actual feeding became conditional stimuli causing the conditional response of salivary secretions. Today, Pavlovian-type conditioning is seldom dis- cussed in the context of learning. This is unfortunate, in part because such conditioning is probably at the 574 Learning root of much emotional learning that occurs in schools and in daily life. Think about the fears and anxiety that adults and children experience in medical ofﬁces and hospitals or in school-related environ- ments, such as classrooms and school busses. If, in these environments a person directly experiences pain, failure, or hostility, the emotional response is not sim- ply to the needle that caused pain, the test result that caused shame, or the ﬁght that induced fear, but it is spread to surrounding cues such as the smells of the hospital or uniformed personnel, the classroom in which poor math performance occurred, or the vehicle in which the ﬁght or hostility occurred. This type of emotional learning can be underappreciated as a very explainable phenomenon, tied directly to the classical conditioning model. Operant Conditioning The better known and broad ly applied behavioral model is connected with the pioneering work of E. L. Thorndike and B. F. Skinner. This approach to learning is based on the simple proposition that behavior is a function of its consequences. The earliest expression of this principle is Thorndi ke’s Law of Effect, which observes that when any response is followed by a satis- factory state of affairs, it tends to be repeated. Similarly, when a behavior is followed by an unsatisfactory or annoying result, it tends to reduce in frequency and strength. Building on the Law of Effect, Skinner and others created an elaborate set of ideas that explained how to increase behaviors of interest, how to teach totally new behaviors, how to maintain learned behavior, and how to reduce unwanted behavior. All of these expla- nations rested on understanding the relationship between three elements of the puzzle: the behavior of interest, the antecedent conditions in which the behav- ior of interest was occurring, and the consequences following behavior. The relationships among the three elements are sometimes referred to as the contingen- cies of reinforcement. Building on the central idea that behavior is a func- tion of its consequences, the next step is to examine four types of possible consequences and their effects. Two of these, positive reinforcement and negative reinforcement , tend to strengthen or increase behav- iors because they result in a positive state of affairs for the subject. Punishment can be used to suppress behavior, but the most effective long-term solution to reduce unwanted behavior is simply to deny rein- forcement. This procedure is referred to as extinction. The most effective combination of these tools would be to use positive reinforcement to strengthen desired aspects of a subject’s behavior, while simultaneously using extinction to reduce less desired or competing behaviors. An important point to note is that punish- ment can be effective in the short run, but it is never a desirable long-term solution because of the negative side effects that can result, such as hostility and fear. Certainly, one of Skinner’s most important contribu- tions was his advocacy of positive consequences in the control of learning. Learning episodes that involve operant condition- ing are usually not just about increasing or reducing behaviors but also about producing responses that are appropriate to particular situations. This is where the concept of stimulus control comes into play. People respond predictably to particular stimulus situations (e.g., trafﬁc signals, classrooms, restaurants) because they have been systematically reinforced for appropri- ate behavior in those settings. Following such selec- tive reinforcement, the stimulus situation itself comes to control behavior, as when a red light shows at a trafﬁc intersection or people politely stand in line at a ticket counter. Learning is also a matter of acquiring completely new behaviors that are not presently in existence. Language-delayed children, for example, may be unable to make certain sounds that need to be part of their speech repertoire. If the children could correctly produce the sounds even occasionally, the strategy would be to simply reinforce the correct behavior. However, if the sounds are never produced, the strat- egy is to use a shaping procedure in which the closest approximations are reinforced. Over time, with skilled use of reinforcement, the approximations become closer and closer to the target. This is the same strat- egy used in animal training, where the object is to teach behaviors the animal is capable of but are not part of their natural repertoire. Again, the strategy is to selectively reinforce closer and closer approxima- tions until the target is reached. Finally, one important issue in behavioral learning is the maintenance of behavior at desired strength and frequency levels. This is where reinforcement sched- ules come into play. This is a complex area in itself, but the main idea is that constant reinforcement never produces the strongest and most extinction-resistant behavior. Rather, once a behavior is learned and can Learning 575 reliably occur in a particular stimulus environment, the reinforcement schedule needs to be adjusted so that reinforcement occurs only intermittently. A good example of this is the timing of payoffs in the gaming industry, particularly with slot machines. Patrons often spend long hours on these machines because the sched- ule is cleverly arranged to keep gamers looking for the reinforcement. Teachers and parents too quickly ﬁnd that if children are constantly reinforced, the behavior in question will quickly disappear once the reinforce- ment is removed. This would not be the case had the behavior been reinforced on a leaner and more unpre- dictable schedule. The entire operant conditioning framework pro- vides a powerful set of tools for anyone who desires to intervene in his or her own behavior or to work toward change in others. To recap, the main idea is that behavior does depend on its consequences. Use of the operant conditioning principles is not difﬁcult, but in the absence of a basic understanding, it is easy to make mistakes. Learning as Information Processing During the long period in which behavioral frame- works dominated learning research, the activity of the human brain was somewhat of a mystery. However, as described earlier, the many questions about what goes on inside the ‘‘black box’’ began to be revealed as investigators employed a range of methodologies to tease out some of the basics of how humans process information and how the memory system worked. This movement began in the late 1950s and was experienc- ing great momentum by the 1970s. In a nutshell, the entire conversation about learning rapidly shifted from questions about behavior to questions about knowledge acquisition and the construction of meaning. This section outlines the basic themes and high- lights the main contributions of the cognitive orienta- tion to learning, as follows: 1. It is important to recognize the active nature of human information processing and to understand some of the capacities and constraints of the mem- ory system. 2. Because knowledge acquisition is such a central theme in cognitive learnin g, it is important to know something about the structure and organization of memory. If learners are co nstantly building knowl- edge, what do their mental representations look like? 3. Learners necessarily exercise a great deal of control over their own learning, so it is important to con- sider that people have much to learn about their own learning. 4. Learning is not simply a linear process in which peo- ple continue to add to their knowledge stores; rather, learning is a cyclical process of returning again and again to existing concepts that must be reﬁned and oftentimes corrected for misconceptions. Active Processing and Capacity Issues The original memory models posited several types of memory stores. For the purposes of this entry, it is sufﬁcient to distinguish between a short-term ‘‘work- ing memory’’ and a long-term, or permanent, mem- ory. Short-term memory is the conscious workspace where new information is brieﬂy held in an active state so a person can either use it for quick responses or process it further into a more permanent form. One difﬁculty with short-term memory is that it is plagued by limited space and also limited time duration. The general rule is that short-term memory can hold about seven, plus or minus two, bits of information, and without constant mental rehearsal, the duration is slightly less than 30 seconds. Once a person processes information into long-term memory, these constraints disappear; however, other issues arise, such as how one goes about ﬁnding information that was previ- ously stored. These complexities of memory simply illustrate the need for strategy and skill in using the system. With short-term memory, learners can keep informa- tion ‘‘alive’’ longer with rehearsal strategies or by using external stores, and the capacity problem can be partially solved by recoding small bits of information into larger chunks based on prior experience. Further- more, when people process new information for more permanent storage, they are typically connecting it with knowledge stored at a prior time. The quality of these connections makes a big difference in whether the new information is retained and whether it can be retrieved for later use. Knowledge Representation Because there is such a vast amount of information stored in human memory, the issues of structure and organization are important. For the sake of space, knowledge representations should be efﬁcient and 576 Learning avoid redundancy. For example, when a person stores information about forms of literature, there is no need to store separately for each story, poem, or play, as literature has a basic structure that is relatively con- stant across thousands of examples. Rather, with experience the person develops basic schemas for how plays, poems, and stories generally go. These schemas may change somewhat over time, but the important thing is that when the person encounters new examples of literature, he or she knows a lot in advance about what to expect. A second beneﬁt of well-formed knowledge is that it gives learners the power to generate their own knowledge. When students in any discipline master the basic underlying structure of their disciplines, they can then generate inferences and further details that were never directly taught, but that are reasonable extensions of the basic knowledge base. Several different types of knowledge representa- tions are represented in the literature on learning. Everyday affairs such as eating at restaurants, going to doctors and dentists, participating in a religion, and observing holidays have underlying structures that are usually temporal in nature. These structures are typi- cally referred to as scripts. People depend on these underlying scripts to give order and predictability to regularly encountered experiences. By contrast, the facts and concepts learned in schools tend to be represented in terms of proposi- tional networks. Researchers can easily demonstrate the ‘‘networked’’ nature of basic ideas in any disci- pline simply by naming one example of a concept— the word disease , for example—and then asking people to generate related ideas that come to mind. Probably the most powerful general schema that people anywhere possess is the knowledge of how stories are organized. Because so much of human experience is shared via stories, it is important for all members of any society to be able to understand the elements of story narratives and to be able to generate them for communication. It could be argued that the ability humans have to organize and communicate human experience at a level above mundane details is their greatest achievement. Executive Control It is clear that learners control their own cognitive activity, and for this they need two things. One necessity is awareness of how they are doing. For example, when people read text material, comprehension is key to their success. Most people have experienced completing a reading passage only to recognize that they have no clue as to what they have just read. This feeling of com- prehension, or lack thereof, is the ﬁrst requirement for being able to take corrective action. Successful readers and learners tend to maintain such awareness to a greater extent than less successful readers. The second necessity is to acquire and use strate- gies for learning, comprehension, and memory retrieval. This is the area in which learners can vary dramatically in their approach to learning. The basic idea is that people can always ‘‘do something’’ to actively process information, and over time research- ers have identiﬁed many powerful domain-speciﬁc strategies that learners either acquire on their own or can be taught. The bottom line is that nothing substi- tutes for taking charge of one’s own learning. Learning Over Time The ﬁnal point to make in this section on learning from a cognitive perspective is that knowledge build- ing is a never-ending process. Even the straight- forward scripts people develop in areas such as their participation in medical services undergo substantial change as practices are modiﬁed based on technology and medical science. Whenever one’s experience changes in any domain, the underlying schemes or frames used to make sense of those practices must change as well. In other words, the basic story lines that give meaning to people’s lives are constantly under construction. In the ﬁnal analysis, this is what the cognitive world is really about; it’s about a con- stant search for meaning. Learning as Social Participation Until the late 1980s the most signiﬁcant contributions to research on learning occurred in laboratory settings, and the largest application contexts were in the public schools at all levels. As see n in the discussion thus far, the emphasis on learning— whether with respect to observable behavior or less visible cognitive activity— has been on individual learners performing mostly solo. This emphasis on individual performance has served people well in some respects; after all, success in school is largely a solo affair, particularly when it is explicitly reinforced that way with the continuing emphasis on grades as the primary indicator of learning. Learning 577 What changed during the 1990s is that new research was conducted not in psychology laboratories but by social anthropologists in everyday cultural prac- tices. Examples of the contex ts studied included craft cultures such as meat cutters and tailors, professional settings such as naval navigation and insurance claims processing, and other practices such as embodied in Weight Watchers clubs and Alcohol Anonymous meetings. Not surprisingly, the story about learning that emerged from these kinds of studies was framed in an entirely different way, and the details provide a window onto learning that enriches researchers’ understanding substantially. One key premise is that humans are social beings, and learning is inherently a social process. This basic framing idea leads to a range of new propositions about learning, which are explained brieﬂy in this concluding section. The Centrality of Participation One prevailing mind-set about learning that has been carried forward through the behavioral and cog- nitive models is that learning is about the acquisition of generic skills and knowledge, with little attention to the contexts that are relevant to these outcomes. In communities where social practices are ongoing, the emphasis shifts to one’s role in the practice and the participation structures that afford access to the prac- tice. With this shift, learning is never separated from doing, and in fact learning is deﬁned in terms of one’s trajectory as a legitimate practitioner. In this context, beginners may enter a complex practice by initially assuming peripheral roles, but even at the periphery, the novice participant has access to the full social apparatus of the practice—such as practice-related conversations, the tools and contexts of the practice, and members who are more advanced in their roles. Over time. novices move to increasingly central roles, and with this movement, they begin to acquire an identity as a legitimate practitioner. Identity If the purpose of learning as cognitive activity is to change people based on what they know, the purpose of social participation is to change people in terms of who they are. The concept of identity is difﬁcult to consider in formal learning contexts, such as schools, because the subject matter of schools (i.e., the tradi- tional disciplines) generally does not allow access to the underlying practice domains referenced by the dis- ciplines themselves. Thus, we could ask how one ‘‘becomes’’ a scientist when the study of science is more about being a student of science than it is about the legitimate practice of science. It is clear, however, that going to school is a form of practice, and it is likely that students, over time, develop identities as people engaged in the practice of school going. Support for Learning Learning in communities of practice is generally a context-rich affair. This is in stark contrast to learn- ing in classrooms, where knowledge to be learned is generally presented, often for efﬁciency, as the bare facts and concepts carefully separated from the messy contexts in which such knowledge was discovered and might be applied. In communities of practice, there is by deﬁnition access to all the tools of the practice, all the social structuring, all the stories, and all the physical aspects of the setting that provide clues to how one successfully participates. In these settings the very cognitive activity, such as math cal- culations, may look entirely different from the same operations as they would occur in school lessons. Emphasis on Situated Cognition One immediate consequence of the social perspec- tives outlined here has been the emergence of a signiﬁ- cant debate about the continued framing of learning as a process whereby individual learners acquire knowledge and skill through the addition of small, incremental pieces. The question for formal education concerns how much of the social practice world to let into traditional learning environments. Although this debate is ongoing, it does seem clear that researchers, theorists, and educators can no longer afford to ignore the fundamentally situated nature of learning. Terry M. Wildman See also Educational Technology; Effective Teaching, Characteristics of; Emotion and Memory; Episodic Memory; Explicit Memory Further Readings Bruner, J. (1990). Acts of meaning. Cambridge, MA: Harvard University Press. Chance, P. (1994). Learning and behavior. Paciﬁc Grove, CA: Brooks/Cole. 578 Learning Gardner, H. (1985). The mind’s new science: A history of the cognitive revolution. New York: Basic Books. National Research Council. (1999). How people learn: Brain, mind, experience, and school. Washington, DC: National Academy Press. Skinner, B. F. (1968). The technology of teaching. New York: Appleton-Century-Crofts. Wenger, E. (1998). Communities of practice: Learning, meaning, and identity. Cambridge, UK: Cambridge University Press. L EARNING C OMMUNITIES Learning communities are a family of programs, typi- cally implemented at the collegiate level, that inten- tionally create community to accomplish speciﬁc learning objectives or goals. They are characterized by intentionally crafted spaces that bring groups of learners together to achieve shared goals around a cen- tral theme, increase interaction and collaboration with peers and faculty both in and out of the classroom, and use active learning techniques to focus on multi- or interdisciplinary concerns. Studies evaluating learn- ing communities’ effectiveness suggest they promote students’ attainment of a wide range of academic and social outcomes important to graduates facing new social, political, and economic challenges. History of Learning Communities In their review of student learning communities, Oscar Lenning and Larry Ebbers not ed that bringing indivi- duals together for the purpos e of creating more power- ful environments for learning could be traced back to the ﬁrst century C . E . However, Barbara Leigh Smith and colleagues have noted that the American pragmatist John Dewey provided the foundation upon which today’s learning communities rest. In Experience and Education , Dewey called for progressive education . This focused on experiential (as opposed to vicarious) learning that situated knowing within the experience of the learner and was concerned with not only the trans- mission of culture but the development of skills needed for future knowledge produ ction and problem solving. Importantly, Dewey noted that the process of progres- sive education depended o n contributions from the stu- dent, his or her peers, and the educator. In Experimental College , educator Alexander Meiklejohn described the University of Wisconsin’s Experimental College, a residentially based learning community, or living-learning program, that opened in 1927. Students spent their ﬁrst year in the Athens- America Curriculum, comparing and contrasting the development of each society’s political and social development. In their second year, students pursued Sophomore Regional Studies, an in-depth sociological and anthropological examination of a given locale. Five years after it opened, the Experimental College closed due to funding concerns and controversy about its methods. However, several of the college’s origi- nal design components remain common in today’s learning communities, including (a) multi- or interdis- ciplinary inquiry focused on a particular theme or prob- lem; (b) the blending of social and academic roles for students, their peers, and f aculty, including enhanced opportunities for formal and informal contact through shared community space; © college-sponsored co- curricular activities and student organizations; and (d) faculty training in teac hing methods akin to today’s integrative, learning-centered pedagogies. In the years that followed, institutions interested in developing learning communities adapted all or part of the philosophical and practical advice of Dewey and Meiklejohn to their unique needs. Several notable examples exist, including Tussman’s work at the Uni- versity of California-Berkeley, patterned on Wiscon- sin’s Experimental College; Evergreen State College (Olympia, Washington), with its emphasis on inter- disciplinarity, team-teaching, and collaborative, prob- lem-focused learning; and curricular reforms at LaGuardia Community College (New York City) and Stony Brook University. The successes and failures of these programs informed subsequent innovation, and the range of program types now classiﬁed as learning communities has grown. Types of Learning Communities Although no deﬁnitive typology of learning communi- ties has been developed, most programs can be sorted into one of four categories. 1. Fully team-taught progr ams typically represent the form of learning community with the highest degree of curricular integration, with a small group of faculty working together to design courses around an interdisci- plinary theme. These progra ms, which are also referred to as coordinated studies programs, may represent a student’s entire academic load for a semester or year. Learning Communities 579 2. Paired or clustered cou rse programs, or block scheduling, join two or more discrete but complemen- tary courses. As such, these programs may or may not be organized under a unifying theme or taught in an inter- disciplinary manner. Combining an English composition or orientation/ﬁrst-year t ransition course with a course from another discipline is a common example, as is join- ing related natural, physical, or social science classes. 3. Cohort programs are designed to create smaller learning units within large, preexisting courses. A large chemistry class, for example, might be broken into groups of 15 students (a cohort) who attend a large lec- ture with their peers but then meet as a cohort in a special recitation or tutorial secti on. In the federated learning community model, cohort me mbers are accompanied to class by a faculty ‘‘master learner,’’ who then teaches the recitation section. Cohorts of students participating in freshman interest groups (FIGs) take a group of courses together, which is often a mix of larger lecture, smaller discussion, and orientation/ﬁrst-year transition courses united under a central theme. 4. Living-learning programs seek to combine one of the three previous learning community models and the student’s residential experience to maximize stu- dent and faculty contact and provide greater opportu- nities for formal and informal interaction around the program’s contents. Students participating in a given program are assigned to all or part of a particular resi- dence hall, often with faculty ofﬁces, academic sup- port resources, classrooms, and spaces for group study or tutoring located directly on their ﬂoor or in their building. Residence hall common spaces are also used for programmatic purposes, such as co-curricular activities and social events. Importantly, each of these program types may also include out-of-class learning experiences, such as service-learning opportunities, community-based problem- solving pursuits, internships or co-ops, team develop- ment activities, or relevant cultural events. In doing so, learning communities purport to support stu- dents’ collegiate success, most notably academic achievement, social growth, and persistence. Student Outcomes Associated With Learning Communities Unfortunately, little quantitative research about the effectiveness of learning communities exists when one considers the number of interventions that are being employed nationwide. Patricia Cross has noted that much of what is reported as causal evidence of the effectiveness of learning communities is actually research showing correlations between student out- comes and experiences that are typical of intentionally designed programs, limiting causality claims. Such research also typically relies upon students’ self- reported gains as opposed to more objective measures. Making generalizable statements about the effective- ness of learning communities is further complicated because the majority of research that has been conducted is limited to single-program evaluations. Despite these methodological problems, two classes of positive outcomes associated with learning commu- nity participation are increased academic achievement and increased student persistence through students’ enhanced integration with the social and academic systems of the institution. Academic Achievement Participation in learning communities has been positively linked to the attainment of a wide range of academic outcomes. In reviewing a collection of domi- nantly single-program stud ies, Lenning and Ebbers noted gains in students’ grade point averages, declines in the number of students on aca demic probation, growth in skills needed for academic success, and enhanced cognitive complexity. These ﬁndings have been corrobo- rated by multi-institutional studies. Researchers have documented higher grade point averages among learning community participants in comparison to nonparticipat- ing peers. Using data from the National Survey of Student Engagement, Chun-Mei Zhao and George Kuh identiﬁed a wide range of other desirable intellectual or academic outcomes for learning community partici- pants, including more academic effort, more frequent engagement in active and collaborative learning, and more frequent enrollment in courses that demanded the use of critical thinking skills. Persistence A number of studies have suggested that learning communities contribute to student persistence. Most attribute this effect to students’ enhanced involvement with the institution’s academic and social systems, which Vincent Tinto’s model of student attrition argues plays a dominant role in persistence behaviors. 580 Learning Communities More frequent faculty contact, a hallmark of aca- demic integration, often has been linked to learning community participation. Beyond mere frequency of contact, Tinto noted that student-faculty interactions may be qualitatively improved: Students who partici- pated in learning communities reported more favor- able perceptions of faculty. Learning communities also allow peers to contribute to academic integration. Tinto and colleagues found learning community stu- dents reported more frequent participation in study groups, a ﬁnding corroborated in two of the cases in Jean MacGregor’s study, and greater levels of peer accountability for academic issues. Research on learning communities suggest their contribution to social integ ration is due, in large part, to the creation of environments through which students gain a greater sense of social support. Tinto noted that learning community members reported higher levels of peer interaction than their peers who were not learn- ing community members, and his work has found that students participating in learning communities were able to build peer networks more readily. Additionally, participation in learning communities appears to con- tribute positively to student s’ general sense of satisfac- tion with their experience on campus, and with peers, faculty, and administration. Living-learning programs ma y contribute distinctively to academic and social int egration because of their co-location of student reside nce and features characteris- tics of nonresidential learning communities. Karen Inke- las and colleagues have noted that on many important indicators, living-learning participants reported more positive experiences and outcomes than their non- learning community peers, including smoother social and academic transitions to college, more frequent academic and sociocultural discussions with peers, greater rates of faculty mentorship out of class, and stronger senses of civic engagement and empowerment. Gains on general education outcomes have been associated with participa- tion in living-learning programs, but most research- ers have noted that these indirect effects are mediated through enhanced student involvement with their environments. Core Practices in Developing Learning Communities Barbara Leigh Smith, Jean MacGregor, Roberta S. Matthews, and Faith Gabelnick are among the most proliﬁc, contemporary proponents of the learning community movement. Their recent work has suggested that the positive outcomes associated with learning communities, like those outli ned in the previous section, are dependent on ﬁve core practices. Based on theoreti- cal propositions and empiric al ﬁndings from the litera- ture surrounding student development, cognition, and learning, each practice pro vides guidance for program development and implementation. Smith and colleagues’ ﬁrst core practice is commu- nity , and it is evidenced at the student, faculty, and institutional levels. For students, community is experi- enced both socially and academically. First, students recognize community as a sense of inclusion, which connotes membership or belonging to the institution’s academic and social realms. Indeed, it has been noted that learning communities can provide otherwise iso- lated students a ready-made location for forming aca- demically and socially supportive peer relationships, both in and out of the classroom. Community is also experienced epistemologically. Cross has noted that, increasingly, higher education is acknowledging a shifting understanding of the nature of learning that recognizes its nature as a social process. Participation in a learning community demands that certain skills and attitudes consistent with this new view of knowl- edge be fostered. As such, Tinto noted that learning community participants recognize that they have a role in facilitating not only their own learning but also the learning of their peers. Just as students beneﬁt from the ‘‘community’’ inherent in learning communities, so too may faculty. Learning community scholars have noted that learning communities can serve as communities of practice for faculty, providing opportunities for faculty develop- ment and a location for meeting social or afﬁliational needs. Finally, Smith and colleagues noted that learn- ing communities may have as their focus a mission of service to the institution’s external community, extending their beneﬁts well beyond the campus gates through service learning, community-based problem solving, or action research. Diversity , or a commitment to multiculturalism and social justice, is the second core practice identi- ﬁed by Smith and colleagues. They have noted that diversity may be promoted and supported in learning communities. First, the authors noted the growth in learning communities focused on serving a group of participants traditionally marginalized in the larger community by virtue of race or ethnicity, gender, sex- ual orientation, or other social identities. They also Learning Communities 581 suggested that learning communities focused on criti- cal or postmodern analysis of social concerns provide participants of all backgrounds opportunities to be exposed to a curriculum that is more inclusive than that taught elsewhere on campus. Finally, both Smith and colleagues and Cross have noted that pedagogies employed to develop in-class and out-of-class learn- ing experiences may themselves be more inclusive, welcoming those who have traditionally been isolated from the educational dialogue into a community of learners, including women and ethnic minorities. Smith and colleagues’ third core practice, integration, calls not only for the integration of diverse curricula to assist students in formulating a view of knowledge as interdisciplinary, but also for the use of pedagogical techniques that empower partic ipants to integrate knowl- edge on their own accord. Typically, curricular integra- tion takes places through the examination of a central problem through multiple disciplinary lenses. This prac- tice promotes epistemic growth, in that it challenges participants to redeﬁne how they come to know and solve problems. Integrative pedagogies typical to learn- ing communities, such as collaborative learning, study abroad, and service-learning, among others, support stu- dent growth by providing an expanded repertoire of methods to explore real-world concerns. The use of active learning is Smith and colleagues’ fourth core practice. Acknowledging the beneﬁts accrued through the use of active learning techniques (i.e., undergraduate research, service-learning, ﬁeld- work, and collaborative teaching and learning prac- tices), Smith and colleagues join Lenning and Ebbers in arguing that well-crafted experiences should appear consistently across learning communities’ designs. Smith and colleagues contended that when students and instructors actively explore substantial, meaning- ful questions in environments built upon the core practices, the roles and capacities of those students and instructors are transformed. Learning, rather than instruction, is ascendant; students and instructors share responsibility for the enterprise of learning; and students’ capacity to generate knowledge in collabora- tion with their peers is enhanced, as opposed to their being passive recipients of knowledge handed down from instructors. Learning communities also hold the promise of extending the temporal boundaries of when active learning occurs. Tinto noted that learning community participants’ increased social interactions with each other provided opportunities for learning at virtually any time. Smith and colleagues’ ﬁfth and ﬁnal core practice is reﬂection and assessment. Itself a form of active learning, ongoing reﬂection and assessment contrib- utes to students’ meaning making and is a way to build community among participants. Smith et al. argue that the task of individual reﬂection should include a thoughtful analysis not only of the content of what has been learned but also of the processes of thinking and learning. Group reﬂection within a com- munity can serve as an important mechanism for strengthening the process of learning by reinforcing those connections and relationships critical for collab- oration. Smith and colleagues also identiﬁed assess- ment as a critical opportunity for enhancing learning. Formative assessment can be particularly beneﬁcial to learning community members, providing regular opportunities for a learner and her or his instructor to discuss what there is to be learned from an experi- ence, where a given learner’s strengths lie, and where further growth can occur. Tasks and Roles of Faculty and Administrators Learning communities represent a conceptualization of the learning enterprise that fundamentally differs from the traditional model often employed in under- graduate education, varying in both process and prod- uct. Didactic techniques are still the norm on most college campuses, at least in introductory and other lower-level courses, and Paulo Freire’s ‘‘banking model’’ of education, in which students are the pas- sive recipients of professors’ knowledge, frequently remains the underlying instructional pedagogy. Learn- ing community scholars have noted that learning communities have the potential to transform such practices, but doing so will require the redeﬁnition of roles for faculty and campus administrators. As faculty members begin working with learning communities, it is often difﬁcult to change from the traditional ways of ‘‘being’’ and ‘‘doing’’ in the acad- emy. The greatest transformation may be pedagogical, as the faculty member moves from an instruction- centered paradigm to one that is learning centered and redeﬁnes the nature of power in the learning relation- ship. It is also important to intentionally design inte- grative curricula that highlight the analytic strengths (and weaknesses) of multiple, and possibly divergent, disciplines and employ acti ve learning pedagogies. Importantly, this reform is often done in concert with 582 Learning Communities colleagues from across the ins titution, requiring a level of collaboration that goes beyond what may be typi- cally experienced in faculty life. Finally, faculty involved in learning communi ties also must sharpen their skills in working with students: Because of increased frequency and quality of interaction and a reduction of the power difference between teacher and learner, faculty—especia lly those residential learn- ing communities—often ﬁnd themselves assisting stu- dents with social, personal, and vocational concerns. Learning communities call for student affairs and academic affairs administrators to collaborate in ways that, according to Charles Schroeder and his col- leagues, are all too often unfamiliar because of histor- ical divisions. Implementing learning communities requires both areas of the university to acknowledge that their work is united under a superordinate goal: Enhancing undergraduate education. As such, delin- eating which responsibilities will be met by academic administrators, which will be met by student affairs administrators, and which must be shared creates space for cultural exploration and an eventual under- standing of culture’s inﬂuence on learning communi- ties’ success. For their part, academic affairs administrators must wrestle with difﬁcult questions related to the imple- mentation and ongoing management of learning com- munities. If release time is needed, for example, how will it be ﬁnancially supported, who will authorize it, and how will faculty loads be re-balanced? How will learning community teaching or service be evaluated when faculty seek tenure or promotion? Who will handle programs’ administrative burdens, especially shepherding new courses through curriculum commit- tees, ensuring that sections of a given course are scheduled in the appropriate sequence and numbers, and handling linked or cohorted class registrations? Although none of these challenges is individually insurmountable, together they represent a burden that must eventually be managed. Developing and implementing learning communi- ties often require the efforts of student affairs admin- istrators and may include providing particular services associated with student affairs units, such as career planning and placement, service-learning and intern- ships, study abroad, or residential education. Especially in the case of living-learning programs, university housing provides not only the facilities needed for successful programs, but also the support required to handle housing assignments, deliver a broader residence education program through professional and paraprofessional staff, address roommate concerns, and manage or maintain ancillary space for program- matic needs

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. Student affairs staff members may also provide needed consultative services for faculty, espe- cially on techniques for building community, promot- ing leadership development, and shaping positive student behaviors. Finally, Anna Goodsell Love has noted that in learning communities where both academic and stu- dent affairs divisions are partners, there are many tasks that require collaboration. First, both academic and student affairs administr ators must identify, and cultivate the continuing support of, key institutional stakeholders (typically particular leaders) who are champions of the learning community movement. Second, programs’ long-term stability must be addressed. Sustainability i s enhanced by (a) intention- ally locating learning commu nities within an institu- tion’s administrative stru cture, (b) dedicating line positions and hard budgets, ( c) developing institution- ally meaningful learning outcomes and a plan for reporting consistent efforts through ongoing assess- ment, and (d) ensuring that growth in learning commu- nity programs does not outpace growth in the infrastructure needed to support them. Finally, both faculty and staff involved in learning communities require—and deserve—conti nual training and develop- ment on a wide range of topics, including student and human development theory, educational psychology, and advanced pedagogies. Future Considerations The demand for postsecondary education to produce increasingly competent graduates is unlikely to abate; the opportunities and threats facing future generations seem to grow ever more complex with each passing day. To the extent to which these needs and the pur- ported capacities of learning communities are coter- minous and effective, learning communities will remain an enduring feature on the educational land- scape for years to come. Increasingly, local program evaluations and multi-institutional studies suggest that their theoretical contributions can be realized. As has been noted, the development and implementation of learning communities are not simple, and they are not a panacea. However, as best practices from the ﬁeld and the research continue to emerge, learning com- munities of all types can be strengthened to beneﬁt Learning Communities 583 both students and faculty and, hopefully, their larger worlds. Matthew Soldner, Karen Kurotsuchi Inkelas, and Aaron M. Brower See also Adult Learning; Cooperative Learning Further Readings Brower, A. M., & Dettinger, K. (1998, Nov/Dec). What is a learning community? Towards a comprehensive model. About Campus , 15–21. Cross, K. P. (1998). Why learning communities? Why now? About Campus , 3 (3), 4–11. Inkelas, K. K., Brower, A. M., Crawford, S., Hummel, M., Pope, D., & Zeller, W. J. (2004). National Study of Living-Learning Programs: 2004 report of ﬁndings. Retrieved October 18, 2006, from http://www .livelearnstudy.net/images/NSLLP_2004_Final_ Report.pdf Lenning, O. T., & Ebbers, L. H. (1999). The powerful potential of learning communities: Improving education for the future. ASHE-ERIC Higher Education Report , 26 (6). Levine Laufgraben, J., & Shapiro, N. S. (2004). Sustaining and improving learning communities. San Francisco: Jossey-Bass. Shapiro, N. S., & Levine, J. H. (1999). Creating learning communities: A practical guide to winning support, organizing for change, and implementing programs. San Francisco: Jossey-Bass. Smith, B. L., MacGregor, J., Matthews, R. S., & Gabelnick, F. (2004). Learning communities: Reforming undergraduate education. San Francisco: Jossey-Bass. Tinto, V. (2000). Learning better together: The impact of learning communities on student success in higher education. Journal of Institutional Research , 9 (1), 48–53. L EARNING D ISABILITIES According to the U.S. Department of Education, stu- dents with speciﬁc learning disabilities (SLD) account for nearly one half of students being served by special education under the Individuals with Disabilities Edu- cation Act (IDEA). There is a general consensus in educational and psychological literature that students with SLD have speciﬁc cognitive or psychological deﬁcits that cause them to evidence academic deﬁcits; however, the speciﬁc nature of these deﬁcits has been highly debated. What is known, however, is that aca- demic deﬁcits that are a result of a learning disability are hidden, often lifelong, and at times may be pro- found. Students with SLD generally demonstrate deﬁ- cits in one or any combination of three basic academic skill sets: reading, written language, and math. This entry begins with an introduction to the cur- rent federal deﬁnition of learning disabilities with a short discussion related to the evolution of the fed- eral deﬁnition over the past 30 years. Next, character- istics of students with SLD will be presented; speciﬁc information on learner characteristics and challenges for each subgroup of SLD (reading, written language, and math) will be provided. Lastly, common service delivery models will be discussed, and information on educational implications for students with SLD will be provided. Past and Current Definitions Federal Definition Speciﬁc learning disability was ﬁrst deﬁned under IDEA in 1975. The initial deﬁnition of SLD was as follows: a severe discrepancy between achievement and intel- lectual ability in one or more of the areas: (1) oral expression; (2) listening comprehension; (3) written expression; (4) basic reading skill; (5) reading com- prehension; (6) mathematics calculation; or (7) math- ematic reasoning. The child may not be identiﬁed as having a speciﬁc learning disability if the discrep- ancy between ability and achievement is primarily the result of: (1) a visual, hearing, or motor handicap; (2) mental retardation; (3) emotional disturbance, or (4) environmental, cultural, or economic disadvan- tage. (USOE, 1977, p. G1082) Since then, many scholars have criticized the 1975 SLD federal deﬁnition for several reasons. First, the deﬁnition does not indicate that learning disabilities can, for some individuals, occur over the life span. Second, it does not indicate that students with SLD represent a heterogeneous group of students, each with unique academic deﬁcits and learning needs. Third, and perhaps most important, the requirement of a dis- crepancy between IQ and achievement has been highly debated. Furthermore, research conducted over the past 20 years has shown that the discrepancy model has weak validity and reliability for identifying students with SLD. 584 Learning Disabilities The Achievement-Discrepancy Model of Identification A main premise of the discrepancy model used in the determination of SLD is that the students who evi- dence a discrepancy between their IQ and achieve- ment are distinct in cognitive processing than students who are solely low achievers in reading, math, or both. However, empirical research conducted since the 1975 federal deﬁnition has shown that there are no clear or signiﬁcant differences in cognitive perfor- mance between discrepant students and those who are considered to be low achieving. The use of cognitive assessments such as IQ tests have also been criticized by many scholars as inade- quate, mainly because such approaches have not proven to be reliable or equitable across ethnic groups for correctly identifying students with learning dis- abilities. There has been little evidence to suggest that students who demonstrate a discrepancy between IQ and achievement have different developmental prog- noses than children who are simply low achieving. Additionally, scholars have argued that focusing on IQ does not provide information about speciﬁc pro- cessing deﬁcits or educational outcomes of students. Furthermore, IQ information does not provide rele- vant information regarding speciﬁc educational inter- ventions for students who are having difﬁculties with reading or math. Discrepancy models of identiﬁcation have also been seen as inadequate in the way in which they have been implemented in the schools. Because of the nature of IQ tests, which in general require stu- dents to be of certain age, students are by and large not identiﬁed as SLD until middle or late elementary years. This model of identiﬁcation has been called by many the ‘‘wait to fail’’ method, as it is difﬁcult to identify students with a discrepancy between their intelligence and academic performance until they reach middle elementary grades. Once students reach these grades, it is difﬁcult to implement pro- grams that will help them ‘‘catch up’’ with their normal-achieving peers. Research has demonstrated that even very intense remedial interventions with this age group are not extremely successful. Not sur- prisingly, the ‘‘wait to fail’’ model does not readily allow for a closing in the achievement gap between normally performing students and those identiﬁed with learning disabilities. Instead, most students identiﬁed in middle elementary grades show very small gains in academic performance and remain in special education throughout their school career. In sum, there are three critical problems associated with the IQ discrepancy model of identiﬁcation: 1. Students are not identiﬁed early enough to receive effective intervention. 2. There are no meaningful differences between stu- dents who are identiﬁed with SLD and those identi- ﬁed as low achieving. 3. Intelligence tests do not provide information as to what intervention is necessary to remediate the stu- dents’ reading difﬁculties. Prevalence of Children With Learning Disabilities Nationally, the occurrence of children identiﬁed as receiving special education services has been reported as slightly less than 5 % of the total number of school- age children. It is important to note, however, that within the general population of students with disabil- ities, the largest category comprises students with a speciﬁc learning disability; this subgroup constitutes approximately 50 % of all students with disabilities. Furthermore, the rate of growth for this category has grown tremendously with the number of students identiﬁed with SLD, nearly tripling since 1975. Response to Intervention In an attempt to address these critical issues within identiﬁcation, response to intervention has been sug- gested as an alternative to the IQ discrepancy model for SLD identiﬁcation. Frank Gresham has deﬁned responsiveness to intervention (RTI) as the change in behavior or performance as a function of an interven- tion. Over the past 20 years there has been a growing body of research showing the usefulness of the RTI model as both a diagnostic tool for SLD and an early prevention model for students who may be at risk for reading failure. In general, RTI research has focused on reading disabled populations. Many researchers have identiﬁed RTI as a valid way to operationalize and diagnose learning disabilities, more speciﬁcally, reading disabilities. In essence, the core of RTI is effective instruction in the general education settings and consistent prog- ress monitoring to determine students’ response to the provided instruction. ‘‘Treatment resisters’’ are Learning Disabilities 585 students who do not respond to the provided high- quality instruction and are ultimately students who, after a series of decision-making processes, are identi- ﬁed for evaluation for special education services. Stu- dents with reading disabilities have been targeted for this model because decades of reading research has shown that prereading skills, such as phonological awareness, alphabet knowledge, and decoding, are essential for successful reading achievement in later elementary grades. This extensive line of research has identiﬁed early skills necessary for reading, which makes reading development and reading disabilities identiﬁcation a natural match for RTI, a method that is grounded in early intervention and prevention of future learning difﬁculties. No Child Left Behind The reauthorization of the Elementary and Second- ary Schools Act (No Child Left Behind Act of 2001, P.L. 107–110) has created an instructional environ- ment with successful reading as the primary goal of early elementary school. For example, the Reading First program requires implementation of scientiﬁ- cally based reading instruction within a multitiered model of instruction in general education settings. These policy changes, coupled with the reauthoriza- tion of the Individuals with Disabilities Education Act (IDEA), have led to a shift in the deﬁnition of learn- ing disabilities, as schools are no longer required to use the discrepancy model of identiﬁcation. Instead, the wording reﬂects the following: In determining whether a child has a speciﬁc learn- ing disability, the LEA shall not be required to take into consideration whether a child has a severe dis- crepancy between achievement and intellectual ability. (Section 614 (b)(6A)). Further, the act states: In determining whether a child has a SLD, the LEA may use a process that determines if the child responds to scientiﬁc, research-based intervention as part of the evaluation procedures described in paragraphs 2 and 3 (of Section 614). (Section 614 (b)(6B)). The reauthorized IDEA allows RTI data to be used in the identiﬁcation and eligibility determination of students with SLD, essentially as an alternative to the discrepancy model. In addition, it allows school dis- tricts to allocate more funds for early intervening ser- vices for students who are not eligible for special education, but who have educational or behavioral needs that qualify them as at risk for school failure. RTI models align with Reading First, in that they are designed around a three-tiered model of instruc- tion, with tier 1 being high-quality, general education instruction for all students; tier 2 including supple- mental instruction for student who are struggling; and tier 3, an even more intense intervention for students who are still nonresponsive after tier 2 instruction has been implemented. Students may be considered for special education if they are dually discrepant, that is, if they are performing below the level of their peers and their learning rate is lower than that of peers. Characteristics of and Challenges Faced by Students With Specific Learning Disabilities Reading Disabilities In general, reading disabilities are divided into two levels: word-level disorders and text-level disorders. Word-level disorders are further divided into decod- ing disorders and ﬂuency disorders. Text-level reading disabilities are related to reading comprehension difﬁ- culties. Furthermore, it has been demonstrated that reading disabilities are persistent and different from developmental lag of reading skills seen in some chil- dren. Additionally, the majority of children (74 % ) identiﬁed as reading disabled in third grade remain disabled in ninth grade. Decoding Disorders Word-level decoding disorders are often called dys- lexia and generally manifest themselves in the deﬁ- ciency in a person’s ability to decode single words. Empirical literature suggests that word-level decoding disorders are caused by difﬁculties in phonological processing , that is, the ability to understand speech sounds ( phonemes ) and process the individual sounds to make words. In general, decoding deﬁciencies lead to profound difﬁculties with reading and reading comprehension. Furthermore, it is suggested that students who are not able to decode words with ease have a difﬁcult 586 Learning Disabilities time comprehending text, as the majority of their con- centration is dedicated to decoding words and not understanding the meaning of the text. Fluency Disorders Fluency is the ability to read words accurately and quickly. The National Reading Panel deﬁned reading ﬂuency as ‘‘the ability to read a text quickly, accu- rately, and with the right expression.’’ When readers are ﬂuent, most words are recognized automatically; therefore, ﬂuency disorders are often seen as a conse- quence of decoding difﬁculties. However, there is research to suggest that ﬂuency disorders can be pres- ent when decoding disorders are present. Explanation for ﬂuency disorders in the absence of decoding disor- ders are usually related to poor attention or poor allo- cation of cognitive resources. Fluency is often seen as the bridge between decod- ing and successful comprehension of text, because if students can recognize words rapidly and with ease, more concentration can be spent on inferring meaning from text. Comprehension Disorders Comprehension is a specialized type of reasoning that is conditioned and bound by the content and cog- nitive requirements of written text. Comprehension requires that students construct coherent representa- tions of text by rapidly recognizing words, accessing a network of semantic relations associated with these words, and, guided by syntax, detecting or construct- ing meaningful relationships among words. Compre- hension requires a complex set of processes beyond processes that are required for accurate decoding and ﬂuent word reading. Although accurate comprehension assumes ﬂuent word reading, it is not necessarily sufﬁ- cient for successful reading comprehension. There is some research to suggest that some students evidence comprehension disorders with an absence of decoding and ﬂuency disorders. Written Language Writing The literature is clear that the writing process is composed of three main subprocesses: planning, sen- tence generation, and revision. Students with weak- nesses in writing may exhibit additional difﬁculties in tasks such as outlining in a logical sequence, composing simple to complex sentences, and inte- grating word-level writing to sentence or paragraph forms. Additionally, children with a writing disorder may evidence extremely poor handwriting; this may be attributed to the inability to perform the requisite motor movements, also known as dysgraphia. Spelling Students with an SLD may experience challenges in their ability to correctly spell words. This difﬁculty may be due to students being unable to merge the relationship between spoken and written language to improve their literacy development. The skill set of poor spellers may be improved, however, with explicit instruction of letter patterns and multiple opportunities for practice. Math Disabilities A math disability, or dyscalculia , refers to students who evidence conspicuously poor skills at using basic computational processes to solve equations, including mathematical thinking and problem-solving skills. The ability to successfully execute each of these skills requires the ability to successfully manipulate multi- ple processes, such as retrieval in computation and language-based tasks involved in problem solving. Metacognition Metacognition refers to one’s awareness of how one thinks and how one monitors what one thinks. Unlike typical learners, students with SLD often dis- play difﬁculties in monitoring their learning and utilizing strategies or problem-solving skills. This inability to know a large number of strategies and understand how to use them efﬁciently is a characteris- tic often experienced by students with SLD. Instructional Approaches for Students and Educators The settings within which students with SLD are edu- cated, and the implementation of effective instruc- tional approaches used, have been an area of great controversy over the years. Settings within which stu- dents with SLD may be educated include inclusive classes, resource support programs, separate class placement, and separate school placement. Addition- ally, there are several instructional recommendations Learning Disabilities 587 that have been validated in the literature to speciﬁ- cally address and improve skill deﬁcits for students with SLD. These settings and instructional recom- mendations will be discussed in detail according to group type (early intervention, elementary and middle school levels, and secondary and transition level), and suggestions will be provided to provide necessary information for the improved academic successes of those students who, with the right supports in place, can learn. Service Delivery Settings Service delivery settings lie on a continuum, which ranges from highly supported and separate (separate class or school) to highly integrated with the general education (inclusive class). Support for students with disabilities being educated for as much of the school dayaspossibleisprotectedbytheIDEAleastrestric- tive environment provision. This policy has been further improved to mandate that students with dis- abilities not only be included but also make progress in the general curriculum. Placement settings include the least restrictive placement, resource room, sepa- rate class, and, ﬁnally, separate schools. The least restrictive placement (most inclusive setting) is identi- ﬁed in the Reports to Congress as a ‘‘regular class’’ or where special education services are delivered to a student for less than 21 % of his or her school day. Further down the continuum are more restrictive environments that include settings in which a student receives services outside of a general education class- room for more than 21 % of the school day. These include a ‘‘resource room’’ placement where students receive services outside the general education class- room from 21 % to 60 % of the school day. Next is a ‘‘separate class’’ setting. This setting includes stu- dents who receive services outside of a general educa- tion classroom for more than 60 % of their school day. Lastly, there is a separate school category. Although there is some evidence that may support students with disabilities being educated outside a general education classroom with instructional methods that may not be readily available in a general education classroom, evidence strongly supports the idea that students with learning disabilities be educated in a general educa- tion classroom for most of their school days. Current ﬁgures report the educational placement of students with SLD include 49 % of students in regular class 80 % to 100 % of their time, 37 % of students in regular classes 40 % to 79 % of their time, 13 % of stu- dents in regular class 0 % to 39% of their time, and the remaining 1 % in residential, separate facilities, or home or hospital programs. Instructional Approaches Much work has been done in the past few decades to contribute greatly to what is known about how to educate students with SLD. Joseph Torgesen speciﬁed that special education differs from general education for students with learning disabilities when it is more explicit, intensive, and supportive. This includes instructional approaches that are characterized as being explicit, carefully designed, and closely related to the area of instructional need (e.g., reading, spelling, math). Furthermore, many instructional approaches have been found to improve the academic performance of students with SLD. These include embedded learning opportu- nities of key skills with multiple exposures and oppor- tunities for engagement, differentiated instruction that involves actually differentiating educational content, and learning strategies instruction to provide students with SLD the means to become independent learners requiring fewer instructional supports. Other instruc- tional approaches include scaffolded instruction, guided practice, modeling, reciprocal questioning, and feedback during instruction. Instruction can be further extended with the use of graphic devices, visual and verbal devices, and memory devices. Variations in instructional grouping that have been found to be bene- ﬁcial include cooperative learning, peer learning, and structured small-group practice. Continual student monitoring is critical. The information collected during student monitoring of learning should be used to guide and deliver further instruction. Following is a brief description of these interventions or teaching methods that have been found to be beneﬁcial for students with SLD. Teaching Methods Scaffolded Instruction Scaffolded instruction is a process engaged in between teachers and their students whereby student understanding of a new concept is improved on through thoughtful dialogue directed by his or her teacher. Teachers who practice scaffolded instruction aim to extend their students’ knowledge by begin- ning with highly teacher-mediated instruction of new 588 Learning Disabilities concepts or materials, always moving toward more independent or highly student-contracted learning. Guided Practice Similar to scaffolded instruction, guided practice focuses on the teacher acting as an educational coach and builds on a speciﬁc strategy or skill that has been described and modeled by the teacher. This is an opportunity for the teacher to shift the focus of instruction from being heavily teacher-mediated to more student-directed learning. Modeling Modeling is an opportunity for a teacher to use a ‘‘think aloud’’ process of instruction of a new con- cept or skill. This process is where the teacher, using student language, motors through the completion of the task being taught. This process allows the students to hear, in their own language, how a skill is initiated and completion is self-regulated. Essentially, it allows for students with SLD to see and hear how good thinkers think. Furthermore, it lends i tself to providing greater opportunities for students with SLD to internalize the requisite processes to succe ssfully complete a task. Reciprocal Questioning Reciprocal questioning is a process engaged in by two or more individuals where mutual learning is facili- tated in a cooperative learning environment. This pro- cess allows for students to ask and respond to questions with each other to further their learning. It also allows for the teacher to provide i ndividual feedback while the other students are enga ged in their activities. Feedback Feedback is an approach that allows teachers to check for understanding of the group or with an indi- vidual. Typically, feedback is provided during an instructional phase during which students are actually working on completing a skill or task. With feedback, the teacher is providing necessary guidance through dia- logue to facilitate learning by helping students get past an area of challenge. It helps students to become ‘‘unstuck’’ should they be completing a task incorrectly. The information gathered du ring feedback is critical to both student and teacher, as it also serves to help the teacher focus the instruction to ensure learning by all. Devices to Improve Learning Various types of devices can be used to enhance the teaching of a particular skill or concept. Devices have been used by effective teachers for many years and are helpful across different levels of students with SLD. Devices allow for a student to construct a deeper understanding of the information, but they are not enough when used in isolation. Teachers need to be explicit in their discussion of devices as simply a means to the end, the end being greater understand- ing of the underlying concept. Graphic Devices Graphic devices allow for students to see a visual representation of an abstract or complicated concept. Graphic devices are widely used. Common forms include maps, graphs, or Web diagrams to display cause and effect, comparison and contrast, problem and solution, hierarchical relationships, and sequence. Verbal Devices Verbal devices can also be used to enhance learn- ing by making an abstract concept more concrete. This can be done by explaining the concept using an analogy to what is already familiar to the student. Using an analogy allows for the student to see the relationships between what is known and what he or she is attempting to learn. Memory Devices Memory-enhancing devices, or mnemonics ,help students with SLD to remember and also retrieve nec- essary information. Common uses of these devices can include helping students remember lists of infor- mation and deﬁnitions of words. An example includes remembering the names of the Great Lakes with the mnemonic HOMES (Huron, Ontario, Michigan, Erie, and Superior). What is critical for success with mem- ory devices is linking the mnemonic to information being learned. Grouping Variations Variations in traditional models of instruction have been shown to be effective for students with SLD. These models include cooperative learning, peer- assisted learning, and structured small-group instruc- tion. Cooperative learning provides opportunities for Learning Disabilities 589 peer interaction and group participation by having stu- dents come together to practice skills learned. Class- wide peer tutoring is a structured peer learning process. Each student has a role and is taught the responsibilities of the role of tutor or tutee. Speciﬁc content material is chosen by the teacher, and students are paired and work together in each of the roles. Small-group instruction has been shown to be beneﬁ- cial for students in the early intervention model as well as those in elementary, middle, and high school. Evidence in these areas suggest that lower student-to- teacher ratios may improve learning outcomes for stu- dents with SLD. Furthermore, smaller groups may allow for better customization of instruction to the individual needs of the students involved because of reduced variability among the students. Learning Strategy Instruction Learning strategies are an effective way to teach students with SLD to become more effective learners. Essentially, strategy instruction is teaching students how to learn and then how to demonstrate what they know. Based on what is known today, educators may no longer assume that their students have the requisite sets of skills required to complete academic tasks before them. These tasks include taking tests; writing sentences, paragraphs, or essays; and organizing their information. There are three underlying principles of effective strategy instruction. These include, ﬁrst, cuing a student to do something. Second, a strategy should provide a means to remember the steps required. Third, the strategy should address an area of difﬁculty for the student. For example, the paraphras- ing strategy is a strategy designed to teach students to paraphrase written material for better comprehension. The strategy uses the mnemonic RAP (Read a para- graph, Ask yourself what is the main idea and what are the details, and Put the main idea and details in your own words). The sequence of the steps outlined in combination with the teaching procedures or stages of acquisition can help students become more inde- pendent in their reading and generalize the strategy use to other settings. Learning strategies help students with SLD become effective, efﬁcient, and indepen- dent learners. In sum, much work has been done to contribute to what we know about teaching students with SLD. It is important to note, however, that even with this knowledge, many students still do not respond to this instruction. This may be attributed to the rate and intensity of implementatio n or ﬁdelity of the instruc- tion. Providing supports for students with SLD can improve their ability to be successful at various skills and academic tasks and facilitate their independent learning. Furthermore, these academic supports can be implemented in a range of settings, the least restrictive being a general education-inclusive classroom. Nanette S. Fritschmann and Emily J. Solari See also Diagnostic and Statistical Manual of Mental Disorders ; Disabilities; Individuals with Disabilities Education Act; Least Restrictive Placement Further Readings Bradley, R., Danielson, L., & Hallahan, D. (2002). Identiﬁcation of learning disabilities: Research to practice. Mahwah, NJ: Lawrence Erlbaum. Fletcher, J. M., Lyon, G. R., Fuchs, L. S., & Barnes, M. A. (2007). Learning disabilities: From identiﬁcation to intervention. New York: Guilford Press. Gresham, F. M. (2002). Responsiveness to intervention: An alternative approach to the identiﬁcation of learning disabilities. Mahwah, NJ: Lawrence Erlbaum. Lenz, B. K., Deshler, D. D., & Kissam, B. R. (Eds.). (2004). Teaching content to all: Evidence-based inclusive practices in middle and secondary schools. Boston: Pearson Education. MacMillan, D., & Siperstein, G. (2002). Learning disabilities as operationally deﬁned by schools. In R. Bradley, L. Danielson, & D. Hallahan (Eds.), Identiﬁcation of learning disabilities: Research to practice. Mahwah, NJ: Lawrence Erlbaum. McLeskey, J., Hoppey, D., Williamson, P., & Rentz, T. (2004). Is inclusion an illusion? An examination of national and state trends toward the education of students with learning disabilities in general education classrooms. Learning Disabilities Research & Practice , 19 (2), 109–115. No Child Left Behind Act of 2001, P.L. No. 107–110, 115 Stat. 1425 (2002). Vaughn, S., & Fuchs, L. S. (2003). Redeﬁning learning disabilities as inadequate response to instruction: The promise and potential problems. Learning Disabilities Research and Practice , 18 (2), 137–146. Vaughn, S., & Linan-Thompson, S. (2003). What is special about special education for students with learning disabilities? The Journal of Special Education , 37 (3), 140–147. Zigmond, N., Jenkins, J., Fuchs, L. S., Deno, S., Fuchs, D., Baker, J., et al. (1995). Special education in restructured schools: Findings from three multi-year students. Phi Delta Kappan , 76 , 531–540. 590 Learning Disabilities Zipperich, M. (1995, January). Teaching web making as a guided planning to improve student narrative writing. Remedial and Special Education , 16 (1), 3–15. L EARNING O BJECTIVES The learning objective , clearly one of the most inﬂu- ential and useful concepts in educational psychology, may be deﬁned as a statement placed within an instructional lesson that describes what the student should learn. The statement must be unambiguous and describe the desired instructional outcomes in terms that are speciﬁc and observable. The purpose of the learning objective is to help the student focus on those aspects of the material to be learned that will help the student successfully complete the lesson. A learning objective may also be called an instructional objective , behavioral objective , performance objec- tive , or simply an objective. Characteristics The following is an example of a typical learning objective in the subject matter area of mathematics: The student will complete multiplication problems where each one is two randomly selected 2-digit numbers; the student will achieve a score of 80 % or greater on a 20-item test. The student will work only with paper and pencil and must complete the test within 30 minutes; he or she is not permitted to use calculators, refer to multiplication tables, or receive assistance from another person. Learning objectives share the following characteristics: 1. Learning objectives are designed for use in one les- son and are not to be viewed as broad goals, according to Robert Mager, one of the ﬁrst advo- cates of learning objectives in education. 2. Learning objectives are not written for the teacher but for the student. Learning objectives do not describe teaching methods or media used in the lesson. 3. Learning objectives do not present information about the content of the lesson. 4. A learning objective has a number of critical com- ponents, and only an individual who has a good understanding of a lesson can write an effective learning objective. ABCD Mnemonic A convenient way to remember each part of a learning objective is to use the ABCD mnemonic. A is for audience. When one reﬂects on this aspect, one should address the following questions: Who will use the objective? Do the students have the prerequi- site knowledge needed to complete the lesson? Are the students ready developmentally for the material? In other words, the instructional designer must know how the lesson ﬁts within the curriculum and the learn- er’s capabilities. B is for behavior. When considering this aspect, one addresses the following questions: What will the student be able to do once he or she has successfully completed the lesson? What should one expect to observe? The heretofore-mentioned learning objective for mathematical content avoids language such as ‘‘understands multiplication’’ or ‘‘knows multiplica- tion,’’ because such phrases are ambiguous. ‘‘Know’’ and ‘‘understand’’ describe mental states that cannot be observed, and consequently, it will be difﬁcult for the student to determine what constitutes mastery per- formance. An advocate, such as Mager, of learning objectives stated in behavioral terms, would recom- mend that terms in a learning objective that describe mental states be replaced with language that describes observable behaviors. The prior learning objective in arithmetic should provide a precise deﬁnition of the type of problem that the student is expected to solve. C is for conditions. This aspect of the learning objective relates to the context of the student’s evalua- tion. In the earlier example of a learning objective in arithmetic, the student is required to solve the problems in 30 minutes without assist ance. The ‘‘conditions’’ portion of the learning objective allows the student to gauge how difﬁcult the evaluation will be and should inﬂuence how the student approaches the lesson. Disfordegree. That is, one indicates the level of performance that the student must attain to achieve mastery. In the arithmetic example, the student must reach 80 % or greater on a 20-item examination. With- out ‘‘degree’’ information, the student may mistakenly develop a skill level that is inadequate for the lesson goals. Learning Objectives 591 Taxonomies Not all advocates of learning objectives restrict learn- ing objectives to behaviors devoid of mental terms. Some advocates such as Benjamin Bloom contended that behaviors described in a learning objective can include any type of skill or knowledge that is to be learned from a lesson. This viewpoint has informed the development of three taxonomies of educational objectives: one for cognitive educational objectives, a second for affective educational objectives, and a third for psychomotor educational objectives. The most famous of these three taxonomies is the taxonomy of cognitive educational objectives written by Bloom and his colleagues. Cognitive objectives include different types of intellectual skills, such as memorizing, decision making, and reasoning. Bloom recognized that different types of cognitive objectives form a hierarchy. Arranged from simple to complex, this hierarchy consists of six classes of cognitive objectives: Knowledge, Comprehension, Application, Analysis, Synthesis, and Evaluation. The taxonomy of affective objectives covers topics such as attitude change and emotional development. Affective learning objectives may be written for les- sons on art appreciation, race relations, or ethical behavior. Categories of such objectives include attending, responding, and valuing. The psychomotor category covers lessons on the development of bodily movements. This would include physical activities, such as sports, keyboard use, dancing, and tool use. Additional Benefits Although learning objectives are designed for the stu- dent, a well-written objecti ve can also help the instruc- tional designer or teacher improve instruction. For example, the objective can help one make more effec- tive decisions about medial se lection, instructional techniques, classroom evaluation, and remedial educa- tion. In other words, a lear ning objective reduces ambiguity for the teacher as well as the student. Despite the usefulness of le arning objectives, they should not be viewed as a requirement for all lessons. For example, J. M. Lewis cites research demonstrating that learning objectives allow the student to progress faster through lessons, but they do not consistently improve the student’s academic performance. Lewis suggests that the instructional designer should consider other techniques to direct student attention in a lesson. Alternatives may include dire ctions, pretests, advance organizers, and questions embedded in the lesson. But whether one views learning objectives as a requirement of all course lessons or not, learning objectives will continue to be useful and inﬂuential in the corpus of educational psychology. Michael Petkovich and William M. Bart See also Bloom’s Taxonomy of Educational Objectives Further Readings Bloom, B. (Ed.). (1956). Taxonomy of educational objectives; the classiﬁcation of educational goals: Handbook 1. Cognitive domain. New York: McKay. How to write clear objectives. (n.d.). Retrieved November 29, 2006, from http://tlt.psu.edu/suggestions/research/ Write_Objectives.shtml Krathwohl, D. R., Bloom, B. S., & Masia, B. M. (1964). Taxonomy of educational objectives; the classiﬁcation of educational goals: Handbook 2. Affective domain. New York: McKay. Lewis, J. M. (1981, March). Answers to twenty questions on behavioral objectives. Educational Technology , 27–31. Mager, R. F. (1962). Preparing instructional objectives. Belmont, CA: Fearon. TenBrink, T. D. (2003). Instructional objectives. In J. W. Guthrie (Ed.), Encyclopedia of education (2nd ed., Vol. 4, pp. 1176–1178). New York: Thomson-Gale. L EARNING S TRATEGIES Forthepurposeofthisentry, learning is deﬁned as behavior change that is governed by the feedback that the child receives from his or her environment. Hence, learning is a process that can be accelerated or decelerated depending on environmental conditions. The focus of this entry is to describe a paradigm within which learning can be evaluated and environ- mental conditions can be altered and optimized to accelerate learning for all children. Learning results from an interaction between the learner and the lear- ner’s environment can include a variety of inﬂuential variables, some of which result automatically when the learner responds (e.g., computer plays a song 592 Learning Strategies when the correct answer is selected), some that are under the instructor’s control (e.g., teacher-directed variables), and some that are under the learner’s con- trol (e.g., child adds a set incorrectly and when check- ing the sum against a set of manipulative materials learns that he or she counted incorrectly). The envi- ronmental changes that precede and follow learner behavior (both programmed or intended events and unintended events) serve to either strengthen or weaken the learned association. This entry describes a paradigm for integrating assessment of learner per- formance with speciﬁc strategies empirically demon- strated to accelerate learning. Instructional Hierarchy The link between assessment and learning has been well documented and endorsed as a primary charac- teristic of effective teaching models. Child per- formance may be characterized in terms that link directly to instructional techniques of demonstrated effectiveness for that particular performance. There- fore, performance-based assessment before instruction is essential to determine prior knowledge that each child brings to the learning task. Regardless of the philosophies that teachers and researchers bring to understanding and promoting learning, the integration of performance assessment and instruction has broad utility and applicability to learning and may be incor- porated within all approaches to instruction. It is helpful to view learning as occurring in stages: initial learning for accuracy or quality; practice for ﬂuency and endurance; and application, or combination of the components into new responses, to solve novel or more complicated problems. Hence, the instructional hierarchy is a useful heuristic for organizing learner proﬁciency and therefore identifying which strategies are likely to accelerate (and decelerate) learning for that particular learner. The instructional hierarchy has been widely and successfully used to design, implement, and evaluate interventions for children’s academic perfor- mance problems. The hierarchy contains four stages of learning: acqui- sition, ﬂuency, gene ralization, and adaptation. Knowing the stage at which a learner’s skill falls relative to goals for learning communicates to i nstructional facilitators exactly which training goals, performance measures, and associated set of instructional strategies will be most effective for that learner. Th e instructional hierarchy provides a framework for instructional decision mak- ing that is driven by learner competence. Speciﬁcally, the instructional hierarchy p rovides a system for trans- lating a continuous variable like learning into categories of proﬁciency for a skill or series of skills drawn from the instructional objectives. The learner’s performance or proﬁciency determines which instructional strategies will be most effective for that particular learner at that particular point in time. Henc e, the instructional hierar- chy provides a basis for implementing effective instruc- tional strategies and for revising these strategies over time as learner skill improves (and new strategies are needed). Characteristics of learner performance and associated instructional strategies are described for each stage of the instructional hierarchy in the following sections. Acquisition The ﬁrst stage of the instructional hierarchy is the acquisition stage. A learner ’s performance at the acqui- sition stage is characterized by low accuracy and sub- sequent dysﬂuency. When children are ﬁrst learning a skill (acquisition stage of learning), responses will be hesitant and sometimes incorrect. The goal of acquisition-level training is for learners to perform a new skill or behavior accurately without assistance. Instruction is provided on a continuum ranging from less intensive and more naturalistic strategies to more intensive and less naturalistic strategies. Because per- formance is continuously monitored as the learner acquires a new skill, instructional facilitators or trainers might initially provide less intensive and more natural- istic instruction embedded into the typical environment. If progress monitoring does not reﬂect discernible accel- eration of learning, more in tensive instructional pro- gramming can be undertaken at this stage, which might include more directive, less naturalistic approaches such as direct instruction. Direct instruction has been demon- stratedtobeaneffectivecoreandsupplementalinstruc- tional approach that reliably accelerates learning. Certain instructional strategies are of primary importance when learner performance is at the acquisi- tion stage of learning. For example, instructional feed- back should immediately occur. Hence, during this stage of learning, independent practice of the skill is counterproductive and actually gives the student a chance to practice the skill incorrectly. Guided prac- tice is the ideal form of instruction whereby a peer or Learning Strategies 593 teacher monitors each learner response and provides immediate corrective feedback. The content of the feedback at this stage should be correct and quick (interrupting the incorrect response). Delayed feed- back or error correction will be inefﬁcient and inef- fective at the acquisition stage of learning. In addition to immediate corrective feedback, certain antecedent strategies are important at the acquisition stage. For example, extensive use of cuing, prompting, and mod- eling of correct responses when the teacher anticipates an incorrect response is pivotal to establish correct responding. Effective instructional facilitators have a system of antecedent support that includes providing task materials of appropriate difﬁculty, providing structured exemplars of correct and incorrect respond- ing, and providing increasingly intensive cues and prompts until the correct response occurs. Important to the successful use of these strategies is the ade- quacy of the learning environment, most often class- rooms. To successfully program acquisition-level instruction, the teacher should maximize time devoted to active student engagement in the lesson (minimiz- ing behaviors that interfere with academic engage- ment) and should briskly pace instruction while frequently checking for student understanding. Effec- tive teachers have a system for tracking student responding when a new skill is introduced to ensure that learners have made the correct discrimination before moving to the next stage of learning where more independent learning can occur. At the acquisition stage of learning, the goal is to establish correct responding with instructional sup- port. The level of intensity of instructional support should be increased until correct responding occurs. Learners who fail to correctly respond given intensive prompting and feedback may require alteration of task materials (making the task easier) or additional instruction on prerequisite skills. Ongoing performance assessment is necessary to determine whether or not the learner has attained the goal of the acquisition stage of learning, that is, accurate and independent performance of the skill. Whatever antecedent and consequent supports have been provided to establish correct responding at this point should be removed to measure persistence of correct responding in the absence of instructional support. If accurate responding persists when instructional supports are removed, then the learner has reached the ﬂuency-building stage of learning. Fluency Building Fluency is necessary to competency. Fluency is deﬁned as the combination of accuracy plus speed and is typically converted to a rate-based metric, such as number of responses correct per minute. The temporal dimension of the response a llows for a performance description that extends beyond the attainment of 100 % accuracy. Fluency has been shown to be an ele- ment in the development of competency within a wide variety of situations including general and special edu- cation. Fluency also requires the ability to quickly link a component skill with other component skills to pro- duce more complex learner responses. Fluent compo- nent or subskill performance enhances competency with complex skills. Fluent learners can identify which component skills will help them to solve more complex problem presentations without hesitation. Learners whose performances fall in the ﬂuency- building stage of learning are learners who can accu- rately respond when the response is required and can therefore tolerate longer intervals between instruc- tional feedback occasions. Independent practice at this stage can be effective so long as materials are controlled such that the learner can continue to accu- rately and independently respond (i.e., low probability of errors). It is difﬁcult to overstate the importance of adequately controlled task materials at each stage of the instructional hierarchy. At the acquisition stage, materials should be controlled such that cues for skill performance are salient to the learner. Hence, predict- able and repetitive cues for responding are desirable. Variation is desirable only to the degree that the learner is given occasion to discern the conditions under which a response is correct and incorrect. In the ﬂuency-building stage of learning, variation in task materials is desirable to the degree that learner errors remain low. Task materials systematically may be increased in difﬁculty at the ﬂuency-building stage so long as learner performance remains accurate as speed of responding improves. At this stage, feedback can be delayed and should be tied to motivating contingencies to maximize growth and learning. Reinforcing faster performance and blocking reinforcement for slower performance is the guiding principle. At this stage, feedback should not interrupt responding (because it interferes with ﬂuency and is unnecessary). At this stage, feedback must still be correct, but it can be less elaborative. 594 Learning Strategies Prompts and cues for correct responding should not be provided at this stage, because they interfere with ﬂu- ency building. Accurate responding is established with frequent and immediate feedback, whereas ﬂuency is built with frequent delayed feedback. The key is to provide feedback after short intervals of practice dur- ing which students are working to improve their perfor- mance. Feedback generally should be brief, rather than elaborative, preserving instructional time and maintain- ing a brisk pace of instruction. At this stage, overcorrec- tion may be an effective consequence-based strategy that can be combined with delayed feedback. When corrective feedback is provided, the student is then asked to provide the correct response three times in quick succession. This strategy has been used success- fully in reading instruction. Similar to decision making at the acquisition stage of learning, ongoing assessment of learner perfor- mance is the basis for determining when the learner has completed the ﬂuency-building stage of learning for a particular skill. Fluent responding governs a lear- ner’s ability to apply a learned skill to the solution of increasingly complex and novel tasks. Learners who can ﬂuently perform a particular skill are ready for the maintenance and generalization stages of learning. Maintenance and Generalization Struggling learners generally fall into the acquisition or ﬂuency-building stages of proﬁciency and, therefore, most often beneﬁt from the strategies described for those two stages. However, learners operating in the generalization or adaptation stages may require interven- tions such as guided application of ﬂuent skills under novel conditions and with more complex tasks. Another element necessary for a student to achieve competency is application. Application refers to learners being able to use a skill in a wide range of settings and situations, or to accurately discriminate between the target skill and similar skills that might be needed to contend with various task demands. The practice conditions that establish ﬂuent responding are the same conditions that promote maintenance and generalization. Maintenance refers to the continued performance of the skill when instructional supports have been removed. Generaliza- tion refers to two speciﬁc events, the occurrence of the trained response under untrained conditions and the occurrence of different responses under the training con- ditions. Maintenance and generalization epitomize the goals of the learning effort. If learning strategies have been successful, then the learned skill will persist when the instruction ceases, will serve the learner in accessing new information or solving similar problems in the future, and will lead to generally greater adaptation for the learner in the future. After all, what good is instruc- tion if it does not produce a robust and enduring skill set that has value to the learner over time? Fluent responding is a necessary pre-condition to maintenance and generalization. Maintenance and generalization is also assessed via ongoing performance assessment. Brief timed episodes of responding yielding a score of responses correct per minute may be utilized to assess the learner’s skill trajectory during the ﬂuency-building stage of learning. Similarly, responses correct per min- ute in the absence of instruction and over time provides important information about the persistence of a learned skill and whether re-training might be needed given cer- tain goals of instruction. Research has demonstrated that greater ﬂuency is associated with successful maintenance, faster recovery or return to ﬂuency, and faster acquisition of related skills. Hence, training to ﬂuency is an important goal related to establishing a skill that maintains and has generality for the learner. Maintenance of foundational skills should be veriﬁed to ensure successful learning of related more complex tasks in the future. Further, responding under conditions that differ from those pro- vided during instruction and more typical of the every- day conditions under which the behavior will need to occur to effectively serve the learner should be exam- ined. For example, students who learn to read a number of content-controlled passages at high ﬂuency levels that maintain in the absence of reading instruction may not necessarily demonstrate adequately changed reading performance on a task in a science lesson that requires successful passage reading. The degree to which the learned skill (ﬂuent reading) generalizes to conditions that are different from those encountered during training (e.g., reading a science lesson) or to responses that allow for successful performance under typically encountered conditions (e.g., looking up an unknown vocabulary word to comprehend a science lesson) can and should be directly assessed. When a learner has demonstrated sufﬁciently ﬂuent performance and has been provided with reinforce- ment to apply that performance under different con- texts and yet application does not occur, then the learner requires instructional support for generaliza- tion. Instructional facilitators should provide guided Learning Strategies 595 practice opportunities to cue the need for application, assist the learner to apply the skill in that context, and provide immediate feedback to promote correct appli- cation. If needed, the instructional facilitator may pro- vide many opportunities to respond, applying the learned skill to novel or more complex problems to build ﬂuency for application of the learned skill. So, for example, often learners will successfully apply their knowledge of basic sums and subtraction facts 0 to 20 to the solution of word problems that utilize those computations, fact family problems, or multidi- git addition or subtraction without, or even with, regrouping. For learners who do not automatically apply the learned skill, the same progression of instructional support to build accurate and ﬂuent application may be needed to support successful application of the learned skill. Adaptation Even when a student is able to use a skill in many situations, he or she may not yet be able to modify or adapt the skill to ﬁt novel task demands or situations. The goal of attaining competency is for the student to become capable of identifying elements of previously learned skills that he or she can adapt to new demands and situations. So, for example, a child who is at the adaptation stage may readily modify the skill of basic fact of 10 + 20 to solve 10 + 21, by solving the basic fact and adding one to the solution. Adaptation can be supported by prompting, suggesting, or reviewing possible strategies for students at this stage of instruc- tion; however, this should only occur for learners who have surpassed the generalization stage of learning. Instruction often inadvertently occurs at this level for learners who have not demonstrated accurate, ﬂuent, and generalized performance, and this mistake of instruction leads to errors in performance and deceler- ated learning trajectories in general. Systems of Data-Based Decision Making to Facilitate Learning The use of routine performance assessment is funda- mental to identifying instructional strategies that will accelerate learning. Instruction that is not matched to student proﬁciency will be less effective and will neg- atively affect learning over time. Those who wish to facilitate learning must have a system for monitoring student performance and responding to those data in an iterative fashion to support continued learning toward competency. In addition to using routine per- formance assessment linked to speciﬁc instructional strategies, researchers must attend to the technical adequacy of the dependent variable (measurement) and the independent variables (implementation and measurement). Recently, systems of data-based deci- sion making have been designed to translate learner performance information into instructional targets and measure the effect of those instructional efforts to reach decisions to ultimately improve learning for all children. These systems of data-based decision mak- ing have been referred to as response to intervention (RTI) models. Use of RTI models in schools has resulted in more equitable identiﬁcation of children requiring special education services, lower numbers of children requiring special education, and improved learning for all children, most particularly for those at risk for failure. RTI evolved out of a desire to utilize the information obtained from routine performance assessment and instructional response to reach judg- ments of importance in schools, including who should receive supplemental or special education and how existing resources could be used to most efﬁciently accelerate learning for the g

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reatest number of students possible. RTI is a very promising science of decision making that is being widely used following recent revisions to educational policy in the United States. Yet, the effectiveness of RTI (or the degree to which routine learning assessment is linked to use of strate- gies that enhance learning) depends upon two critical variables: intervention integrity and decision-making accuracy. Intervention Integrity Understanding how (and how well) an intended intervention was carried out is critical to internal, external, and consequential validity. Arranging ante- cedent conditions is a necessary but not sufﬁcient condition to promote integrity of intervention imple- mentation. Research is clear in suggesting that implementation integrity cannot be assumed. Rather, integrity of instructional implementation also must be routinely assessed and high levels of integrity must be strategically programmed. Research has found that to ensure adequate implementation of desired instruc- tional strategies, teachers should be provided with 596 Learning Strategies needed materials and should receive an in vivo perfor- mance coaching system that uses a combination of verbal instruction, written prompts detailing interven- tion steps, modeling, coaching, and ongoing perfor- mance feedback about the accuracy of instructional implementation along with documented changes in learning associated with correct use of the instruc- tional strategy. Decision-Making Accuracy Decision rules should be operationalized, linked to data-collection procedures, and monitored for accu- racy. Researchers have found that decision-making teams in schools rarely reach decisions about the need for a special education eligibility evaluation that match with (a) their own assessment data, (b) others’ assessment data, © or even local criteria for identiﬁ- cation. Hence, monitoring and quantifying the degree to which decision makers correctly utilize perfor- mance data to reach decisions about what types of instructional strategies are needed and when children might require more intensive support, such as that provided through special education, is essential. Amanda M. VanDerHeyden See also Applied Behavior Analysis; Curriculum Development; Direct Instruction; Individuals with Disabilities Education Act; Learning Disabilities; Measurement; No Child Left Behind; Precision Teaching Further Readings Burns, M. K., VanDerHeyden, A. M., & Jiban, C. (2006). Assessing the instructional level for mathematics: A comparison of methods. School Psychology Review , 35 , 401–418. Daly, E. J., III, Lentz, F. E., & Boyer, J. (1996). The instructional hierarchy: A conceptual model for understanding the effective components of reading interventions. School Psychology Quarterly , 11 , 369–386. Fuchs, L. S., & Fuchs, D. (1986). Effects of systematic formative evaluation: A meta-analysis. Exceptional Children , 53 , 199–208. Haring, N. G., Lovitt, T. C., Eaton, M. D., & Hansen, C. L. (1978). The fourth R: Research in the classroom. Columbus, OH: Merrill. Johnson, K. R., & Layng, T. V. J. (1992). Breaking the structuralist barrier: Literacy and numeracy with ﬂuency. American Psychologist , 47 , 1475–1490. Kameenui, E. J., & Carnine, D. W. (1998). Effective teaching strategies that accommodate diverse learners. Upper Saddle River, NJ: Merrill. Lentz, F. E., & Shapiro, E. S. (1986). Functional assessment of the academic environment. School Psychology Review , 15 , 346–357. Martens, B. K., & Witt, J. C. (2004). Competence, persistence, and success: The positive psychology of behavioral skill instruction. Psychology in the Schools , 41 , 19–30. Vellutino, F. R., Scanlon, D. M., & Tanzman, V. S. (1998). The case for early intervention in diagnosing speciﬁc reading disability. Journal of School Psychology , 36 , 367–397. Wolery, M., Bailey, D. B., & Sugai, G. M. (1988). Effective teaching: Principles and procedures of applied behavior analysis with exceptional students. Boston: Allyn & Bacon. L EARNING S TYLE Learning style is a term used to portray individual dif- ferences in the way that people prefer to learn. Learn- ing styles are typical patterns individuals use to process information or approach learning situations. These learning style preferences are thought to occur naturally. According to learning style theory, when an individual’s learning preferences are met, the individ- ual learns more easily and effectively. There are more than 70 theories and models of learning styles. Each model describes how particular kinds of individual differences inﬂuence learning. However, the kinds of individual differences and the ways that these differ- ences inﬂuence learning vary considerably among theories. Although it is not possible or useful to sum- marize all theories, a few models that are frequently cited and described in the learning style literature are overviewed here and used as examples. Cautions and guidelines for using learning style information will also be discussed. Importance An underlying assumption of learning style theories is that individual differences in learning preferences are positive and useful and that both learners and teachers will beneﬁt from becoming aware of, and understanding, learning style information about them- selves and others. Also implicit in these theories is Learning Style 597 the idea that it is important to acknowledge learner diversity and to customize and individualize learning so the needs of all learners are met. When learners understand how they prefer to learn, they can seek preferred learning settings and learn to cope with set- tings that do not align to their learning preferences. Teachers, administrators, and program planners can use learning style information when planning teaching strategies and learning activities, evaluating learning, and developing programs and curricula. Teacher edu- cation about learning styles will help teachers recog- nize their preferred learning and teaching styles and provide alternative ideas and strategies to help teach- ers incorporate multiple teaching strategies to facili- tate the needs of individuals with different learning styles. Many models assert that the process of self- awareness of how one learns may be the most useful part of learning style information. In many models learning style information is seen as a key component in ‘‘learning to learn.’’ When learners understand how they prefer to learn and ﬁnd ways to incorporate their learning preferences into a variety of learning settings, they can become more effective learners. Thus, the purpose of learning style information is to increase learner awareness about how they prefer to learn, so that they can learn more effectively. Learners who understand their own learning styles can also recog- nize and seek learning situations that match their pref- erences and learn to develop skills and strategies for success in conditions that do not match their learning preferences. Are Learning Styles Modifiable? Individual differences in learning style can be seen as preferences or as stable traits. In most learning style models, a learning preference is not thought to be the same as a trait or ability. However, in some theories, learning styles are thought to be relatively ﬁxed characteristics or traits inherent within individuals. When learning styles are seen as relatively stable or unchanging, the theory’s emphasis is on the need for teachers and trainers to adapt learning strategies and settings to accommodate the needs of learners with different learning styles. Within these models, it is often proposed that it is essential for teachers to be aware of all learning styles and to be able to accommodate them. Teachers are encouraged to present the same information in multiple formats and to provide optional learning assignments and options. However, matching learning to the learner’s style is not always possible. Most theories tend to see learning style as somewhat adaptable and assert learn- ers can succeed in a variety of learning tasks, settings, and situations. In these models, learners are encour- aged to identify their learning preferences and utilize strategies aligned to their learning style to maximize their learning. Learners are also encouraged to iden- tify learning situations that are challenging and then develop learning skills and strategies to manage their learning in these situations. In models that conceptual- ize learning style as modiﬁable, often the focus is on becoming aware of preferences while, at the same time, recognizing and learning to adapt to learning tasks and situations that do not align with an indivi- dual’s learning style. Some models place learning styles within steps or stages of a learning process. In these models, learning is usually conceptualized as a multistep process. Learning style is seen as a preference for a particular step within the learning process. Because learning requires all steps in these models, learners are encour- aged to expand and develop learning skills and strategies to complete the nonpreferred parts of the learning process. Consensus indicates that learning style describes natural and innate preferences for learning. However, the literature also makes it clear that learning style preferences are not to be seen as limiting or deﬁning. Everyone can learn to thrive in nonpreferred learning situations, as necessary. However, when natural learn- ing preferences are identiﬁed and supported, learning is easiest and most comfortable. Learning Style Models There have been various attempts made to organize learning style models into groupings. Some classiﬁca- tion systems organize models on the basis of how sta- ble or ﬂexible learning styles are thought to be. Other classiﬁcations are made based on the various inﬂu- ences on learning, such as learning modality prefer- ences, personality preferences, social or emotional aspects, and preferences for particular cognitive pro- cesses. Still other models focus on the process of learning and individual preferences for engaging in parts of the learning process. 598 Learning Style To simplify a complex topic, three general kinds of learning style theories will be overviewed: those focus- ing on input of information, which will cover prefer- ences for sensory input and learning environments; those focused on the cognitive processing and organiza- tion of information; and those developed around a learn- ing process. Although there are more than 70 different models, only a few of the most often-cited and well- established models will be discussed. Perceptually and Environmentally Based Learning Style Theories Some theories propose that sensory input or envi- ronmental preferences are key aspects of learning style. These theories focus on preferences such as the sensory modality in which information is provided, preferred activity level of the learner, and speciﬁc characteristics of the physical learning environment that may impede or enhance learning. One popular way of looking at learning style is by preference for visual, auditory, tactile, or kinesthetic sensory modes. Seeing, hearing, touching, and doing may be more or less preferred by an individual learner. It is assumed that individuals will learn more easily and remember better if information is presented in one or two of these modes. Visual learners will prefer written or visual instructions and will observe and remember visual resources. Auditory learners will prefer verbal instructions, ﬁnd discussion helpful, and remember what is said. Tactile learners will want to touch and manipulate learning materials and will remember best when they can handle materials. Kinesthetic learners will prefer hands-on active experiences and will remember best when they can move around or become physically involved with learning materials. A learning style model by Rita Dunn and Kenneth Dunn builds on this basic sensory preference model and suggests there are at least 18 basic elements that inﬂuence how well an individual will take in and retain information. These elements are linked to four modalities: environmental, emotional, sociological, and physical. The physical modality includes the four sensory modality preferences (auditory, visual, tactile, and kinesthetic) as elements. Their model also includes three other physical modality elements: preferences for intake of food or drink, time of day, and mobility. Environmental elements include noise, temperature, and design of learning space. Sociological elements include preferences for learning with others, presence of authority, routines, and need for approval of others. Emotional elements include motivation, responsibility, persistence, and need for structure. In this model, all of these elements combine to form an individual’s learn- ing style. When these elements are in place, learning will be enhanced. Some learning style models explore other kinds of perceptual differences am ong learners. Herman Witkin explored how an individual’s perception was inﬂuenced by the context or ﬁeld the information is contained in. He found two kinds of perception: ﬁeld-dependent and ﬁeld-independent. Field-dependent perception learners are inﬂuenced by the visual ﬁeld in which visual infor- mation is presented, whereas ﬁeld-independent learners are not. He then asserted ﬁeld-dependent learners will perceive information globally and will have a social orientation to the learning . Field-dependent learners will thrive in more personal learning settings and when learning information that is personally relevant. Field- independent learners will perceive information analyti- cally and will have an impersonal orientation to learning. They will thrive in learning settings that provide opportu- nities to ask questions, solve problems, and work independently. Cognitive Processing Models Many learning style models describe differences in the way a learner prefers to process information. Sometimes these models refer to cognitive processing styles rather than learning styles. The term cognitive style is used in various ways in the learning style liter- ature. Cognitive styles are sometimes conceptualized as a part of an overall learning style; when thought of this way, it describes how individuals approach cogni- tive tasks rather than how they approach learning overall. However, in many models the terms cognitive style and learning style are used interchangeably. Similarly, in different models, the terms thinking styles and intellectual styles are also sometimes used to describe learning style preferences, as well as alter- natively proposed as a component of learning styles. In general, cognitive processing models of learning styles propose dichotomies of individual differences. These models usually acknowledge that both sides of a processing dichotomy are important parts of the learning process. They assert that individual learners will prefer one side of each dichotomy and will ﬁnd it Learning Style 599 easier to learn when this preference is accommodated in the learning situation. These differences are given a variety of names and are described in different ways, depending on the speciﬁc model; generally, however, they ﬁt into three dichotomies: abstract versus concrete, sequential versus simultaneous, and action versus reﬂection. Models that incorporate social aspects of learning include an additional dichot- omy: logical versus personal. Learners with a concrete learning style prefer to learn about relevant, practical, and useful information. They are drawn to learning that can be immediately applied in their current sit uation. Learners with an abstract learning style prefer learning about ideas and concepts. They are drawn to theory and enjoy linking and connecting ideas. Sequential learners prefer a step- by-step approach to learning, whereas simultaneous learners prefer to process information in a nonordered, more random way. Simultaneous learners tend to focus on more than one fact or concept at a time, whereas sequential learners tend to take on one piece of infor- mation at a time. In some theories, simultaneous pro- cessingisalsoreferredtoas random processing. Action-oriented learners prefer to interact with others and with materials when they are learning; they are stimulated by discussions and other opportunities to share ideas and information with others. Reﬂective learners, on the other hand, prefer to have time to think about material. They process information most effectively when they are alone. Learners who prefer a logical approach to learning are described as objec- tive and tend to prefer frank, corrective feedback from a competent expert. Individuals with a values-based approach prefer cooperative and collaborative learn- ing settings and like to receive positive feedback and support from an approachable, personable teacher. Anthony Gregorc, in his mind styles model, pro- poses combinations of two processing preferences to delineate four learning styles. Gregorc uses the con- crete versus abstract dichotomy to describe how learners perceive and understand information. He then adds a second dichotomy—sequential versus random—to describe how learners organize and order information. When these processing preferences are combined, his model results in four distinct learn- ing styles: concrete sequential, abstract sequential, abstract random, and concrete random. An emotional and logical dichotomy is also incorporated into the model. For example, an abstract sequential learning style is characterized as logical and analytical, whereas an abstract random learning style is charac- terized as sensitive and emotional. An individual may have one strongly preferred learning style or may learn best with a combination of two or more styles. Theories built on the personality type theory of Carl Jung link abstract and simultaneous processing. In personality type models, this preference is referred to as Intuition: a preference for taking in abstract information about ideas, theories, and concepts. This theory also links preferences for concrete and sequential learning. In the personality type model, this preference is referred to as Sensing: a preference for taking in information gained through the senses that is related to real-world experiences and applica- tions. Personality type theory also proposes dichoto- mies between action and reﬂection (Extraversion and Introversion) as preferred orientation to the world, between logical and personal information processing (Thinking and Feeling), and between a structured and ﬂexible approach to the environment (Judging and Perceiving). Because this model uses four dichotomies, the various combinations of prefer- ences lead to 16 distinct learning styles with individ- ualized learning preferences. Some learning style models simplify personality type theory and use dif- ferences in two of the four dichotomies to describe four learning styles. Left- and right-brain models provide another way of looking at cognitive processing. In these models, the processing differences are verbal versus visual- spatial, sequential versus holistic, and logical versus emotional. Building on the idea that there are biologi- cal differences in the way the different sides of the brain process information, these models assert that the left side of the brain prefers to process information verbally, sequentially, and logically, whereas the right side of the brain processes information in a visual- spatial, holistic, and emotional manner. Ned Herrmann created a learning styles model based on mental preferences or thinking styles from right- and left-brain models. In his model, there are four styles: the Theorists (rational), Organizers (safe keeping), Innovators (experimental), and Humanitar- ians (feeling). The Theorist learning style is character- ized by preferences for logical analysis. Sequencing and structuring information characterizes the Orga- nizer learning style. The Innovator learning style is characterized by preferences for exploration and self- discovery, and the Humanitarian learning style is linked to emotional involvement and harmony. In his 600 Learning Style model, Herrmann asserts that it is difﬁcult for learners to accommodate information presented in opposing styles. For example, a learner who prefers an Orga- nizer learning style may have difﬁculty accommodat- ing Innovator styles, or a learner with a Humanitarian learning style may ﬁnd it difﬁcult to accommodate a Theoretical style. Learning Process Models Some models, such as the one by David Kolb, pro- pose that learning occurs in a process or cycle. Each part of the learning cycle requires the use of different combinations of processing preferences. In his model, the processing dichotomies (abstract vs. concrete and action vs. reﬂection) are not only linked to individ- uals’ learning preferences but also incorporated into a deﬁned learning cycle. In his model, the learning process begins with a concrete experience. Then reﬂective observation occurs, followed by abstract conceptualization and active experimentation. Learn- ers tend to prefer one part of the learning process to the other. As a result of these preferences, four learn- ing styles are proposed: abstract conceptualization combined with active experimentation (converging learning style), concrete experience combined with reﬂective observation (diverging learning style), abstract conceptualization combined with reﬂective observation (assimilating learning style), and concrete experience combined with active experimentation (accommodating learning style). Peter Honey and Alan Mumford built on Kolb’s work to identify four different learning styles. They proposed that learning comprises four steps: experi- encing, reﬂecting, concluding, and planning next steps. Individuals tend to prefer one or two steps in the process over the others, so the four steps in the learning cycle link to four learning styles. The four styles include activists, who prefer to actively engage in experiences when learning; reﬂectors, who prefer to review or ponder experiences; theor- ists, who analyze and make conclusions; and prag- matists, who plan next steps. Similarly, Bernice McCarthy elaborated on Kolb’s model. She linked the abstract versus concrete and action versus reﬂec- tion processes to left- and right-brain functions. McCarthy proposed four learning styles within these new dimensions. In these process-based learning style models, learning styles are thought to be modi- ﬁable. Effective learners need to utilize all four steps. Learning style information helps them under- stand what steps they prefer and provides insights into how to develop underutilized steps. Measuring Learning Styles From the various theoretical models, there are at least a hundred inventories developed to measure learning styles. Many of these instruments have not been sub- jected to stringent test construction, and because of this, some practitioners and researchers question the use of learning style inventories. Many of these inventories do not have demon- strated repeatability or accuracy, so it is important for practitioners to assess the reliability and validity evidence provided with a learning style measure to determine if it is based on sound psychometric prin- ciples. Even when a reliable and valid instrument is used, most instruments have not yet demonstrated a clear link between learning style and an individ- ual’s ability to learn certain kinds of information or thrive in speciﬁc learning environments. For exam- ple, if a learner does succeed in an environment that is not aligned to his or her learning style, it is difﬁ- cult to know if this success indicates that learning styles are not important. Such a ﬁnding may alterna- tively indicate the learner has been able to adapt to that setting. Researchers cannot easily know if learning was more difﬁcult or uncomfortable in that situation than it would have been in another environment. The plethora of terminology and the large number of models and inventories contribute to the difﬁculty of surveying and assessing learning style inventories. As with many kinds of applied research, multiple interest groups in various settings, including aca- demics, schools, and businesses, are developing learn- ing style measures. These various interest groups have different aims and approaches, and there is little integration of the information gathered about the instruments used in each sector. There is also a large interest in the commercial applications of learning style inventories. A commercial focus can lead to research and promotional material that is focused on marketing a product rather than demonstrating the reliability of the inventory or the validity of a model. Many learning style inventories use a self-report format. Self-report instruments are subject to error if learners are unaware of, or unable to, accurately report their preferences. If learning style measures are Learning Style 601 to be a tool for self-awareness, those taking them must be able to use metacognitive skills to accurately evaluate themselves. When using these kinds of mea- sures, it is always important to use the results only as a guide and explore possible reasons for inaccurate results. Some administration instructions for using learning style inventories do include a self-validating process whereby learners think about, and can over- ride, results on an inventory. However, it is possible that not all learners have the skill to engage in this kind of reﬂective, self-awareness process. It is also important to ensure the results of learning style indicators do not limit or stereotype learners so as to discourage them or have them dismiss certain ways of learning. For example, some information is more abstract than concrete. If a learner believes he or she cannot learn abstract information because he or she has a concrete learning style, then the learning style information has limited rather than beneﬁted the learner. It would be more useful to show the learner how to ground the abstract information in a concrete way or to teach other similar learning strategies for thriving in this situation. It is possible to use observational data and meta- cognitive questioning as well as inventories to help students become aware of their learning preferences. For example, Barbara Given has created a methodol- ogy for assessing learning styles that incorporates information from many models within an observa- tional and self-report format. This model considers emotional, social, cognitive, physical, and metacogni- tive aspects of learning preferences. Validity of Learning Styles With all of the different theories, models, and inven- tories of learning styles, it is difﬁcult to know which ones are valid. Likely there are a number of individ- ual differences and preferences in the way a learner absorbs and retains information and interacts with others in a speciﬁc learning situation that affects the ease of learning and comfort the learner experiences. Reviews of learning style models and instruments conclude that there is a lack of deﬁnitive evidence that would demonstrate the adequacy and validity of any one approach to learning styles. Reviewers often mention the importance of considering the context and purposes for learning style information when assessing and choosing to use a particular model or instrument. When critiquing the learning style literature, it is important to understand the connotation of the labels and terminology used. For example, the word abstract is used in several learning style models. However, what is meant by abstract and the characteristics of learners who prefer ‘‘abstract’’ learning can vary greatly. To use learning style information, practi- tioners need to be able to sort through the multiple models, terminology, and concepts associated with learning styles to ﬁnd a model that works in their situ- ation. This can be accomplished by critically asses- sing the strengths and limitations of speciﬁc models. For example, if the purpose of learning style informa- tion is to help individuals understand how they prefer to learn, models with deﬁned support resources and applications will be more useful than those that do not provide this link. It also is important to ensure learning style models are not too limiting. This can be the case when learn- ing styles are conceptualized as ‘‘either/or.’’ For example, it may be unwise to characterize a learner as experiential if this infers they are not reﬂective. This kind of characterization might indicate an experiential learner cannot reﬂect or will struggle in situations that require reﬂection. Such categorization has not been demonstrated and may provide a mind-set in which learners unnecessarily avoid or feel inadequate in cer- tain learning situations. Some researchers propose it would be most effec- tive to take an integrated approach to deﬁning and describing learning styles by including a number of models and dimensions for learners to consider as they are thinking about and identifying their learn- ing preferences. Such models would include sensory preferences, environmental preferences, instruc- tional preferences, social and emotional learning aspects, and thinking or cognitive style preferences. Ultimately, learning style information is a tool to be utilized carefully by teachers, educational planners, and learners, with an emphasis on an increased awareness of learning and teaching preferences, on learning how to adapt to and manage all learning situations, and on enhancing learning and teach- ing effectiveness. Perhaps it is the process of help- ing students and educators to think about and determine their learning preferences that is more important than any speciﬁc model used to carry this activity out. Donna Dunning 602 Learning Style See also Cognitive and Cultural Styles; Learning Strategies; Metacognition and Learning; Teaching Strategies Further Readings Bostrom, L., & Lassen, L. M. (2006). Unraveling learning, learning styles, learning strategies and meta-cognition. Education & Training , 48 (2–3), 178–189. Cassidy, S. (2004). Learning styles: An overview of theories, models, and measures. Educational Psychology , 24 (4), 419–444. Cofﬁeld, F., Moseley, D., Hall, E., Ecclestone, K. (2004). Learning styles and pedagogy in post-16 learning. A systematic and critical review. London: Learning and Skills Research Centre. Cofﬁeld, F., Moseley, D., Hall, E., Ecclestone, K. (2004). Should we be using learning styles? What research has to say to practice. London: Learning and Skills Research Centre. Delahoussaye, M. (2002). The perfect learner: An expert debate on learning styles. Training , 39 (5), 28–36. Desmedt, E., & Valcke, M. (2004). Mapping the learning styles ‘‘jungle’’: An overview of the literature based on citation analysis. Educational Psychology , 24 (4), 445–464. Evans, C., & Sadler-Smith, E. (2006). Learning styles in education and training: Problems, politicisation and potential. Education & Training , 48 (2), 77–83. Guild, P. B., & Garger, S. (1998). Marching to different drummers (2nd ed.). Alexandria, VA: Association for Supervision and Curriculum Development. Hall, E., & Moseley, D. (2005). Is there a role for learning styles in personalised education and training? International Journal of Lifelong Education , 24 (3), 243–255. Reid, G. (2005). Learning styles and inclusion. Thousand Oaks, CA: Sage. Zhang, L., & Sternberg, R. J. (2005). A threefold model of intellectual styles. Educational Psychology Review , 17 (1), 1–53. L EAST R ESTRICTIVE P LACEMENT The term least restrictive placement refers to the con- cept of the least restrictive environment (LRE), a legal principle ensuring the social integration of people with disabilities. Social policies in the United States, including the Americans with Disabilities Act, require public entities to administer their programs in the most integrated setting appropriate to the needs of qualiﬁed individuals with disabilities to facilitate their positive relationships with nondisabled people in typical community settings. The focus of the LRE principle is not on the type of facility but rather on whether a placement can provide the necessary ser- vices an individual needs to have life experiences that most community members ﬁnd desirable. Placements that might be appropriate for an individual receiving public health services range from institutional settings to noninstitutional residential settings, such as assisted living, home, and community-based settings. This entry is intended to clarify the LRE principle in mak- ing placement decisions in public health agencies, educational institutions, and human services. From a legal perspective, institutionalizing a person with a disability who can beneﬁt from living in the community, and who wishes to do so, constitutes discrimination, because removal to a separate setting severely limits the individual’s ability to interact with family and friends, to work, and to live independently. The right of people with disabilities to receive ser- vices in the most integrated setting is not absolute, however. Least restrictive placement policies do not require measures that would fundamentally alter the nature of a public entity’s programs, and costs may be considered in making that determination. In reviewing the fairness of placement decisions, courts consider not only the cost of providing care in integrated set- tings to individuals but also the range of services pro- vided to others with disabilities and the state’s obligation to offer those services in an equitable man- ner. Understanding the LRE principle, and applying it correctly, is especially important to family members, psychologists, and other professionals responsible for making special education placement decisions on behalf of students with disabilities. Understanding the Principle of the Least Restrictive Placement The principle of the least restrictive placement is one of six core principles of the Individuals with Disabil- ities Education Act (IDEA), the federal legislation guiding special education policy in the United States. The LRE principle stipulates that, to the maximum extent appropriate to their individual needs, students with disabilities are to be educated with nondisabled students. Special classes, separate schooling, or other removal from the general education environment is to occur only if the nature or severity of a student’s dis- ability is such that education in regular classes with the use of supplementary aids and services cannot be achieved satisfactorily. The purpose of the IDEA is to Least Restrictive Placement 603 ensure that students with disabilities receive a free, individually appropriate, public education (FAPE) emphasizing special education and related services that meet their unique educational needs and that prepare them for further education, productive employment, and independent living. The LRE principle supports the goals of the IDEA by ensuring that a special educa- tion student’s Individualized Education Program (IEP) is implemented in a learning environment that meets the child’s needs and that least restricts his or her social integration with typically developing peers. In the language of public policy, the LRE principle is considered to be a rebuttable presumption, which means the law presumes that the regular class is the least restrictive placement for any student to receive appropriate instruction. The presumption of regular class placement is rebutted by convincing evidence that an alternative placement would provide a particu- lar student with an appropriate education. For this rea- son, school systems are required to make a full continuum of alternative placements available for stu- dents that range from regular classes, special classes, separate schools, residential facilities, hospitals, and home settings. School systems are also required to make provision for supplementary services, such as resource rooms or itinerant instruction to be provided in conjunction with regular class placement. In addition to requiring school districts to provide a continuum of alternative placements, the IDEA requires special education placement decisions to be made by a group of people, including the student’s parents and others who are knowledgeable not only about the child but also about the meaning of the evaluation data and the placement options. The IDEA identiﬁes ﬁve factors that decision makers must follow to ensure that individual students are placed in LREs based on their speciﬁc learning needs. Placement deci- sions (a) must be made annually, (b) must be based on the student’s IEP, and © must give consideration to any potential harmful effect on the child or to the qual- ity of the required services. Unless their individualized programs require otherwise, (d) students with disabil- ities are expected to attend either a school as close to home as possible or the school they would attend if they were not disabled, and (e) they must not be removed from education in age-appropriate regular classrooms solely because of needed modiﬁcations in the general curriculum. The least restrictive placement, or environment, is not a speciﬁc location but the outcome of a procedural process in which a greater weight is given to the stan- dard of appropriate services based on individual needs than to the factors that determine the placement in which the services occur. In making placement deci- sions, courts compare the student’s educational needs with the statute’s overall preference for placement in the regular classroom. Paren ts and professionals, less familiar with the law’s pr esumptive language, often confuse the terms mainstreaming, inclusion,and LRE, which do not have interchangeable meanings. Main- streaming implies that special education and general education students will be e ducated together as appro- priate but not exclusively. Full inclusion implies that students with disabilities have an absolute right to regu- lar class placement. The term LRE is not synonymous with inclusion but rather requires that placement deci- sions for students be made on the basis of an appropri- ateIEP.LREisalegalprincipleembodiedinthe IDEA; in contrast, the practices of mainstreaming and inclusion are not required by law but are educational strategies used to make the least restrictive placement principle operational in schools. Where a student receives instruction is only one component of an appropriate education. Some students may need instruction that cannot be provided in regular classes because they need to learn something different than general education students, such as Braille, Amer- ican Sign Language, or speciﬁc technologies that are more efﬁciently taught in other settings. Some students may need to learn things differently, such as students with severe learning disabilities who need intensive reading instruction in more private learning environ- ments, or students with cognitive disabilities whose job training and life skills curriculum requires them to spend time in community-based settings. The LRE requirements compel school systems to make a contin- uum of options possible so that IEP teams can make appropriate student-cente red placement decisions across a range of viable alternatives. With regard to special education placements, decision makers need to not only tally the beneﬁts of regular classes for each special education student but also calculate the risks. Educational harm can result when (a) decisions about students are based on stereotypes instead of individual strengths, (b) students are misplaced and left in place- ments that do not match their needs, or © students are included in regular classes without receiving services that comport with their IEPs. The word harm is men- tioned only once in the IDEA, and that is in the least restrictive placement requirements. 604 Least Restrictive Placement Determining the Appropriate Least Restrictive Placement To meet the standard of being individually appropriate, placement decisions in education and public policy are requiredtobemadeonacase-by-casebasisusingper- son-speciﬁc data, not philosophical arguments about social integration. In addres sing the integration princi- ple of the IDEA, educators and legal analysts have cre- ated analytic frameworks to ensure full consideration of the LRE placement requirements. One framework guides decisions about place ment by using a sequential format that begins by considering whether the appro- priate educational services written in the IEP can be delivered in the regular class if modiﬁed through the use of supplementary aids and services. If the answer is yes, then the regular class is the primary placement. If not, the decision-maki ng team would move along the continuum of alternative placements one step at a time, from regular class to resource room, to separate class, to separate school, res idential setting, hospital, or home, considering whether th e appropriate educational services might be delivered w ith appropriate supports until the answer ‘‘yes’’ is obtained. Another approach follows a set of questions to guide special education teams in making least restric- tive placement decisions. The following questions, developed by legal scholar Mitchell Yell, address the components embodied in the LRE frameworks and rely on student-centered data collected throughout the LRE determination process: 1. Has the school taken steps to maintain the child in the general education class? What supplementary aides and services were used? What interventions were attempted? 2. What are the beneﬁts of placement in a general education setting with supplementary aids and ser- vices versus the beneﬁts of placement in a special education setting? What are the academic beneﬁts? What are the nonacademic beneﬁts (e.g., social communication and interactions)? 3. What are the effects on the education of other stu- dents? If the student is disruptive, is the education of other students adversely affected? Does the stu- dent require an inordinate amount of attention from the teacher and, as a result, adversely affect the education of others? 4. If a student requires a separate setting, are appro- priate opportunities for integration available? In what academic settings is the student integrated with nondisabled students? In what nonacademic settings is the child integrated with nondisabled students? 5. Is the full continuum of alternative services made available across the system from which to choose an appropriate placement? Although the IDEA prefers students to be included in regular classes with nondisabled students, the law does not require social inclusion. The courts, how- ever, give careful scrutiny to decisions that place stu- dents in more restrictive settings. Decisions regarding the least restrictive placement for any individual in public health, education, and human services require thoughtful analysis. Public policies acknowledge a rational basis for determining, on a case-by-case basis, that a particular person’s appropriate treatment might be provided in special- ized settings using differing strategies and more inten- sive supports. Jean B. Crockett See also Inclusion; Individualized Education Program; Individuals with Disabilities Education Act; Special Education Further Readings Crockett, J. B. (2005). IEPs, Least Restrictive Environment, and placement. In K. Lane (Ed.), The principal’s legal handbook. Dayton, OH: Education Law Association. Crockett, J. B., & Kauffman, J. M. (1999). The Least Restrictive Environment: Its origins and interpretations in special education. Mahwah, NJ: Lawrence Erlbaum. Silverstein, R. (2000). The disability policy framework: A guidepost for analyzing public policy. Iowa Law Review , 85 , 1757. Turnbull, H. R., Stowe, M. J., & Huerta, N. E. (2007). Free appropriate public education: The law and children with disabilities. Denver, CO: Love. Yell, M. L. (2006). The law and special education. Upper Saddle River, NJ: Pearson. L IFELONG L EARNING Lifelong learning is an education trend that des- cribes the engagement of adults in multiple educa- tional opportunities across thelifespan.Thelearning Lifelong Learning 605 opportunities can be formal or informal, but these adult learning practices are di stinguished from childhood learning because they are intentional, voluntary, and under the control of the adult learner. In today’s soci- ety, adults may choose to explore further educational opportunities for vocational and personal enrichment or maybedriventomorelearninginthefaceofvasteco- nomic competition. Howeve r, the pattern of embracing multiple learning opportuni ties throughout adult life is the key factor in deﬁning the lifelong learner. The choice to learn continuously across the life span demonstrates how some adults have adapted to shifting professional and personal expectations. With more adults seeking learning opportunities, colleges and uni- versities have restructured their institutions to accom- modate the lifelong learner. Similarly, human resource divisions within companies have been called upon to meet the needs of their employees who seek supple- mental training or instructio n. Lifelong learning, there- fore, has left an imprint on the way adults think, work, and learn. The technology and information revolution of the past 10 years has ampliﬁed adult education opportunities, making it possible for more adults to have access to learning. In the future, educational psychology will need to examine the effects of continu- ous learning on adult cognitive development, the pro- cess of adult education, and the adjustment of adults who embrace or reject multiple learning opportunities throughout their lives. Adult Learners in Higher Education Colleges and universities have traditionally provided a formative experience fo r young people. But as adults began seeking additional l earning opportunities in the past 30 years, the landscape of higher education has changed. Evening and weekend courses are now inte- grated in every college and university across the coun- try, due to the demand for ﬂexible course scheduling from adults who balance family and career obligations. Instructors and administra tors now distinguish tradi- tional-age students from n ontraditional students and recognize their different nee ds, different expectations, and different ways of learning. Colleges and universi- ties have begun accelerated degree programs for adults who began college courses earlier in life, left educa- tion to enter the workforce, and now are returning to classrooms with a rich set of life and work experi- ences. Accelerated degree programs often give these returning learners college credit for the acquisition of those life experiences, with the twofold purpose of validating the experiences as learning and reduc- ing the time it takes to obtain a degree. As a result of the increased demand for adult education, higher education has changed class schedules, courses, and degree programs to accommodate the new consumer, that is, the adult learner. As adults have demanded more ﬂexibility and choice in their educational experiences, technology has begun to play an exceedingly important role in how education is delivered. Colleges and universities now offer courses in their entir ety over the Internet, com- plete with online class discus sions, requirements for ‘‘posting’’ comments (the equ ivalent of class participa- tion), and submitting all assignments electronically. In this new education delivery system, in lieu of having face-to-face classroom interactions, adults and instruc- tors communicate via e-mail or chat rooms. The virtual classroom meets the ﬂexibility demands of adult learners, but educators speculate whether ‘‘e-learning’’ (i.e., electronic learning) achieves the traditional goals of higher education. To address this concern, some colleges and universities who offer online degrees have incorporated one or more physical face-to-face meetings between students and instructors. But adult learners, speciﬁcally lifelong learners, seek out higher education for a variety of personal objec- tives, some of which may not include the traditional objectives of higher education: to acquire critical think- ing and writing skills, to sol idify basic knowledge, and to be introduced to a particular professional ﬁeld. As adults seek continuing educational experiences that support their lifelong learni ng goals, colleges and uni- versities will need to adjust, again, their expectations and deﬁnitions of learnin g for these students. An instructor may ﬁnd it difﬁcult to expect the same moti- vation and quality of work from a traditional-age college student as he or she does from an adult learner who already has one degree but who enrolls in courses to learn more. Adult Development Across the Life Span As a movement, lifelong learning has changed the way educators and psychologists think about cogni- tive development. As adults continue to learn through- out their life span, previously held views of cognitive stage development may need alteration. Jean Piaget’s theory of cognitive development holds that children 606 Lifelong Learning and adolescents move through stages of development based on their ongoing maturity combined with the inﬂuence of formal education opportunities. Speciﬁ- cally, Piaget theorized that adolescents reach formal operational thought, the highest stage of his cognitive development theory, only when they are afforded the experience of formal education. Erik Erikson posited that humans go through broad stages, not speciﬁcally cognitive, across the life span, which reﬂect tradi- tional and historical biographies: establishing families, raising children, growing older, and evaluating one’s life. But neither Erikson’s maturation through the life span nor Piaget’s cognitive development stages explain the developmental process of adults who con- tinually seek out and are transformed by learning experiences. Theorists such as William Perry suggested that the process of learning in college affects students cogni- tively and ethically in four broad categories. In the ﬁrst category, dualism, Perry suggests that students focus on the extremes of intellectual ideas, that knowledge is right or wrong, good or bad, and that experts or authority ﬁgures hold the answers. In the next category, multiplicity, students move slightly from the dualist perspective in that they begin to let go of absolute thinking. This is a confusing time for students because they have to let go of some of their past ideology to make room for more knowledge, but in part they still seek to know the ‘‘right’’ answer. The third category, relativism, occurs when students resolve their ‘‘need to know the right answer’’ by framing ideas or choices as relative to the circum- stances. Authority ﬁgures are seen as a source of information but not the only source, for in this stage, students begin to see their own ability to analyze and interpret information as signiﬁcant. In the last cate- gory, commitment to relativism, students adopt the thinking that most ideas can be relative to the situa- tion but that they must choose the best course of action or thinking for themselves. Perry’s stages of cognitive development were developed as a model of understanding how formal education affects the thinking of students. But the effects of formal educatio n on adults who continue to pursue educational opportun ities across their life span are not known. Drawing from Perry’s work, it is possi- ble to see that if formal education can facilitate cogni- tive development, then c ontinuous learning across the life span would also have an effect on cognitive development. Jack Mezirow suggests that cognitive development occurs when a dults critically reﬂect on assumptions. For Mezirow, critically reﬂecting on assumptions requires examining suppositions of ideas and is the key factor in adult learning. As adults con- tinue to pursue education ac ross the life span, educa- tional psychologists will have more opportunities to study how lifelong learning affects adult development. Within the new ﬁeld of andragogy, the study of how adults learn, researchers attempt to determine what strategies are best suited to help adults learn. Ser- guey Zmeyov says that adult learning is based largely on the learner’s life experien ce, with all learning being ﬁltered through those expe riences where the ‘‘self’’ becomes an active mediator in the learning process. In this view, the learner and teacher act cooperatively because the adult learner has self-awareness and is actively involved in his or her own learning. But fur- ther research is needed to determine how choosing continuous learning as an adaptive function of post- modern life affects adult c ognitive development. Lifelong Learning in Recent Historical Context In the United States, both the industrial revolution and the technology revolution solidiﬁed the global postmodern perspective by changing what and how adults learn. Folke Glastra, Barry Hake, and Petra Schedler have theorized that globalization and indi- vidualization have intersected to create societies that must continually adjust to stay current in hypercom- petitive economies. These cultural and economic shifts are imperative to the understanding of how life- long learning developed and how the pattern of life- long learning represents a change in the way adults view and adapt to the world. Unparalleled changes in the world of work during the past century set the stage for a new shift in think- ing about the world of work. Speciﬁcally, modern workers transitioned from trades to factory positions during the Industrial Revolution. The factory worker learned to operate new machines or risk the unem- ployment line. The invention of the light bulb gave way to round-the-clock shift work, forcing workers to adapt to new living patterns. The transition from trade to factory work created a need for workers to embrace new machines, new techniques, and new learning about the world of work. In the spirit of enterprise and innovation, with workers being ‘‘trained’’ for speciﬁc jobs and not lifetime trades, the Industrial Lifelong Learning 607 Revolution moved forward, carrying many countries into economic prosperity. World War II marked another major shift in the movement toward lifelong learning. The G.I. Bill launched hundreds of thousands of adult learners into the institutes of higher educ ation. Eager not to disrupt the current economy with the sudden inﬂux of return- ing soldiers, the government could not have foreseen the far-reaching effects of adult learners in classrooms. At that time, most Americans did not receive a college education, as it was preserved for speciﬁc professions and the ﬁnancial aristocracy. With postsecondary edu- cation now ﬁnancially accessible, American soldiers took advantage of this oppo rtunity to integrate new knowledge into their lives with formal college degrees. This new generation of adult learners, now armed with degrees, launched into the booming postwar economy to eventually reshape the world of work. The social repercussions, however, could not have been easy to predict. Veteran fathers who returned home from the war and earned degrees went on to create families where higher education was an expectation for their children, not just an option. For the ﬁrst time, middle- class children were being sent to college. In short, learning was becoming a social value. Since the 1960s, cultural and social traditions have become decentralized from the human experience. This has had profound implications on the way adults work, learn, and make decisions about working and learning. Whereas social institutions reigned supreme in the mid-20th century, today, the individual is hon- ored with the authority to choose the path that is best for him- or herself. Paul Belanger described the change as a new concern for personal growth and search for self-identity that signaled major changes in life patterns and increased life path diversiﬁcation. This focus on the individual has created space for individuals to pursue more opportunities, more learn- ing, and new identities. Globalization and the Future of Learning Today, as companies compete globally for business, employees must compete with more and more candi- dates for fewer jobs. Thus, the need to stay competi- tive, to learn more, and to produce more seems to be increasing. Today’s employee is called upon to multi- task, be multiskilled, and transfer those skills from organization to organization. Remaining competitive in the world of work means embracing new learning, new ideas, and new strategies. Adaptability is the heart of this new economic revolution, and lifelong learning represents the personal adaptation that more and more adults are choosing. The topic of lifelong learning is currently being researched primarily outside of the United States, par- ticularly by several European nations. The United Kingdom has a government-sponsored department of lifelong learning charged with supporting citizens in their vocational preparation and ﬁeld transitions. As the international community examines the effects of global- ization on the world of work, lifelong learning will con- tinue to be explored. Formal and informal education demands are on the rise in every competitive industrial- ized nation. Lifelong learning is, therefore, a global education trend that demands further examination. Tiffany Lynnette Arrington and Patricia A. Lowe See also Adult Learning; Cognitive Development and School Readiness Further Readings Belanger, P. (1994). Lifelong learning: The dialectics of ‘‘lifelong educations.’’ International Review of Education , 40 , 353–381. Crow, S. R. (2006). What motivates a lifelong learner? School Libraries Worldwide , 12 , 22–34. Glastra, F. J., Hake, B. J., & Schelder, P. E. (2004). Lifelong learning as traditional learning. Adult Education Quarterly , 54 , 291–307. Gorard, S., & Selwyn, N. (2005). What makes a lifelong learner? Teachers College Record , 107 , 1193–1216. Kett, J. F. (1994). The pursuit of knowledge under difﬁculties: From self-improvement to adult education in America, 1750–1990. Stanford, CA: Stanfo rd University Press. Love, P. (1999). Understanding and applying cognitive development theory . New Directions for Student Services , 88 , 5–99. Mezirow, J. (1998). On critical reﬂection. Adult Education Quarterly , 48 , 185–198. Zmeyov, S. I. (1998). Andragogy: Origins, developments and trends. International Review of Education , 44 , 103–108. L ITERACY Four senses of the term literacy can be distinguished. First, literacy is simply the ability to read and write; it is the set of basic skills that provide individuals with 608 Literacy entry into the realms of written language and commu- nication. Second, literacy is sufﬁcient competence in reading, writing, and computation (numeracy) required to meet the demands of daily life. In this second sense, literacy represents a threshold of functional competen- cies that allow an individual to adapt to the demands of a complex and technologically sophisticated society. It is a pragmatic perspective linked to skills essential to employment, personal ﬁnances, consumer behaviors, and family life. Third, literacy is the state of being highly educated, well read, well informed, and knowledgeable in the realms of culture, art, music, literature, history, eco- nomics, science, technology, mathematics, geography, politics, and public affairs—as such, it enables full par- ticipation in the cultural, economic, and political life of the society. A college-level education and preparation to enter a profession are commonly recognized as indi- cations of literacy in this sense of the term. Fourth, literacy is a characteristic of a social or cultural group. Literacy, in this sense, like language, can be regarded as varieties of cultural practices that entail the creation and use of texts. Individuals are lit- erate to the extent that they may participate in the lit- erate social activities that are important to the social groups to which they belong. In education and psychology , theorists and practi- tioners have, for the most part, addressed literacy as the acquisition of the skills and competencies required for reading and writing. Throughout the past century, research and practice have been directed toward discov- ering the complex perceptual processes, cognitive sys- tems, motivational factors, and social contexts that underlie an individual’s ability to read and write and toward devising the most efﬁcient methods to teach those skills. Basic research has drawn from all branches of learnin

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g theory, educational psychology, child and adolescent development, cognitive science, neurology, sociology, and cultural anthropology. Applied research has examined alternatives in teaching and instructional practices, in the development and implementation of curriculum and curriculum standards, in support for children and adolescents with learning disabilities and other special needs, in support of English language learn- ers, and in assessment and evaluation practices. Policy Debates That literacy is essential for citizenship and for full participation in the cultural, political, and economic life of a free society is one of the most fundamental tenets of American education. There is agreement on all sides that illiteracy and marginal literacy preclude equal opportunities for employment, education, and civic engagement. Yet, despite decades of research and the repeated promises of developers of innovative approaches to teaching and learning, there are, by var- ious estimates, between 20 and 50 million Americans who are functionally illiterate. The ‘‘literacy crisis’’ has prompted ﬁerce controversies in educational the- ory and practice, which range from concerns for the relative success of alternative methods of instruction in reading and writing, to the value of liberal educa- tion, to the wholesale critique of public schooling in this society. In recent decades, scholarly discourse on literacy has been replaced often by bitter debates and partisan political battles. In the 1 960s, it was the ‘‘great debate’’; more recently, it has been the ‘‘reading wars.’’ The No Child Left Behind Act of 2001 codi- ﬁed elements of these debates into federal law, which requires that approved curricula for the elementary grades must now be based on these ﬁve essential com- ponents of reading instruction: phonemic awareness, phonics, vocabulary, ﬂuency, and comprehension. In an effort to address the public controversies surrounding literacy in the United States, a series of reports and policy statements have appeared from the national professional organizations: International Reading Association, National Council of Teachers of English, National Association for the Education of Young Children, the National Institute for Child Health and Human Development, the National Research Council, the National Reading Panel, the U.S. Department of Education, and many other agen- cies, associations, and organizations. The collective purpose of these efforts has been to establish clear understandings of what the best research has revealed about literacy and to outline areas requiring further research. Although there are continuing controversies about speciﬁc topics, such as the most effective approaches to phonics (or the learning of phoneme- grapheme, or letter-sound, correspondences), there is general agreement among psychologists and educators about how children acquire language and develop competencies in reading and writing, as well as other dimensions of literacy. The present consensus pro- vides a sensible framework for understanding literacy development and the roles of parents and teachers who support children’s literacy learning. In the Literacy 609 corresponding policy debates, there is also growing consensus, although some sharp disagreements remain concerning accountability, funding, and the allocation of resources to low income, linguistic minority, and special needs populations. Evidence indicates that literacy learning is not in precipitous decline. Over the past 25 years, the National Assessment of Educational Progress has found that reading skills have remained virtually unchanged. These results suggest that schools con- tinue to foster literacy development under conditions of increased immigration, shifting demographics, and the persistent achievement gap. American students continue to perform well in international comparisons in the fourth grade and at age 15, but relative perfor- mance declines sharply for the lowest quartile of U.S. scores in comparison to other countries. That suggests greater variability in performance and diminishing success for a signiﬁcant number of lower-performing students as they enter the high school years. These data have prompted researchers and policy makers to continue the search for large-scale solutions to a per- ceived literacy crisis. Literate Social Practices Conceptions of literacy that emphasize individual skills and achievements may tend to overlook the essentially social nature of literacy. Literacy is more than simply the ability of individuals to read and write. It is a characteristic of soc ial and cultural groups that engage in social activities that entail the creation and use of texts. Individuals are literate to the extent that they do participate in the lit erate social activities that are important to the social groups to which they belong. In this sense, children become literate by a combination of particip ation in informal engage- ments with texts (e.g., observi ng parents’ literate activ- ities, sharing in storybook reading) and in formal instruction with adults directed toward learning- speciﬁc aspects of the complex competencies that comprise literacy (e.g., deli berate teaching of letter- sound correspondences, rea ding comprehension strate- gies, procedures for organizing and composing an essay). What educators mean by literacy and how they understand the nature of learning and development will determine the nature of teaching practices that would create the conditions a ppropriate to invite learn- ers to become competent part icipants in the literate social practices that have genuine meaning for them. Literacy is participation in the socially embedded, purposeful activities that occur among members of a linguistic community (speakers, readers, and writ- ers) and the texts they create and use to construct and share meanings and intentions. It follows that the development of literacy is the acquisition of the com- petence to fully participate in the literate social prac- tices valued by that social group. Children acquire cultural competencies by immer- sion and participation in the daily activities of the community. When oral and written texts (e.g., prayers and storybooks) are involved, children also become literate as they learn to participate in the use of these texts. Upon entering school, children are exposed to a new set of social practices, a new community hav- ing its own rules concerning the use of language and literacy. Because all social practices are learned in relation to those already learned, the acquisition of the literate social practices of schools will depend on the cultural relationship between home and school. Academic English Research and practice that focuses on English language learners, and on speakers of dialects that diverge signiﬁcantly from standard English, have drawn attention to the distinctive characteristics of academic English and its relationship to literacy. It is widely recognized that students who complete high school and are well prepared to enter college need to have command of academic English, which includes rich vocabulary, advanced reading comprehension, control of complex syntax, and competence in stan- dard written English. It is also widely recognized that schooling alone cannot provide sufﬁcient oppor- tunities to achieve all the necessary competencies. Regarding vocabulary, for example, it is estimated that, in one school year, it might be possible to directly teach about 1,000 new words, but it is also estimated that to be well prepared to enter college requires a receptive vocabulary of 80,000 words. If direct teaching is insufﬁcient to accomplish this goal, then informal and incidental learning are required. Moreover, the student must have access to Latinate words (e.g., inundate for ﬂood ) and other learned borrowings into English. Access to academic English requires extensive reading of complex texts and routine exposure to those literate social practices that typify literacy in the 610 Literacy sense of becoming highly educated. Students whose parents are well educated will tend to have greater exposure to academic English. For all other students, the schools become the chief source of opportunities to acquire the discourse patterns used in higher educa- tion and the professions. The core of everyday English, as is well known, comes down to present times from Anglo-Saxon (as well as Old Norse—examples include get, want, give). Yet, it is estimated that perhaps 75 % of the English lexicon derives from French, Latin, Greek, and assorted other languages, and many of these are regarded as scholarly or academic words not generally used in everyday spoken communication in the home and com- munity. Access to literate language in the sense of aca- demic English is also a condition of access to literate social practices that provide entry to higher education and corresponding economic opportunities. Emergent Literacy Research efforts of the past 40 years have made tre- mendous progress in understanding the genetic, neu- rological, physiological, cognitive, and social systems that make possible the acquisition of language and social communication. Among the core ﬁndings are the following: 1. All human societies use language, and all children acquire their native language—with the relatively rare exception of those who suffer signiﬁcant impairments in one or more of the systems that support language. 2. The 5,000 to 6,000 languages that exist among the cultures of the world today have abstract features in common, and all particular languages are but variants of ‘‘human language’’; the common or uni- versal features of human languages are given by human genetic endowment. 3. Native language acquisition occurs rapidly without formal or expert instruction. By age 5 or 6, children have acquired the core features of all the rule sys- tems that govern language form and use. 4. The broad stages of language acquisition are invari- ant across cultures and languages, although at ﬁner levels of analysis, patterns of individual differences emerge. 5. Language is acquired in use; it is a meaning- making process through which children construct or reinvent the language while engaged in genuine communication. 6. Speciﬁc features of the social environment account for the speciﬁc language children will acquire; that is, children will acquire the linguistic patterns of their parents and members of their immediate communities. 7. Speciﬁc features of the linguistic environment account for some of the differences in the nature of language acquisition between and within groups, for example, using speciﬁc discourse styles, devel- oping a large vocabulary, or learning modes of politeness. Human language is a complex system that relates sound to meaning. An adequate description of lan- guage requires, at minimum, the recognition of multi- ple, interacting subsystems, each of which must be acquired: pragmatics, semantics, syntax, morphology, phonology, and the lexicon. Language production and comprehension require the simultaneous, rapid pro- cessing of information from all subsystems, which are acquired without conscious reﬂection or formal instruction. Literacy develops upon the foundation provided by language acquisition for children who are raised in a literate social environment. From the earliest recog- nition of street signs and product logos, to the earliest experiences with books, stories, and other texts, chil- dren’s literacy development interacts with language development. For example, lexical development (vocabulary) is an astoundingly rapid process. By age 3, a typical child will have a receptive vocabulary of 1,000 words. By age 6, a conservative estimate will be 10,000 words. Children who are richly exposed to the language of books will tend to acquire a more var- ied, rich vocabulary, which will, in turn, enable them to successfully engage with ever more challenging texts. Children who are exposed to the alphabet from an early age will begin to associate letter names with the visual letters and later will begin to associate some speech sounds with letters. Nursery rhymes and chil- dren’s songs and poetry will help children recognize (and become ‘‘aware of’’) features of speech sounds and words, for example, rhymes linking ending sounds of words and alliteration drawing attention to beginning sounds. Taken together, such experiences support phonological development and, in particular, phonemic awareness. Literacy 611 Family literacy provides children with many opportunities for learning the basic features of oral and written language. When parents read to children, or tell stories, sing songs, share family histories, say prayers, and so forth, they are providing opportunities for children to experience the pleasure of powerful texts and to become sensitive to the structures of nar- rative. Children’s listening comprehension for texts will far exceed their independent reading skills for most of the elementary school years. Finally, children who are given opportunities for writing in the preschool years will have further occa- sions for linking letters to sounds to meanings. Whether with magnetic letters, alphabet blocks, pens and pencils, or computer keyboards, children will string together letters in an attempt to ‘‘write’’ and to have adults ‘‘read’’ their creations. What children begin to learn is that written symbols correspond to speech. All early literacy experiences provide children with richly important opportunities to learn the rela- tion between print and language. Under the circumstances of exposure to a genuinely bilingual home or community, children from infancy can develop two languages simultaneously. In many places in the world, bilingualism is the norm. When children are immersed in a second language during the preschool years, and where that language is used for the full range of communicative purposes, children can achieve ﬂuent bilingualism to the same levels of competence of monolingual children within a few years. However, when children ﬁrst encounter a sec- ond language in the context of an elementary school classroom, where instruction (and especially literacy instruction) is primarily in the second language, then the children will face greater challenges in acquiring that language and developing literacy. Greater home support for the two languages and literacy in both languages will make it more likely for children to succeed. Children whose home language is other than English may appear to be ﬂuent in English because they have acquired the ‘‘language of the playground’’ during preschool and kindergarten experiences. How- ever, some of these children will exhibit ﬂuency but not have achieved proﬁciency in the language to the level that will readily support literacy development. A ﬁrst grader whose home language is other than English may appear ﬂuent even if the child has com- mand of only 1,500 words of English. That number, however, is far less than the 10,000 or more words known by the monolingual English child growing up within a literate family. On the other hand, the child whose home language is, for example, Spanish, and whose parents provide a literate home environment in Spanish, will acquire the essential early literacy com- petencies in Spanish and be better prepared to transfer those competencies to the English-speaking context. Beginning Literacy Children who enter school with those experiences that support language development and early literacy learning begin more formal literacy instruction with • knowledge of the language, • an extensive vocabulary, • initial phonemic awareness, • knowledge of environmental print, • knowledge of the alphabet, • awareness of the organization of books and stories, • experience with writing, and • knowledge of some letter-sound correspondences. Some children will also know some words and names by sight. They may also have memorized favorite stories or songs which they can ‘‘pretend’’ to read, and they may have dictated or written their own stories with the help of parents, siblings, or other care- givers. A few children will have become ‘‘early read- ers’’ who can read independently (whether silently or aloud) from so-called chapter books that are com- monly read in third or fourth grade. Children who have not been exposed to the infor- mal opportunities for literacy learning in the home will enter kindergarten and ﬁrst grade with a distinct disad- vantage. In addition, children whose home language is other than the language of the schools will have the greatest challenge if they are expected to both learn the language of the school and begin to read and write for the ﬁrst time in the unfamiliar language. Kindergarten and ﬁrst-grade classrooms should provide a literate environment; that is, teachers and students should engage in literate social practices for authentic purposes in order to continue the powerful informal learning that underlies language acquisition and home literacy learning. Children need to share with each other and to participate in reading and writ- ing activities with competent adults who can model their own literacy. Teachers need to read aloud from the best of literature for children, as well as encourage 612 Literacy children to read for themselves by ﬁrst engaging in shared reading and guided reading. Similarly, teachers need to support children’s writing with varied oppor- tunities, ranging from taking dictation, to shared and guided writing, to independent writing. Informal learning should be complemented by for- mal instruction. To succeed in becoming literate, some children may need only to be exposed to com- petent models. Most children, however, will also require direct instruction that will guide them through the intricacies of letter-sound correspondences, the vast number of irregularities of English spellings (both for reading and writing), the complexities of comprehension across diverse genres, and the chal- lenges of writing narrative and exposition for various audiences. A number of children—estimates range from 1 % or 3% all the way to 10 % or 20 % —will experience greater difﬁculties achieving literacy, even when English is their ﬁrst language and their parents provide a literate home environment. These children will require further, expert direct instruction, such as that provided by Reading Recovery, or other one-to- one tutor programs. Research clearly indicates that early, intensive intervention is more likely to be suc- cessful than later interventions. Direct, planned, explicit instruction may take many forms. Researchers and practitioners continue to dis- pute the exact nature of direct instruction. Some call for rigid scripts, lesson sequences, highly controlled texts, and heightened attention to isolated, speciﬁc features of print, for example, letter-sound correspon- dences (sometimes referred to as phoneme-grapheme relations). Others call for direct instruction in the con- text carefully chosen, quality literature that will main- tain a meaningful context while also allowing success (reading with comprehension) and attention to speciﬁc features of print. Collections of recommended books are sometimes ‘‘leveled’’ in an effort to more accu- rately determine appropriate ‘‘instructional-level’’ materials. Greater training of teachers and greater varieties of books and materials are required for the latter approach. The general consensus of teachers in the ﬁeld is that a balanced or integrative approach is best, with ﬂexibility in arrangements of whole class, small group, and individual instruction, which itself ranges from well-crafted informal learning environments to expertly planned formal learning opportunities. The primary goal of an integrative approach is to sustain meaningfulness within an authentic literate classroom environment, while also providing explicit, direct instruction where it is judged to be most needed, including judicious attention to practice with isolated features of the language. Children need time to read and write for pleasure and for the range of authentic purposes. Instruction should build on prior knowl- edge, provide support where needed (scaffolds), and present challenges in reasonable measure to advance children’s competencies. Moreover, instruction should be guided by careful observation and ongoing assess- ment of children’s successes and struggles; thus, instruction is responsive to the requirements of spe- ciﬁc children in speciﬁc circumstances. Reading and writing, like language processing (lis- tening and speaking), require the simultaneous, rapid processing of multiple levels of information; this is also called parallel processing. At a minimum, the levels include • orthographic (letters, spellings, capitalization, punctuation), • phonological (sounds), • morphological (word forms, plurals, tenses, preﬁxes, sufﬁxes, etc.), • syntactic (clause structures and sentences, larger discourse), • lexical (properties of words, including sounds, spellings, and meanings), • semantic (meaning and comprehension), • pragmatic (intentions, e.g., narrative and expository), and • cultural (e.g., assumptions, background knowledge, and cultural expectations). Fluent, independent reading and writing require competence within each of these levels of processing. Instructional approaches tha t substantially neglect cer- tain levels while attending exclusively to others, or that focus on reading while neglecting writing, will be less successful in supporting full literacy development. Development Toward Independence If English provided a perfect alphabet system, then it might be possible for children to learn the alphabetic principle (letter-sound correspondences) in 2 or 3 months in ﬁrst grade, and then all other language arts instruction would be directed toward developing lan- guage: greater vocabulary, more subtle comprehen- sion, writing for an audience, greater knowledge of Literacy 613 the physical and social world through texts. Learning to read, as such, would be very easy. The complexity of the English orthography tends, however, to require 3 or more years for children to gain independence in reading sufﬁcient to take full advantage of their oral language competence. Learning to spell in English becomes a lifelong challenge for many, including many well-educated adults. Learning to read (accurately, ﬂuently, and with comprehension) requires both frequent access to demonstrations of mature literacy by competent models and continued direct instruction in effective strategies throughout elementary school. The same may be said for learning to write (including spelling, punctuation, and conventions of composition). Both reading and writingshouldbeblendedwithotheraspectsof language development and language arts instruction. Discussions about the role of phonics in reading instruction often ignore that in learning to write, chil- dren are confronted with the complementary problem of discovering the appropriate letters to represent sounds. They soon learn that letter-sound correspon- dences can take one only so far; word knowledge will be required to make furthe r progress (e.g., consider homonyms, such as pear, pair,and pare,orwordswith a common root, such as native, nation,and nature). Thus, second- and third-grade instruction should continue the practices initiated in kindergarten and ﬁrst grade, carefully advancing the richness and the challenges of the literate environment (sustaining informal learning), while continuing direct instruction where needed as children encounter ever more com- plex features of English. Exposure to larger vocabu- laries, wider varieties of text, and more complex ideas requires expert instruction that includes continuous assessment of the progress of individual children and the willingness to make instructional decisions based on that information. An integrative approach remains the consensus of experts in the ﬁeld, though differ- ences of opinion persist concerning the day-by-day, lesson-by-lesson recommendations. Those differences remain largely matters of emphasis. Developing Proficiency and Fluency Extending the practices outlined in the previous section, the goals of the intermediate grades shift from learning to read to reading to learn—across the curriculum. Reading and writing are directed toward developing knowledge and understanding in an ever-expanding range of texts, genres, and purposes. Students continue to need opportunities for collabora- tive, informal learning within an authentic literate environment where teachers continue to model their competencies. They also continue to need explicit demonstrations, direct instruction, opportunity to prac- tice, encouragement to achieve ﬂuency as well as precision, and high expectations. Students need to engage in literacy for authentic purposes, for example, to write for genuine audiences (beyond the classroom teacher alone) and to read for interest, pleasure, and self-directed learning. Those students who, for various reasons, are still struggling with beginning reading and writing require special opportunities, individually or in small groups, for accelerated learning, guided by master teachers with the goal of having them catch up to their peers. Such instruction will be directed toward the students’ greatest challenges (e.g., phonics, comprehension strategies, or gaining necessary knowledge of English) and will support and build upon those areas within which the students have the greatest successes. Late interventions are less likely to achieve rapid results than earlier interventions, and they will tend to require greater allocation of resources. Support for home liter- acy and English language learning should be incorpo- rated where appropriate. Literacy Programs In the United States, a long tradition of cooperation exists between school systems and numerous publish- ers and curriculum developers, who also work closely with national professional associations and universi- ties, in the design of literacy programs. At present, more than 20 well-known reading and writing pro- grams are available from publishers, foundations, and universities, and each offers attention to • mechanics of reading (graphophonemic details, visual processes), • reading comprehension (strategies, purposes, and critical reading), • literature (varied genres), • spelling and punctuation, • word knowledge, vocabulary, • grammar and conventions of written language, • writing expressively and persuasively (with revision and editing), 614 Literacy • approaches to maintaining motivation and pleasure in literacy, • approaches to integrating the language arts and liter- acy across the curriculum, and • using reading and writing as tools for thinking and learning about the world. Each also provides some form of assessment or recordkeeping procedures to aid teachers and adminis- trators in ongoing program pl anning. Most also include attention to new technologies. Some focus on chil- dren with speciﬁc difﬁculties (e.g., dyslexia or other reading disabilities), and others focus on the needs of children acquiring English as a second language. Yet, all draw from the same understandings of what reading and writing entail and what variety of class- room activities are available to support literacy development. Publishers and program developers have combined, balanced, and integrated the differ- ent elements in the previous list, each with some dif- ference in emphasis. There is no experimental research that deﬁnitively identiﬁes one variant program as superior to another. Such research is not even possible because of the practical limits of experimentation with human sub- jects in the real world. When critics demand proof from randomized, experimental ﬁeld studies, they must settle for small-scale studies completed with small populations in speciﬁc locations, with particu- lar, uncontrolled local conditions. Sorting through this research was indeed the task of the National Research Council (see Preventing Reading Difﬁculties in Young Children , 1998) and the National Reading Panel (results published by the National Institute of Child Health and Human Development, in 2000). Their ﬁndings mention a few speciﬁc programs but focus on underlying, common features that have been shown to contribute to the success of various programs. Socioeconomic Conditions All children throughout the world acquire their par- ents’ language—the ‘‘mother tongue.’’ All learn the discourse patterns of their families and communities. Language is universal, but l iteracy is not. In addition, the conditions of schooling and literacy are not equally distributed in society. It is well established tha t socioeconomic conditions are powerful predictors of both literacy and school suc- cess. Where it is possible to establish good measures of family literacy (levels of parents’ education and liter- acy practices in the home) and sensitive measures of family support for schooling and literacy (e.g., parents’ beliefs about the value of school success and literacy), these factors can be combined with economic condi- tions to produce multiple correlations that reach .8 or higher. What this suggests is that the unique contributions of the schools (and teachers) should be understood in relation to other social c onditions. It follows that research that focuses exclusively on school-based con- ditions will be overlooking important, powerful condi- tions. Also, it follows that only marginal differences will be found by new research into competing school- based programs, which, with minor differences, are themselves guided by the same body of knowledge and understandings of li teracy development. In the current debates on literacy, there is an astounding silence on these issues. Most reports focus on the school or the classroom and largely avoid the larger social issues. In the call for consensus and the pressure for ‘‘best practices,’’ there is an explicit bias toward considering only the scientiﬁcally based research, which is deﬁned to mean only rigorously con- trolled experimental and qu asi-experimental designs. Because students (and parents) cannot be randomly assigned to socioeconomic categories, those variables, arguably the most powerful, are recognized in most research designs only as the ‘‘co-variates’’—that is, efforts are made to control them rather than to directly investigate them. Other research approaches, especially ethnographic models, which can more fully investigate sociocultural and economic inﬂuences, are given less attention in the current reports. Quantiﬁcation, control, and replication are preferred over long-term, careful documentation of complex systems. Future Directions The biological and social foundations of language acquisition are now reasonably well understood. In a similar sense, the nature of family literacy and school curricula that support reading and writing and the full scope of literacy development are well under- stood. Questions remain as to how best support lan- guage and literacy for children with special needs and for children who are learning English as a second lan- guage. There is consensus, however, that excellent and expert teaching succeeds when conditions are most conducive, especially in relation to community Literacy 615 support and to institutional variables such as the num- ber of children who are to receive attention at the same time from the teacher. Children beneﬁt the most when teachers can move ﬂexibly among large-group, small-group, and individual modes of instruction. The general consensus of teachers in the ﬁeld is that a balanced or integrative approach is best, with both expertly planned formal learning opportunities and well-crafted informal learning environments (including competent models and demonstrations). The primary goal of an integrative approach is to sus- tain meaningfulness within an authentic literate class- room environment, while also providing explicit, direct instruction where it is judged to be most needed. Moreover, instruction should be guided by careful observation and ongoing assessment of chil- dren’s successes and struggles; thus, instruction will be responsive to the requirements of individual chil- dren in speciﬁc circumstances. Continued investigation of the social, linguistic, economic, and political cond itions of literacy develop- ment should be included within the current attention to best practices and experimental research efforts to compare one speciﬁed program with another. Only then will we have the opportunity to move closer to universal literacy a nd full participation in the cultural, economic, and political life of this society. William T. Stokes See also Assessment; English as a Second Language; Reading Comprehension Strategies Further Readings Adams, M. J., (1990). Beginning to read: Thinking and learning about print. Cambridge: MIT Press. Berliner, D., & Biddle, B. (1995). The manufactured crisis: Myths, fraud, and the attack on American public schools. Reading, MA: Addison-Wesley. Chall, J. S. (1983). Stages of reading development. New York: McGraw-Hill. Clay, M. M. (1991). Becoming literate: The construction of inner control. Portsmouth, NH: Heinemann. Cunningham, P., & Allington, R. (2007). Classrooms that work: They can all read and write (4th ed.). Boston: Pearson. Durkin, D. (1966). Children who read early. New York: Teachers College Press. Holdaway, D. (1979). The foundations of literacy. Sydney, Australia: Ashton Scholastic. Kozol, J. (1985). Illiterate America. New York: New American Library. National Institute of Child Health and Human Development. (2000). Report of the National Reading Panel. Teaching children to read: An evidence-based assessment of the scientiﬁc research literature on reading and its implications for reading instruction (NIH Publication No. 00–4769). Washington, DC: U.S. Government Printing Ofﬁce. National Research Council. (1997). Improving schooling for language-minority children: A research agenda (D. August & K. Hakuta, Eds.). Washington, DC: National Academy Press. National Research Council. (1998). Preventing reading difﬁculties in young children (C. Snow, M. S. Burns, & P. Grifﬁn, Eds.). Washington, DC: National Academy Press. National Research Council. (1998). Starting out right: A guide to promoting children’s reading success. Washington, DC: National Academy Press. Pinker, S. (1994). The language instinct: How the mind creates language. New York: William Morrow. L ONGITUDINAL R ESEARCH Longitudinal research is generally deﬁned as studies that investigate change over time with the same cohort(s). This deﬁnition characterizes four key fea- tures of longitudinal research. First, by change , it means that longitudinal studies focus on a dynamic process rather than a static status as the outcome variable. A process is a series of changes from the initial status to the ﬁnal status through various intermediate statuses. In a methodolog- ical term, one status is often called one wave. Thus, longitudinal studies use multiple waves to represent a process. Second, by over time , it means that longitudinal studies must include the time dimension as the funda- mental predictor. A multiwave process can be consid- ered as a function of time, and various substantive predictors (e.g., gender or IQ scores) can be used to explain the process, as in nonlongitudinal studies. Third, by with the same cohort(s) , it means that longitudinal studies typically measure the same group of individuals (i.e., one cohort) repeatedly over time to examine the intraindividual changes (e.g., each stu- dent’s reading development) as well as interindividual differences (e.g., gender differences in reading devel- opment). In some cases, a longitudinal study repeat- edly measures just one same individual (e.g., the single-subject study) or multiple cohorts (e.g., the 616 Longitudinal Research cohort-sequential study). Longitudinal studies focus on changes within the same cohorts, whereas cross- sectional studies focus on differences across different cohorts. Fourth, by investigate, it means that longitudinal studies are not limited to repeated measurement or analysis of change over time. Instead, longitudinal design, longitudinal measurement, and longitudinal analysis represent not only t he three areas of longitudi- nal research methodology as an established ﬁeld of study but also three major phases of a longitudinal study. Learning, teaching, educat ion, development, inter- vention, and various psychological processes are essen- tially intended to produce desirable changes among human beings. Thus, focusing on change over time, longitudinal research can be considered the method of choice for the social and behavioral sciences in general and educational psychology in particular. This entry presents basic methodologic al issues of longitudinal design, measurement, and ana lysis and provides real- life examples of empirical longitudinal studies. Longitudinal Design Longitudinal design concerns how to collect longitu- dinal data to address longitudinal research questions. To study children’s social development, for instance, Anthony Pellegrini and his collaborators conducted a longitudinal study to examine games (e.g., chanting, chasing, playing balls, jumping rope, clapping) that the ﬁrst graders played on the school playground. Speciﬁcally, they addressed two major research ques- tions: whether there were any changes in games and why these changes occurred. They chose to use a sin- gle cohort, a total of 77 students in all ﬁrst-grade clas- ses from two neighboring schools. They collected three waves of data, mainly observing the change in frequency and variation of these students’ games that were played in September, January, and May. They focused their observations on children’s games at recess, a good time window to see children’s free interactions at school, during their entire ﬁrst-grade year as their ﬁrst experience of full-day mandatory schooling in the 1995–1996 school year, with an interval of over 3 months. They found that there was a signiﬁcant increase in frequency of game activities over the entire year, and this increase was signiﬁ- cantly inﬂuenced by gender and ethical differences. This example illustrates that at least four speciﬁc issues, the question design, cohort design, wave design, and time design, need to be considered care- fully in designing a sound longitudinal study. First, a longitudinal study must address research questions that are clearly related to change over time. There are generally three kinds of research questions with a longitudinal nature: (1) Does change occur over time? To answer this question, researchers must examine the initial status and ﬁnal status of a process (e.g., examine the frequency of ﬁrst-graders’ games played on the school playground in September 1995 to May 1996). (2) How does change occur over time? To answer this question, researchers must look at the initial status, ﬁnal status, and a few intermediate statuses of a process (e.g., observe the frequency of ﬁrst-graders’ school playground games in September, January, and May). (3) Why does change occur over time? To answer the why question, researchers need to examine not only a multiwave process but also var- ious substantive predictors that might contribute to the process (e.g., estimate both gender differences and race differences in changes of school playground games in the ﬁrst-grade year). Second, it is important to decide how many cohorts will be used. In education and psychology, a typical longitudinal design is a quasi-experimental design; that is, one single nonrandomize d cohort is investigated repeatedly over time. To address different research ques- tions, longitudinal researchers have used a wide variety of longitudinal designs, such as intervention design, cohort-sequential design, microdevelopmental design, life-span study design, nonexperiment design, and even occasionally true-experim ental design that randomly assigns human subjects to experiment and control groups to increase internal validity. Longitudinal methodologists Judith Singer and John Willett recommended the cohort- sequential design for effecti vely collecting longitudinal data in a limited time period by studying multiple age cohorts simultaneously. Third, it is also important to determine how many waves of data need to be collected. Two waves of data enable the researcher to address only the research question of whether change occurs over time, whereas three or more waves of data help the researcher to address the question of how change occurs over time. Singer and Willett found that increasing the number of waves of data collection substantially reduces the standard error of individual rate of change and signiﬁ- cantly increases the reliability of estimated rate of change and thus suggest collecting extra waves of data Longitudinal Research 617 even at the cost of the total sample size. Two types of special longitudinal designs, the time series design and single-subject design, normally include more than 10 waves of data to discover underlying patterns. Finally, longitudinal res earchers need to consider the issue of time thoughtfully, because the precision of estimating individual change depends more on the duration, frequency, interval, and timing of the waves of data collection. For instance, how long must the study last (e.g., 1 semester, 3 years, or 4 decades to capture the target behavioral change)? When will the study start (e.g., age 13 or age 17 to reduce the cohort effect)? What interval should be used (e.g., four times per semester or once per decade to reduce the practice effect)? What speciﬁc time is the best time to collect data (e.g., before the No Child Left Behind Act was implemented or after the Act to avoid the historical effect)? Recently, differing from the time design of conventional longitudinal studies of change over years or decades, microdevelopmental designs that intensely investigate over a short per iodoftimehavebeenexten- sively used by developmental psychologist to capture ongoing transitions in a critical period of time (e.g., examining second-graders’ change in the use of differ- ent arithmetic strategies 10 times within 1 week). Longitudinal Measurement Longitudinal measurement concerns how to develop valid, reliable, and equitable measures for examining behavioral change over time. A longitudinal study normally involves three types of measures: (1) the outcome variable, which can be either continuous or dichotomous but must be time-variant to represent a multiwave process (e.g., initial, middle, and ﬁnal IQ scores); (2) the time predictor, which can be either discrete or continuous but must be sensitive enough to capture change over a speciﬁc time period (e.g., studying early reading development for 3 years with the interval of 3 months); and (3) the substantive pre- dictor, which can be either continuous or dichotomous and either time-variant or tim e-invariant (e.g., gender and change of socioeconomic status over 10 years). These three types of variabl es form the empirical foun- dation for subsequent longit udinal analysis of data, and whether these variables are valid, reliable, and equita- ble determines the quality of a longitudinal research. Marlene Schommer and her collaborators, for exam- ple, examined whether and why there was improve- ment in high-school students’ epistemological beliefs (e.g., ‘‘really smart students don’t have to work hard’’). They developed a 63-item questionnaire on a 5-point Likert scale with adequate va lidity and reliability and used it to assess students’ epistemological beliefs twice as the outcome variable. They focused on the 3-year period between the freshman year to the senior year in the high school between January 1992 and January 1995, with 3 years as the inte rval, as the time predictor. They used gender as the substantive predictor. With these measures, they found signiﬁcant improvement in epistemological beliefs as well as gender main effect (girls had better beliefs) and gender-year interaction effect (gender difference was greater after 3 years). In another longitudinal study, David Kaplan and Sharon Walpole examined 3,575 students’ early read- ing development across kindergarten and ﬁrst grade. Their outcome variable was four-wave dichotomous measures of reading skills, a pass or fail score at a particular skill level on a Gutman scale. They focused on a 2-year period (1998–1999) at four time points (fall kindergarten, spring kindergarten, fall ﬁrst grade, spring ﬁrst grade). The substantive p redictor was poverty status in 1998, a dichotomous predictor of whether the child’s household was below or above the poverty line. Based on these measures, they found that children living below poverty are less likely to e xperience successful reading transitions than their above-poverty peers. A unique and controversial feature in longitudinal measurement is that normally the same instrument ought to be used repeatedly over time to generate time-variant outcome variables or substantive predic- tors. This produces the test practice effect, or penal conditioning effect, which reduces validity and reli- ability of measurement, especially while many waves of data are collected and the between-wave interval is small. Some methodologists suggest avoiding change scores completely, whereas others have considered recently that this pr actice effect is small. In addition, some methodologists suggest developing equitable ver- sions of the same instrument for repeated use (like ETS in building a large item pool for the TOEFL or the GRE), some encourage using dichotomous variables with clear-cut criteria, and others advocate unobtrusive measures through nonac tive observations. Longitudinal Analysis Longitudinal analysis concerns how to analyze longi- tudinal data to address various kinds of research ques- tions about change over time. Regression analysis and 618 Longitudinal Research repeated measures analysis of variance (ANOVA) are two, widely used, simple statistical methods for longitudinal data analysis in educational psychology research. For instance, to examine what factors inﬂu- enced high-risk children’s math achievement scores, Shane Jimerson and others conducted a regression analysis by using ﬁve predictors (students’ years in special education, behavior assessment scores, paren- tal involvement, home environment, and socioeco- nomic status) to predict differences in math scores between Grades 1 and 6 as the outcome variable. The results indicate that only socioeconomic status was the signiﬁcant predictor of the math score difference. Here, regression analysis can handle only two-wave data when the outcome variable is either the ﬁnal sta- tus or the difference between the initial and ﬁnal sta- tus. It is the most rudimental data analysis method. In another study, Pellegrini and others ran repeated mea- sures ANOVA to examine whether and why there were any changes in children’s playground games at recess across the three time points. They used the fre- quency of the total games observed at three time points as the within-subject variable, and gender and race as the between-subject variable. They found sig- niﬁcant effects of time, gender, and race. Better than regression analysis, repeated measures ANOVA can handle three or more waves of data by treating one multiple-wave outcome variable as multiple depen- dent variables in the multivariate analysis of variance (MANOVA) context. Among various newly emerging advanced longitu- dinal data analysis methods, multilevel growth model- ing and survival analysis are among the best tools to effectively analyze multiwave longitudinal data and address complex research questions. For instance, Zheng Yan ﬁtted a basic two-level growth model to examine how and why a group of students’ perfor- mance of using a statistic program changed across four waves for one semester. The level-1 model ﬁtted individual trajectories of students’ performance at four time points to describe within-individual change as a function of time, and the level-2 model further examined the intercept and slope of the average ﬁtted lines to explain between-individual difference as a function of four substantive predictors. The ﬁndings indicate that only students’ previous experience of using computer network systems affected the initial status of learning and that none of four substantive pre- dictors inﬂuenced the rate of learning. The multilevel growth model is powerful, ﬂexible, and integrative in analyzing complex longitudinal data that are not only multiwave but also multilayer (e.g., using structural equation modeling [SEM] for manifest and measure variables), multilevel (e.g., using hierarchical linear modeling [HLM]), multivariable (e.g., using MAN- OVA), and multipath (e.g., using path analysis). While the multilevel growth model can effectively analyze complete continuous longitudinal data, survival analy- sis can effectively analyze complex dichotomous longi- tudinal data. These advanced methods overcome the obvious weakness of regression analysis and repeated measures ANOVA and create new opportunities to entertain rich longitudinal data and address complex longitudinal research questions. Future Directions Although longitudinal research has been performed for more than a century, it has not yet reached its full potential. It is currently enjoying a fast growth and will become a true method of choice in the social and behavioral sciences. The pr omising directions of longi- tudinal research might include (a) addressing research questions about very complex and dynamic changes over time in the real world; (b) performing Internet- based automatic data collec tion in authentic settings and collecting natural data through the use of digital video technology; © developing computer-generated measurements and unobtrusive measurements; (d) con- ducting nonlinear dynamic modeling, computer simula- tion, and mixed qualitative-quantitative data analysis; and (e) witnessing productive dialogues between longi- tudinal methodologists and longitudinal practitioners. Zheng Yan and Lailei Lou See also Cross-Sectional Research; Measurement Further Readings Jimerson, S., Egeland, B., & Teo, A. (1999). A longitudinal study of achievement trajectories: Factors associated with change. Journal of Educational Psychology , 91 (1), 116–126. Nesselroade, J. R., & Baltes, P. B. (1979). Longitudinal research in the study of behavior and development. New York: Academic Press. Pellegrini, A. D., Kato, K., Blatchford, P., & Baines, E. (2002). A short-term longitudinal study of children’s playground games across the ﬁrst year of school: Implications for social competence and adjustment to Longitudinal Research 619 school. American Educational Research Journal , 39 (4), 991–1015. Schommer, M., Calvert, C., Gariglietti, G., & Bajaj, A. (1997). The development of epistemological beliefs among secondary students: A longitudinal study. Journal of Educational Psychology , 89 (1), 37–40. Singer, J. D., & Willett, J. B. (2003). Applied longitudinal data analysis: Modeling change and event occurrence. New York: Oxford University Press. Willett, J. B., Singer, J. D., & Martin, N. C. (1998). The design and analysis of longitudinal studies of development and psychopathology in context: Statistical models and methodological recommendations. Development and Psychopathology , 10 (2), 395–426. Yan, Z. (2006). Different experiences, different effects: A longitudinal study of learning a computer program in a network environment. Computers in Human Behavior , 22 , 364–380. L ONG -T ERM M EMORY Long-term memory (LTM) refers to people’s vast storehouse of retrievable information other than per- ceptual and short-term memory. It usually remains dormant until activated by a particular stimulus event and is divided into a couple of components: episodic LTM , which contains individuals’ personal histories, their recollections of what, when, and where events have occurred in their past; and s eman- tic LTM , which is individuals’ storehouse of knowl- edge that is not time dependent. Research of episodic LTM focuses on two main categories: for- getting and remembering. Theories of Long-Term Memory An early theory of LTM was the perceptual moment hypothesis. This theory proposed that people encode information in 100-millisecond bundles and store them into memory as an unbroken record, a continu- ous loop—10 snapshots per second, 600 per minute, and more than 500,000 per 16-hour day. This theory did not explain how or where these memories were stored or how they could be retrieved. Presumably most memories remained hidden from people except for unexpected remembrances or purposeful efforts to recall. Dreams, often comprising mindless yet vivid segments, might draw their substance from random samplings from this loop. Subsequent research by the eminent neurologist Wilder Penﬁeld lent credence to this theory. Penﬁeld operated on patients who were afﬂicted with violent epileptic seizures. Removal of damaged regions of the brain often reduced the severity of the seizure. Before surgery, and with the patient fully conscious, Penﬁeld applied a mild electrical current (which produces no pain) to exposed regions of the brain. How the patient responded to the current helped Penﬁeld distinguish damaged tissue from healthy tissue. Many points of stimulation produced utterances and body movements. However, when regions of the temporal lobe were stimulated, vivid memories moving forward in real time were reported, as if this continuous ‘‘memory loop’’ had been engaged at some temporal location. One patient, a stenographer 10 years earlier, stated, ‘‘I could see the desks. I was there, and someone was calling to me, a man leaning on a desk with a pencil in his hand.’’ Another reported, ‘‘I hear music again,’’ and began to hum along, later noting, ‘‘There were instruments. It was as though it were being played by an orchestra. Deﬁnitely it was not as though I were imagining the tune to myself. I actually heard it.’’ Penﬁeld, who operated on more than 1,000 patients, concluded that he had tapped into a ‘‘stream of con- sciousness’’ reﬂecting memories stored many years earlier. However, not all patients reported re-activated memories, and other scientists could not replicate Penﬁeld’s ﬁndings. Other scientists simply were skep- tical of the claims by Penﬁeld, and this line of research largely disappeared. Today, researchers know that some of Penﬁeld’s speculations, provocative as they were, must be incomplete if not wrong. For one, memories cannot be a veridical encoding of an event, like an unbiased camera recording of each day’s activities. Rather, memories often contain embellishments, added at later points in time. Memories can even be created for an event that never occurred at all. In short, people store not only what they have experienced but also signiﬁcant ‘‘add-ons’’ that can alter or distort the orig- inal memory. Second, it seems likely that people ﬁlter their experiences based on what engages their atten- tion and emotions. What escapes their attention is likely not encoded at all and, therefore, is absent from memory. To appreciate the complexities of human memory, it is important to start from a somewhat different but broader perspective. 620 Long-Term Memory