Part II
Pregnancy to Preschool: Early Influences on Cognition and Behavior

As Chapter 2 suggests, one can observe variation in the proportion of students from different ethnic groups assigned to special education and gifted and talented programs without knowing whether there are too many or too few members of any racial/ethnic group in any given category. To answer such a question, one would have to understand the source of the disproportion.

The committee considered three potential explanations, which are not mutually exclusive and which may well operate in tandem:

  1. By the time they reach school age, children differ in the cognitive and behavioral characteristics that are related to placement in special education and gifted and talented programs. These differences may be distributed disproportionately among children in different racial/ethnic groups.

  2. Schools may have an independent influence on the academic success and behavioral problems of students that varies with the racial/ethnic composition of students in the school, or with the race or ethnicity of the individual student.

  3. Standards (or the implementation of standards) for referral and assessment of students for special education and gifted and talented programs may be biased, or they may be applied differentially across racial/ethnic groups to produce disproportion.



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Minority Students in Special and Gifted Education Part II Pregnancy to Preschool: Early Influences on Cognition and Behavior As Chapter 2 suggests, one can observe variation in the proportion of students from different ethnic groups assigned to special education and gifted and talented programs without knowing whether there are too many or too few members of any racial/ethnic group in any given category. To answer such a question, one would have to understand the source of the disproportion. The committee considered three potential explanations, which are not mutually exclusive and which may well operate in tandem: By the time they reach school age, children differ in the cognitive and behavioral characteristics that are related to placement in special education and gifted and talented programs. These differences may be distributed disproportionately among children in different racial/ethnic groups. Schools may have an independent influence on the academic success and behavioral problems of students that varies with the racial/ethnic composition of students in the school, or with the race or ethnicity of the individual student. Standards (or the implementation of standards) for referral and assessment of students for special education and gifted and talented programs may be biased, or they may be applied differentially across racial/ethnic groups to produce disproportion.

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Minority Students in Special and Gifted Education In this part we focus on the first explanation, asking whether characteristics that predict achievement and behavior problems differ across racial/ ethnic groups. To do so, we ask what is known about factors that significantly contribute to variation in cognitive and behavioral function. Because such a review could itself span volumes, we focus in Chapter 3 on factors for which a research base is available to suggest both that the factor is significant in cognitive and behavioral development and that prevalence differs by race or ethnicity. In Chapter 4 we review what is known from a now-extensive research base about early intervention programs and their potential to improve cognitive and behavioral outcomes for children at risk. We focus particularly on the more limited evidence available regarding the impact of early intervention on the placement of children in special education programs once they have entered school. Our early childhood recommendations appear at the end of Chapter 4.

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Minority Students in Special and Gifted Education 3 Influences on Cognitive and Behavioral Development CHANGING PERSPECTIVES ON COGNITIVE AND BEHAVIORAL FUNCTION Research in a variety of biological and social sciences in the past few decades has brought about substantial change in earlier understandings of the contributors to cognitive and behavioral function. In classic works by Galton (1869) and Burt et al. (1934), differences in intelligence were attributed to heredity, emphasizing a perception of the child as constitutionally separate from the environment. In the social sciences, however, a series of landmark studies in the 1930s and 1940s of infants and young children reared in institutions drew attention to the environmental and contextual contributors to child development (Ramey and Sackett, 2000). The research that ensued using animal models (Sackett et al., 1999), the study of children who experienced deprivation in institutional settings, and the proactive early intervention efforts in the 1960s collectively provided compelling evidence that early experience matters a great deal. While genetic and physiological factors continue to play a central role in the understanding of cognitive and behavioral performance, the perception of the child as constitutionally separate from the environment no longer holds. Understanding the development of child behavior increasingly has required a focus on aspects of the environment that serve as moderators of performance (Sameroff, 1993; Ceci et al., 1997). The analytic lenses and

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Minority Students in Special and Gifted Education methods of different social sciences have focused attention on different correlates of achievement and behavior. Economics has focused on the role of family income and the education (or human capital) of parents; sociology looks more at the community, school, and family structure; and psychology focuses on the interactions among family members and other important individuals to understand social, emotional, and cognitive development. In seminal work that launched a line of research in social ecology, Bronfenbrenner (1979) suggested that the development of the child needs to be viewed as influenced by all of these factors. The current scientific task is to catalog and describe the relevant contributions of these dynamic components through time. As the tools of the social sciences have become more powerful, so have those for studying the brain. We have come to understand that biological and environmental factors are not completely separate parts of the picture (Shore, 1997; Wahlsten and Gottlieb, 1997; Bidell and Fischer, 1997; Hunt, 1997). They combine as two pigments in a single paint, together determining a color that neither alone could create. Genetic and health influences themselves are no longer seen as purely biological (National Research Council [NRC], 2000b). Genetic expression is now understood not as a fixed and predetermined influence, but as a probabilistic propensity responsive in some degree to environmental influence (Plomin, 1997; Sameroff, 2000). Researchers can observe in animal studies and, to a more limited extent, in human studies that environmental experiences change the very physiology of the brain: encoding new experiences fosters new brain growth (Greenough and Black, 1992; Black and Greenough, 1986). Contemporary genetics suggests further that the gene-environment dynamic is not one in which each has a distinct but separate role to play, nor that environment determines whether a gene does or does not exert the influence of its predetermined code. Rather, the function of the genetic system is itself context dependent (Bidell and Fischer, 1997). A dramatic instance is the case of a parasitic wasp that lays its eggs in two different hosts, a butterfly or a fly. Offspring that develop in the butterfly host have wings, but those that develop in the fly host do not, despite an identical genetic code (Gottlieb, 1992; Bidell and Fischer, 1997). While a substantial body of research has demonstrated the importance of genetics in explaining variation in cognitive and behavioral performance (Bouchard, 1997; Hunt, 1997), it is clear that genetic variation cannot be understood separately from context. Figure 3-1 presents one schema that explicitly acknowledges the dynamic, reciprocal interplay between biology and experience (Ramey and Ramey, 2000). In this model, cognitive, social, and emotional development is an outgrowth of the transactions between children and the significant others in their environment. But a myriad of factors—biological, social,

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Minority Students in Special and Gifted Education FIGURE 3-1 Schematic portrayal of biosocial developmental contextualism. SOURCE: Ramey and Ramey (1998). Reprinted with permission.

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Minority Students in Special and Gifted Education economic, and cultural—influence the behaviors of both the child and the adults engaged in those interactions. Below we review the current knowledge base regarding early influences on cognition and behavior by looking first at research regarding the biological influences on early development and then the research on environmental (social, emotional, economic) influences. The artificial nature of the dichotomy between biological and environmental influences is perhaps most evident when we discuss the role of poverty under the social and environmental context of development. Each of the biological factors discussed is found to vary with poverty status as well. Increasingly, research suggests that the biological and social worlds must be seen as tightly intertwined if the goal is to understand the cognitive and behavioral outcomes for children and the potential roles for social intervention (McLoyd and Lozoff, 2001; Ramey and Ramey, 1998). Despite the contemporary understanding of their inseparablity, the research enterprises regarding biological and social contributors have for the most part been conducted independently and from different disciplinary research traditions. We therefore look at each piece individually, after which we turn to their interactions. Our focus in this chapter is, of necessity, on early harms and risk factors that impair normal development, as well as interventions that can diminish the impact of those risk factors. Our limited attention to issues regarding accelerated development reflects the research base, and the research base in turn reflects research opportunities (NRC, 2000c). Much of what we have learned about the developing brain, for example, we have learned because an abnormal event (premature birth, trauma, fetal alcohol syndrome) has occurred to call attention to the phenomenon. The group for study is clearly defined, and the contrasting case between the normal and the abnormal circumstance is clear. The group of high achievers is not so easily defined by an event. Moreover, the social policies designed to address the needs of disadvantaged children provide opportunities for research on the effects of physical and environmental risk, and of its amelioration, on development. No similar scaled, sustained research effort has been undertaken to better understand high achievement. Nonetheless, the complex of factors that influence student achievement is likely to do so across the entire distribution. In Figure 3-2, achievement is plotted as a normal distribution, with the “main population” representing a hypothetical circumstance of a general population in which students differ in achievement because they themselves differ and because their environments differ within an average or low-risk range. The diagonal area of the distribution represents a hypothetical group of students who might require additional supports (special education at the lower end, gifted education at the upper end) when teaching targets students at the mean. We focus in this chapter on circumstances that diminish achievement—or shift the location

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Minority Students in Special and Gifted Education FIGURE 3-2 Idealized representation depicting displacement of subgroups with regard to main population on any variable that is normally distributed. SOURCE: Case, Griffin, and Kelly (1999). Reprinted with permission. of the curve back, as in the “subpopulation” for those developing in high-risk environments. This shift simultaneously increases the number of children with special needs at the lower end and decreases the number of high achievers who may be identified as gifted at the upper end. In a sense then, this chapter is about both groups, although those cases at the left tail of the distribution have been studied more because of their distinguishing characteristics than those in the right tail. BIOLOGICAL CONTRIBUTORS TO COGNITION AND BEHAVIOR The importance of the early years of life to development is incontrovertible (Ramey et al., 2000; Ramey and Ramey, 1999; NRC, 2000a). The unparalleled pace of brain growth and the development of fundamental cognitive, emotional, social, and motor processes make the period from conception through infancy one of exceptional opportunity and vulnerability (McLoyd and Lozoff, 2001). While the plasticity of the brain appears to extend well into adolescence, with growth in some areas of the brain as late as the third decade of life (NRC, 2000a), children who experience biological insults and stressors early in life are at greater risk for long-term developmental problems (McLoyd and Lozoff, 2001). Deprivation in the extreme can produce functional mental retardation and aberrant social and emotional behavior in animals born healthy and with good genetic endowment (Ramey and Ramey, 1999). In humans, mild mental retardation with

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Minority Students in Special and Gifted Education TABLE 3-1 Contributors to Early Brain Development Conditions or substances needed for normal brain development: • Oxygen • Adequate protein and energy • Micronutrients, such as iron and zinc • Adequate gestation • Iodine • Thyroid hormone • Folic acid • Essential fatty acids • Sensory stimulation • Activity • Social interaction Conditions and substances that are detrimental or toxic to the developing brain: • Alcohol • Lead • Tobacco • Prenatal infections (e.g., rubella, plasmolysis, cytomegalovirus) • Polychlorinated biphenyls (pcb)s • Ionizing radiation • Cocaine • Metabolic abnormalities (excess phenylalanine, ammonia) • Aluminum • Methylmercury • Chronic illness   SOURCE: NRC (2000). no documented biomedical cause has been observed at elevated levels among very poor families (Garber, 1988). For any individual child, genetic and experiential information come together in a process that organizes the brain to function. An NRC report on the science of early childhood development lists environmental factors that play a significant role in modulating prenatal and early postnatal brain development (see NRC, 2000a:199). The list, although not exhaustive, includes factors selected on the basis of clinical importance, the availability of basic research on brain effects, and/or the existence of relevant clinical studies (Table 3-1). In this report, we focus on a subset of these factors, which research suggests are implicated in differential developmental outcomes for children by race: premature birth (adequate gestation), fetal alcohol and nicotine exposure, and micronutrient deficiency, and exposure to lead. We do not suggest that these factors are uniquely important to healthy development. Other critical factors, such as the role of iodine in cognitive development, are not considered here because in this country they are unlikely to contribute to current developmental differences, since effective prevention measures have eliminated the iodine deficiency problem for children of all races (Stanbury, 1998). Low Birthweight In each year in the past decade, between 7 and 8 percent of babies were born at weights below 2,500 grams. The vast majority of low-birthweight

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Minority Students in Special and Gifted Education children have normal outcomes. As a group, however, low-birthweight babies have higher rates of neurodevelopmental and behavioral problems (Hack et al., 1995; McLoyd and Lozoff, 2001). They are more likely to have lower IQ, cerebral palsy, less emotional maturity and social competence, and attentional difficulties (National Research Council, 2000a). A recent study of siblings found that those born weighing less than 5.5 pounds were almost four times less likely to graduate from high school by age 19 than their normal-birthweight siblings—15.2 percent of low-birthweight siblings, compared with 57.5 percent of normal-birthweight siblings graduated on time (Conley and Bennett, 2000). The neurocognitive differences that are observed with low birthweight are more pronounced the lower the weight (Breslau et al., 1996). Similarly, the child’s general developmental status and intelligence scores decrease with reductions in gestational age (Saigal et al., 1991).1 At the borders of viability (22-24 weeks) where mortality is high, neurological damage to babies who survive is often sustained (Allen et al., 1993). But even lower-risk preterm babies (27-34 weeks) sometimes show cognitive lags compared with their full-term counterparts (de Haan et al., 2000). Damage from premature birth arises in part due to the interruption of the normal process of brain development in utero, including the expected intrauterine stimuli and nutrients important for growth (NRC, 2000a). Recent research suggests that even when preterm infants have benign neonatal courses, they show poorer performance on elicited imitation tasks at 18 months (de Haan et al., 2000). But premature birth also increases the probability that infants will experience pathological events that directly injure the brain. Intracranial hemorrhage, for example, occurs in approximately 20 percent of 28- to 34-week infants and 60 percent of infants born between 24 and 28 weeks. The hemorrhage tends to be more severe at lower gestational ages, resulting in a higher likelihood of a major disability. Even with less severe hemorrhages, however, the risk of minor disabilities— including behavior problems, attention problems, and memory deficits— rises (Lowe and Papile, 1990; Ross et al., 1996; National Research Council 2000a; McLoyd and Lozoff, 2001). In the United States, low birthweight is more common among blacks than any other racial/ethnic group (McLoyd and Lozoff, 2001; David and Collins, 1997; Foster, 1997) (see Table 3-2). Blacks are about twice as likely as whites to be born at low birthweights (see Figure 3-3), even controlling for socioeconomic status (Conley and Bennett, 2000; Foster, 1997). Interestingly, the incidence of low birthweight for babies of African-born 1   While gestational age and birthweight are strongly correlated, babies can be small for gestational age.

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Minority Students in Special and Gifted Education black women more closely resembles that of U.S.-born whites than of U.S.-born blacks (David and Collins, 1997). Among whites there is a strong association between maternal education and low birthweight (National Center for Health Statistics, 1998; Guyer et al., 1997). While this is true of blacks as well, the rate for black mothers who have 16 or more years of education is still above that of whites with less than a high school education. The link between income and the incidence of low birthweight has been well established (McLoyd and Lozoff, 2001; NRC, 2000a; Kiely et al., 1994). This relationship persists even when the mother’s educational attainment, sex, birth order, and race/ethnicity are controlled (Conley and Bennett, 2000). In a recent provocative study, however, income lost its significance when parental birthweight status was controlled. The probability of having a low-birthweight child increased fourfold if the mother herself had low birthweight, and sixfold if the father had low birthweight (Conley and Bennett, 2000). This is a single study, however, and has not been replicated to our knowledge. At the same time that this study questioned the role of income in predicting the incidence of low birthweight, it found that an income-to-needs ratio of the family during the child’s first five years was a significant predictor of the effect of low birthweight on timely high school graduation. The incidence of low birthweight declined in the 1970s and early 1980s but has risen 10 percent since then—from a low of 6.7 in 1984 to 7.6 in 1998. Much of this is due to the increase in the odds of survival for low-birthweight babies due to increases in medical technologies (Seelman and Sweeney, 1995) and to a rise in multiple-birth rates among white women. The rate has declined overall for black mothers but has remained stable (at about 3 percent) for very small babies of 1,500 grams or less (McLoyd and Lozoff, 2001). Several interventions have been shown to reduce the incidence of low birthweight: prenatal care, maternal nutrition and adequate weight gain during pregnancy, control of hypertension, and avoidance of long work hours and excessive physical exertion toward the end of pregnancy (Luke et al., 1995; McLoyd and Lozoff, 2001). Interventions focused on improving outcomes for low-birthweight babies have also demonstrated some effectiveness. These range from changes in the care these infants receive in neonatal intensive care units (Als, 1997; Hernandez-Reif and Field, 2000) to the Infant Health and Development Program, which provided comprehensive services to the infants and their families for several months after discharge (see Box 3-1). Additional stimulation of low-birthweight babies can reduce the cognitive impact, especially for the heavier babies in families with lower socioeconomic status (Hack et al., 1995; Ramey et al., 1992).

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Minority Students in Special and Gifted Education TABLE 3-2 Percentage of Low-Birthweight Births by Detailed Race and Hispanic Origin, 1980-1998   Low Birthweight (less than 2,500 grams, about 5.5 pounds) Very Low Birthweight (less than 1,500 grams, about 3.25 pounds) Race and Hispanic Origin 1980 1985 1990 1995 1998 1980 1985 1990 1995 1998 Total 6.8 6.8 7.0 7.3 7.6 1.15 1.21 1.27 1.35 1.45 White, non-Hispanic 5.7 5.6 5.6 6.2 6.6 .86 .90 .93 1.04 1.15 Black, non-Hispanic 12.7 12.6 13.3 13.2 13.2 2.46 2.66 2.93 2.98 3.11 Hispanica 6.1 6.2 6.1 6.3 6.4 .98 1.01 1.03 1.11 1.15 Mexican American 5.6 5.8 5.5 5.8 6.0 .92 .97 .92 1.01 1.02 Puerto Rican 9.0 8.7 9.0 9.4 9.7 1.29 1.30 1.62 1.79 1.86 Cuban 5.6 6.0 5.7 6.5 6.5 1.02 1.18 1.20 1.19 1.33 Central and South American 5.8 5.7 5.8 6.2 6.5 .99 1.01 1.05 1.13 1.23 Other and unknown Hispanic 7.0 6.8 6.9 7.5 7.6 1.01 .96 1.09 1.28 1.38 Asian/Pacific Islander 6.7 6.2 6.5 6.9 7.4 .92 .85 .87 .91 1.10 Chinese 5.2 5.0 4.7 5.3 5.3 .66 .57 .51 .67 .75 Japanese 6.6 6.2 6.2 7.3 7.5 .94 .84 .73 .87 .84 Filipino 7.4 6.9 7.3 7.8 8.2 .99 .86 1.05 1.13 1.35 Hawaiian and part Hawaiian 7.2 6.5 7.2 6.8 7.2 1.05 1.03 .97 .94 1.53 Other Asian/Pacific Islander 6.8 6.2 6.6 7.1 7.8 .96 .91 .92 .91 1.12 American Indian/Alaska Native 6.4 5.9 6.1 6.6 6.8 .92 1.01 1.01 1.10 1.24 NOTES: Excludes live births with unknown birthweight. Low-birthweight infants weigh less than 2,500 grams at birth, about 5.5 pounds. Very-low-birthweight infants weigh less than 1,500 grams, about 3.25 pounds. Trend data for births to Hispanics and non-Hispanic whites and blacks are affected by expansion of the reporting area in which an item on Hispanic origin is included on the birth certificate as well as by immigration. These two factors affect the numbers of events, the composition of the Hispanic population, and maternal and infant health characteristics. The number of states in the reporting area increased from 22 in 1980 to 23 and the District of Columbia (DC) in 1983-1987, 30 and DC in 1988, 47 and DC in 1989, 48 and DC in 1990, 49 and DC in 1991-1992, and all 50 states and DC from 1993 forward. Trend data for births to Asian/Pacific Islander and Hispanic women are also affected by immigration. SOURCE: Ventura, Martin, Curtin, Mathews and Park (2000). aPersons of Hispanic origin may be of any race.

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Minority Students in Special and Gifted Education Intelligence verbal intelligence score) and mental health outcomes (measured by the Rochester Adaptive Behavior Inventory). The risk factors considered were maternal mental illness; high maternal anxiety; rigidity in the attitudes, beliefs, and values of mothers regarding the child’s development; few positive maternal interactions with the child during infancy; less maternal education than high school; head of household in an unskilled occupation; disadvantaged minority status; single parenthood; stressful life events; and large family size. While each variable had a statistically significant negative impact by itself, no single variable was able to predict much of the variation. The total number of risk factors, however, was a powerful predictor. On the intelligence test, children with no environmental risks scored more than 30 points higher than children with eight or nine risk factors. No preschoolers in the zero-risk category had an IQ below 85, but 26 percent of those in the high-risk group did. And 4-year-olds with five or more risk factors were 12.3 times as likely to have clinical mental health symptoms as those with fewer risks (Sameroff, 2000). Child development theory in recent years has incorporated the notion that children not only react to their environment, but also help create it as their behavior elicits responses from those around them (NRC, 2000c, 2001b). In an effort to determine the role played by the characteristics a child brings—including temperament, perinatal physical condition, interactive behaviors, and competence in motor behaviors and regulatory abilities—children were assessed during the first 12 months on a variety of development and behavior scales.6 The children were assessed again at age 4 on both social-emotional competence (mental health) and on IQ. Infant competence scores were rendered insignificant compared with environmental risk. “High competent infants in high risk environments did worse as 4-year-olds than low competent infants in low risk environments . . . individual characteristics were not able to overcome the effects of environmental adversity. If one wants to predict the developmental course for infants, attention to the accumulation of environmental risk factors would be the best strategy” (Sameroff, 2000:26-27) (see Figure 3-14). Effects of SES on School Readiness Data from the National Center for Education Statistics on children entering kindergarten demonstrate how striking are the accumulated differences in knowledge and skill development across SES groups by the time 6   These included scores from the infant’s perinatal physical condition from the Research Obstetrical Scale (Sameroff et al., 1982), the Brazelton Neonatal Behavioral Assessment Scales (Brazelton, 1973), and the Bayley Scales of Infant Development (Sameroff, 2000).

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Minority Students in Special and Gifted Education children reach the schoolhouse door. The survey collects data on emergent literacy and numeracy skills and content knowledge. It also collects teacher and parent ratings on children’s social skills (National Center for Education Statistics, 2000). Table 3-7 displays differences by family and child characteristics in the skills that have been established to be prerequisites to learning to read: knowing that print reads left to right, knowing where to go when a line of print ends, and knowing where a story ends. Without a regression analysis, the independent effects of poverty, race, maternal education, marital status, and a primary language other than English cannot be disentangled. The simple correlations, however, are pronounced for each characteristic. At the extremes, 47 percent of white children with a mother who graduated from high school had all three skills, while only 11 percent of black children with mothers who did not graduate from high school had all three. The same pattern can be found for prereading skill level in letter recognition, beginning and ending sound identification, and identifying words by sight or in context and for early mathematics skills, including number and shape recognition, relative size comparison, ordinal sequencing, the ability to add, subtract, multiply, or divide small numbers. Finally, social and emotional skills differ by SES as well. While these skills are of value in and of themselves, for the purposes of this report their relationship to later academic achievement and behavior is noteworthy (Swartz and Walker, 1984). While the Early Childhood Longitudinal Study collects data on a variety of measures, we focus here on self-regulatory and motivation characteristics and problem behaviors as rated by the teacher. Teacher ratings may incorporate bias (discussed in Chapter 5), but these are the ratings that are likely to influence special education placement. Teachers see differences between boys and girls in the ability to attend, with only 58 percent of boys rated as being able to attend often, compared with 74 percent of girls. They also rate white and Asian children as better able to attend and as more persistent than black and Hispanic children. Children’s ratings on all attributes rise with parents’ education levels, and children in two-parent families are rated higher on average than those in one-parent families (see Table 3-8). With respect to problem behaviors, the number of children who argue or fight with others is relatively small; most children can get along in the classroom. However, the differences by race are substantial, with Asians rated as exhibiting few problem behaviors and black children exhibiting the highest rate (see Table 3-9). Hispanic and white children receive similar ratings.

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Minority Students in Special and Gifted Education FIGURE 3-14 Relation of infant competence to competence and IQ scores at 4 years of age, controlling for early multiple environmental risk scores. SOURCE: Sameroff (2000). Reprinted with permission of John Wiley & Sons. Implications of School Readiness Differences The early disparities in school readiness are of marked significance because they portend future achievement gaps. While gaps in the particular skills of letter and number identification close during the kindergarten year,

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Minority Students in Special and Gifted Education TABLE 3-7 Percentage Distribution of First-Time Kindergartners by Print Familiarity Scores, by Child and Family Characteristics: Fall 1998 Characteristic 0 Skills 1 Skill 2 Skills 3 Skills Total 18 21 24 37 Child’s sex Male 20 20 23 37 Female 17 21 25 38 Child’s race/ethnicity White, non-Hispanic 14 18 24 45 Black, non-Hispanic 29 26 24 21 Asian 15 19 22 43 Hispanic 24 23 26 27 Hawaiian Native/Pacific Islander 30 27 19 23 American Indian/Alaska Native 38 27 18 17 More than one race, non-Hispanic 18 23 24 35 Child’s race/ethnicity by maternal education Maternal education: High school diploma/equivalent or more White, non-Hispanic 12 17 24 47 Black, non-Hispanic 27 25 25 23 Asian 14 17 22 46 Hispanic 22 22 25 31 Maternal education: Less than high school diploma or equivalent White, non-Hispanic 26 26 25 22 Black, non-Hispanic 40 30 20 11 Asian 22 36 23 19 Hispanic 32 26 27 15 Welfare receipt Utilized welfare 32 27 22 19 Never utilized welfare 17 19 24 40 Primary language spoken in home Non-English 26 22 24 28 English 18 20 24 38 NOTES: Estimates based on first-time kindergartners who were assessed in English (approximately 19 percent of Asian children and approximately 30 percent of Hispanic children were not assessed). Percentages may not sum to 100 due to rounding. SOURCE: U.S. Department of Education, National Center for Education Statistics, Early Childhood Longitudinal Study, Kindergarten Class of 1998-99, Fall 1998. children who enter kindergarten with those skills already in place have made strides in other areas that take them beyond early skill development. Figure 3-15 shows the gains in reading scores over the course of the kindergarten year by maternal education level. While all children gained significantly over the course of the year, the gap did not narrow, even though

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Minority Students in Special and Gifted Education TABLE 3-8 Percentage Distribution of First-Time Kindergartners by the Frequency with Which Teachers Say They Persist at a Task, Are Eager to Learn New Things, and Pay Attention Well, by Child and Family Characteristics: Fall 1998   Persist Characteristic Never/Sometimes Often/Very Often Total 29 71 Child’s sex Male 35 65 Female 22 78 Child’s race/ethnicity White, non-Hispanic 25 75 Black, non-Hispanic 38 62 Asian 19 81 Hispanic 33 67 Hawaiian Native/Pacific Islander 36 64 American Indian/Alaska Native 36 64 More than one race, non-Hispanic 27 73 Child’s race/ethnicity by maternal education Maternal education: High school diploma/equivalent or more White, non-Hispanic 23 77 Black, non-Hispanic 36 64 Asian 18 82 Hispanic 31 69 Maternal education: Less than high school diploma or equivalent White, non-Hispanic 39 61 Black, non-Hispanic 50 50 Asian 18 82 Hispanic 35 65 Welfare receipt Utilized welfare 41 59 Never utilized welfare 27 73 Primary language spoken in home Non-English 31 69 English 28 72 NOTE: Estimates based on first-time kindergartners. Percentages may not sum to 100 due to rounding. SOURCE: U.S. Department of Education, National Center for Education Statistics, Early Childhood Longitudinal Study, Kindergarten Class of 1998-99, Fall 1998.

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Minority Students in Special and Gifted Education Eager to Learn Attention Never/Sometimes Often/Very Often Never/Sometimes Often/Very Often 25 75 34 66 29 71 42 58 22 78 26 74 22 78 30 70 34 66 45 55 20 80 29 71 30 70 38 62 32 68 41 59 28 72 48 52 28 72 33 67 20 80 28 72 31 69 42 58 18 82 28 72 27 73 36 64 35 65 44 56 47 53 58 42 23 77 32 68 36 64 41 59 38 62 47 53 24 76 32 68 32 68 37 63 25 75 34 66

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Minority Students in Special and Gifted Education TABLE 3-9 Percentage Distribution of First-Time Kindergartners by the Frequency with Which Teachers Say They Exhibit Antisocial Behavior, by Child and Family Characteristics: Fall 1998   Argue with Others Characteristic Never/Sometimes Often/Very Often Total 89 11 Child’s sex Male 87 13 Female 92 8 Child’s race/ethnicity White, non-Hispanic 90 10 Black, non-Hispanic 83 17 Asian 94 6 Hispanic 90 10 Hawaiian Native/Pacific Islander 86 14 American Indian/Alaska Native 86 14 More than one race, non-Hispanic 90 10 Child’s race/ethnicity by maternal education Maternal education: High school diploma/equivalent or more White, non-Hispanic 91 9 Black, non-Hispanic 84 16 Asian 94 6 Hispanic 90 10 Maternal education: Less than high school diploma or equivalent White, non-Hispanic 87 13 Black, non-Hispanic 80 20 Asian 97 3 Hispanic 89 11 Welfare receipt Utilized welfare 84 16 Never utilized welfare 90 10 Primary language spoken in home Non-English 91 9 English 89 11 NOTE: Estimates based on first-time kindergartners. Percentages may not sum to 100 due to rounding. SOURCE: U.S. Department of Education, National Center for Education Statistics, Early Childhood Longitudinal Study, Kindergarten Class of 1998-99, Fall 1998.

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Minority Students in Special and Gifted Education Fight with Others Easily Get Angry Never/Sometimes Often/Very Often Never/Sometimes Often/Very Often 90 10 89 11 89 11 86 14 92 8 91 9 92 8 90 10 86 14 85 15 93 7 91 9 89 11 88 12 89 11 88 12 85 15 87 13 90 10 88 12 92 8 90 10 87 13 85 15 92 8 90 10 90 10 89 11 88 12 87 13 83 17 85 15 97 3 95 5 86 14 86 14 85 15 85 15 91 9 89 11 89 11 88 12 90 10 89 11

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Minority Students in Special and Gifted Education FIGURE 3-15 First-time kindergartners’ reading mean scale scores, by mother’s education: Fall 1998 and Spring 1999. SOURCE: U.S. Department of Education, National Center for Education Statistics, Early Childhood Longitudinal Study, Kindergarten Class of 1998-1999. almost all children had acquired letter recognition and print awareness skills (West et al., 2001). As children move through the school years, those who read well read more (Stanovich, 1986) and therefore acquire a larger knowledge base. A similar pattern occurs in mathematics: children from low-SES groups acquire the same knowledge as those from higher-SES groups, but they acquire it later (West et al., 2001). Griffin et al. (1994) found that low-income 5- to 6-year-olds performed like middle-income 3- to 4-year-olds on a test of early math skills. The implications of the lag apply not only to special education, but also to gifted education. At the upper end of the achievement distribution in the literacy domain are children who can recognize words by sight or can add and subtract in the spring of the kindergarten year. Figures 3-16 and 3-17 plot the percentage of such children by the number of risk characteristics present, including less maternal education than high school, family receiving welfare or food stamps, single-parent household, and primary language other than English. While about 1 in 5 children in families with none of those risk factors has mastered these skills, the representation of children with two or more risk factors in that category is very low. Disparities in school readiness are also manifested in the development of peer and student-teacher relationships. We know from research on the development of behavior and emotional problems that young children who already exhibit aggressive, disruptive behaviors when they enter school are

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Minority Students in Special and Gifted Education FIGURE 3-16 Percentage of first-time kindergartners recognizing the words by sight, by number of risk factors: Fall 1998 and Spring 1999. SOURCE: U.S. Department of Education, National Center for Education Statistics, Early Childhood Longitudinal Study, Kindergarten Class of 1998-1999. often not equipped with the necessary skills to develop healthy peer and adult relationships later on (Goldstein et al., 1980; Patterson, 1986; Patterson et al., 1992; Walker et al., 1987). We also know that aggressive and violent boys differ from less aggressive boys on measures of interpersonal problem solving, with the scores of aggressive and violent boys dem- FIGURE 3-17 Percentage of first-time kindergartners adding and subtracting, by number of risk factors: Fall 1998 and Spring 1999. SOURCE: U.S. Department of Education, National Center for Education Statistics, Early Childhood Longitudinal Study, Kindergarten Class of 1998-1999.

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Minority Students in Special and Gifted Education onstrating significantly poorer skills (Lochman and Dodge, 1994). This inability to appropriately solve problems, coupled with the use of coercive behaviors, makes it extremely difficult for antisocial students to attend, concentrate, and learn the basic academic skills necessary to function in school. These learning skill deficits, which often develop before school entry, cause students to have trouble moving successfully through the curriculum, because they usually need additional time and assistance to help them achieve mastery (Fuchs et al., 1993; Walker et al., 1995; Gleason et al., 1991). The weight of the evidence reviewed above suggests that in order to have an education system in which non-Asian minority students (and disadvantaged students more generally) are not represented in disproportionately high numbers among those at the low end of the achievement distribution and in disproportionately low numbers at the high end of that distribution, efforts to support the cognitive, social, and emotional development of those children in the years before they arrive at kindergarten are critical. This is not to say that early experience sets a child on an unalterable course. We know, for example, that some schools do far better than others at promoting achievement among high-risk children (discussed in Chapter 5 ). Yet when children are exposed to many risk factors early on, promoting school success will be a much more difficult task for both the child and the school.