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Eager to Learn: Educating our Preschoolers
3
The Importance of Individual and Cultural Variations
WHILE DEVELOPMENT OCCURS IN A similar fashion for all children, developmental differences are the inevitable result of individual genetic and experiential variations and differing cultural and social contexts. In the past several decades, social scientists who study children have paid greater attention to this diversity in development. The potential of human development interacts with diversity among individuals, available resources, and the goals and preferred interaction patterns of communities in a way that links the biological and the social in the construction of diverse developmental pathways.
Among the many differences with which children present themselves to preschool teachers, we highlight three dimensions of variation that require particular attention on the part of a responsive preschool teacher:
The child’s level of development in the cognitive skills and knowledge of relevance to the preschool classroom,
The child’s social skills and behavior in a classroom context and the familiar norms of interaction with peers and adults, and
The child’s level of physical and motor development.
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These differences are associated with functional characteristics—such as temperament, learning style, and motivation—and from status characteristics—including gender, race, ethnicity, and social class (Gordon and Shipman, 1979).
VARIATION IN COGNITIVE SKILLS AND KNOWLEDGE
Children come to preschool with a set of cognitive skills and proficiencies that include language and literacy, reasoning, and general knowledge (Kagan et al., 1995). Although virtually all preschool children by age 3 or so have mastered the basic grammar and phonology and a reasonably large vocabulary for everyday learning and play, there are nevertheless large individual differences in areas that are related to achievement in formal learning settings. They vary widely in their language acquisition and use, their language comprehension, their understanding of number and causation, and their knowledge about the world around them. We review findings in the area of language and literacy, where much research has been done, and in mathematics, where a smaller but growing body of research is available.
Language Development
A major source of variation among children is their rate of language development, a difference that begins in the early months of life. Roe (1974) found that, among 28 infants, the earlier a high rate of babbling occurred, the earlier every subsequent index of language maturity was likely to occur. Some researchers have found a pattern of gender difference in language learning, with girls more advanced in vocabulary learning than boys (Huttenlocher et al., 1991).
Although research has shown the developmental sequence of language learning to be much the same for all children, great variation in the rate of language learning occurs across as well as within languages. Each language has its own areas of complexity and irregularity, leading to slow acquisition, and its own areas of relative ease. Slobin (1985) tested children ages 2 to 4 who were learning one of four languages: English, Italian, Serbo-Croatian,
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or Turkish. Before age 2, the children learning Turkish were using productively the 16 case inflections required on nouns plus much of the verb morphology, whereas the “absence of a regular and predictable system contributes to the prolonged and confused course of inflectional acquisition in English” (Slobin, 1985:151). In Turkish, inflectional morphemes are stressed, obligatory, regular, and distinct. Children do not have to deal with homonyms, as in “She ate eight cookies,” with irregularities such as “cows, mice, sheep,” with contrasts such as “ring/rang, bring/brought,” or “eat/ate, beat/beat, treat/treated,” or with acceptable options such as “None of these go/goes.” Regardless of the sentence structure heard, the objective case ending enabled the children learning Turkish to identify the receiver of an action correctly 80 percent of the time. The children learning English, who had to rely on sentence structure (as in “The ball hit the boy” versus “The ball hit by the boy”), were 3 1/2 years old before reaching that level of accuracy.
Among children learning English, the range in age at particular stages and in the amount and kinds of language they acquire is very wide. Among the 42 children Hart and Risley (1999) observed longitudinally, the average age of saying the first word was 11 months; the range, however, was 8 to 14 months. The average age at which half of what the children said contained recognizable words was 19 months, with a range of 15 to 30 months. At age 2, the variation was enormous: children produced an average of 338 comprehensible utterances an hour, with a range from 42 to 672; they used 134 different words per hour on average, with a range from 18 to 286. The range in vocabulary size parents reported for their 2-year-olds was 50 to 550 words in another study of several hundred children (Fenson et al., 1994).
The range of language abilities confronting preschool teachers is wider the younger the children in the classroom. Significantly delayed language occurs in a relatively large number of 2-year-olds, with a progressively smaller proportion of children affected across the preschool years (Whitehurst and Fischel, 1994). For example, in one study, between 9 and 17 percent of 2-year-olds (varying with socioeconomic status) met a criterion for expressive delay of fewer than 30 words and no word combinations at 24 months (Rescorla, 1989). By 36 months, estimated preva
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lence of specific and secondary delay dropped to between 3 and 8 percent (Silva, 1980; Stevenson and Richman, 1976). The longitudinal study by Silva (1980) indicates that the prevalence of secondary and specific forms of developmental language delay dropped by another 60 percent between ages 3 and 5. This would indicate a prevalence of between 1 and 3 percent at age 5.
Approaches to Language Learning
Children differ in how they approach the task of learning language. Bates et al., (1988) describe a continuum ranging from children who approach language holistically, acquiring whole sentences in chunks (“Leave me alone,” “I want some more”), to children who take an analytical approach, learning one word at a time. Children who approach language analytically are described as having a referential bias (Nelson, 1973); they acquire large initial vocabularies of object labels (or of verbs if they are learning Korean or Chinese, languages in which verbs occur in salient positions at the beginnings and ends of sentences, where nouns occur in English (see Choi and Bowerman, 1991; Tardiff, 1996). Children with a holistic approach are described as less interested in objects than in social interaction, such that they acquire larger initial vocabularies of expressions and action words (Nelson, 1973).
Children also differ in the extent to which they are risk-takers (Peters, 1983). Some children appear to prefer to listen: there may be a prolonged “silent period” followed by starting to talk at a skill level comparable to that of children who have been practicing speaking for months (Saville-Troike, 1988). Other children begin exploring the effects of words heedless of accuracy and inflection. Nelson (1973) found talkativeness positively associated with all aspects of learning to talk when children were 2 years old. Talkativeness has been found positively associated with larger expressive vocabularies and faster vocabulary growth rates at age 3 (Hart and Risley, 1999), and with use of more sophisticated syntax at age 4 and 5 (Landon and Sommers, 1979). Talkativeness is important, because the language children display influences communicative interactions with caregivers (Hart and Risley, 1999; Oller et al., 1995).
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Sources of Language Differences
Culture. Children learn language in the process of becoming members of a culture (Schieffelin and Ochs, 1986; Tomasello, 1992), and cultural practices are likely to be the chief determinant both of the amount and kinds of language children learn and of the environmental support provided for language learning (Schieffelin and Ochs, 1983). American families differ greatly in how much talking customarily goes on (Hart and Risley, 1995), and cultures differ in how much talking is acceptable on the part of little children (Schieffelin and Eisenberg, 1984). Heath (1989) and Schieffelin and Eisenberg (1984) describe cultures in which children are expected to learn from listening to the adult conversations going on around them, speaking only when asked to do so, so that the children’s contributions will be relevant, well formed, and both sharing the conversational topic and contributing new information.
There is ample evidence that cultural influences in terms of language affect children’s thinking, problem solving, and interpersonal interactions. For example, studies have shown that Japanese children excel in mathematics compared with U.S. children. One of the reasons for this may reside in the transparent nature of the base 10 counting system in the Japanese language. Similar differences might be found in classification because of different criteria and labels available. For example, Navaho-speaking children have more difficulty than English-speaking children classifying by color, but excel in classifying by shape, reflecting the presence of shape-dependent morphemes in their language.
Ochs (1986) notes the increasing number of cross-cultural studies showing that societies differ in language-socializing procedures, resulting in variation in language development associated with cultural context. “Prompting a child what to say appears widespread, but procedures described as facilitating language acquisition in studies of interactions between American middle-class parents and their children—fine-tuning, simplified, stressed speech, asking leading questions, expanding children’s utterances—are not characteristic in non-Western cultures” (Ochs, 1986:6). Studies by Pye (1986) and Schieffelin and Ochs (1983)
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also suggest that the environmental support provided by American middle-class parents reflects the demands of a technological society in which a cultural priority is preparing children for academic achievement and managerial and professional occupations (Hart and Risley, 1995).
However, Fernald and Morikawa (1993) compared the interactions of 30 middle-class American parents to those of 30 monolingual wives of affiliates of Japanese companies visiting in America. All the parents, given identical sets of toys and video-taped in 10 to 15 minutes of toy play during home visits, were found to fine-tune their speech to the skill levels of their children. The American parents talked with their 6-, 12-, and 19-month-old children primarily about objects (naming them), and the Japanese parents talked primarily about social relations (polite verbal routines accompanying the exchange of objects, encouraging positive actions on toys: “pat it gently”). The major influence on the language children learn is the culture’s socialization practices, which aim to establish and maintain the “language learning games” of the culture (Tomasello, 1992).
Socioeconomic Status. A significant association between children’s performance on cognitive tasks and parent income and years of education is well documented (see Gottfried, 1984; Neisser et al., 1996; Stipek and Ryan, 1997), both within and across cultural groups. Parents with the advantages of education are reported to interact with their infants in ways relevant to mainstream schooling. They prompt their infants to respond to books and pictures, ask questions that promote organizing knowledge into names and categories (Schieffelin and Ochs, 1983), and arrange for children to have materials, uninterrupted time, and adult support for exploratory play that challenges them to initiate actions and combine and modify them in order to achieve a goal (Bruner, 1974). Duncan et al. (1994) demonstrated that the effect of poverty is partially mediated by the home environment. One-third of the variance in age 5 IQ scores that was associated with income was eliminated when measures of the home learning environment, family social support, maternal depression, and active behavioral coping were included in the model. The extent to which poverty is related to quality of the home environment depends on the de-
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gree of poverty: Garrett et al. (1994) found that as the income-to-needs ratio increased, the quality of the home environment increased. Moreover, the severity of the impact of socioeconomic status (SES) on the child’s development appears to be highly responsive to the number of risk factors that characterize the home environment; poverty alone would predict an impact far smaller than poverty in the context of a single-parent home with low parental education and maternal depression (Sameroff, 1989).
Implications
The preschool period is a time when the environment in which children develop can contribute to large differences in language and literacy skills. Before children can actually read, they generally acquire some sense of the purposes and mechanics of the reading enterprise. For some children, opportunities to learn about reading are many, and for others, they are few (McCormick and Mason, 1986). Those who can identify letters and are familiar with the concept and purpose of print are considered “reading ready” (National Research Council, 1998). Reading readiness at school entry is highly correlated with reading ability in the primary grades (Hammill and McNutt, 1980; Scarborough, 1998).
The National Center for Education Statistics recently published the results of a survey of America’s kindergarten class of 1998–99 (National Center for Education Statistics, 2000). The survey recorded the number of first-time-to-kindergarten children with literacy skills that are 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 the story ends. The results: 37 percent of first-time kindergartners could do all three of these skills, but 18 percent could do none of the three (Table 3–1). As they enter kindergarten, 66 percent of children recognize their letters, 29 percent recognize beginning sounds in words, and 17 percent recognize ending sounds (Table 3–2).
Several factors, including gender and age, affect test results. Girls perform better than boys in the test, and the age of the student at first entry matters. The latter variable in particular suggests that normal developmental processes are at work in the development of literacy skills. But environmental factors are clearly
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TABLE 3–1 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 Age at Entry
Born Jan.-Aug. 1992
11
17
22
50
Born Sep.-Dec. 1992
13
18
24
45
Born Jan.-Apr. 1993
17
20
24
38
Born May-Aug. 1993
22
22
24
32
Born Sep.-Dec. 1993
27
25
22
26
Mother’s Education
Less than high school
32
28
24
17
High school diploma or equivalent
23
23
24
30
Some college, including vocational/technical
17
20
24
39
Bachelor’s degree or higher
8
14
23
56
Family Type
Single mother
26
24
24
25
Single father
22
25
24
29
Two parent
16
19
24
41
Welfare Receipt
Utilized AFDC
32
27
22
19
Never utilized AFDC
17
19
24
40
Primary Language Spoken in Home
Non-English
26
22
24
28
English
18
20
24
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
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Characteristic
0 Skills
1 Skill
2 Skills
3 Skills
Child’s Race/Ethnicity by 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
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
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: National Center for Education Statistics (2000: Table 5).
relevant as well: when the survey data are arrayed according to family characteristics, maternal education, poverty (as measured by welfare receipt), family type, and race/ethnicity are all shown to be correlated with literacy skills.
Through what mechanisms do demographic characteristics operate? Research and survey data suggest that families from lower-SES groups provide a similar array of language experiences as families in higher-SES groups, but the quantity of verbal interaction, and thus the vocabulary of the child, is much more limited (Hart and Risley, 1995). Moreover, language-rich environments are typically associated with activities like book reading, which by itself has a relatively modest predictive value (National Research Council, 1998). The NCES data indicate that mother’s education level is positively correlated with the number of books and music recordings in the home, that single-parent families and those receiving welfare have fewer books and recordings, and that these parents read and tell stories less often to their children (Tables 3–3 and 3–4). The relationship is not as strong for song singing or arts and crafts projects, however (Table 3–5).
As we indicated in the previous chapter, recent theories have
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TABLE 3–2 Percentage of First-Time Kindergartners Passing Each Reading Proficiency Level, by Child and Family Characteristics: Fall 1998
Characteristic
Letter Recognition
Beginning Sounds
Ending Sounds
Sight Words
Words in Context
Total
66
29
17
2
1
Child’s Sex
Male
62
26
15
3
1
Female
70
32
19
2
1
Child’s Age at Entry
Born Jan.-Aug. 1992
76
38
24
5
2
Born Sep.-Dec. 1992
73
36
22
4
2
Born Jan.-Apr. 1993
67
31
17
2
1
Born May-Aug. 1993
60
23
13
1
1
Born Sep.-Dec. 1993
56
20
11
1
1
Mother’s Education
Less than high school
38
9
4
*
*
High school diploma or equivalent
57
20
11
1
*
Some college, including vocational/technical
69
30
17
2
1
Bachelor’s degree or higher
86
50
32
6
2
Family Type
Single mother
53
18
10
1
*
Single father
58
21
11
2
1
Two parent
70
33
19
3
1
Welfare Receipt
Utilized AFDC
41
11
5
1
*
Never utilized AFDC
69
31
18
4
1
Primary Language Spoken in Home
Non-English
49
20
12
3
2
English
67
30
17
2
1
Child’s race/ethnicity
White, non-Hispanic
73
34
20
3
1
Black, non-Hispanic
55
19
10
1
*
Asian
79
43
29
9
5
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Characteristic
Letter Recognition
Beginning Sounds
Ending Sounds
Sight Words
Words in Context
Hispanic
49
19
10
1
1
Hawaiian Native/ Pacific Islander
55
24
14
2
1
American Indian/ Alaska Native
34
11
6
*
*
More than one race, non-Hispanic
61
27
16
4
2
Child’s Race/Ethnicity by Maternal Education
High school diploma/equivalent or more
White, non-Hispanic
75
36
21
3
1
Black, non-Hispanic
59
22
12
1
1
Asian
82
47
32
10
5
Hispanic
55
23
13
1
1
Less than high school diploma or equivalent
White, non-Hispanic
47
12
6
*
*
Black, non-Hispanic
37
7
3
*
*
Asian
60
20
9
1
1
Hispanic
29
6
3
*
*
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.
*less than 0.5 percent.
SOURCE: National Center for Education Statistics (2000: Table 6).
emphasized the influence of relationships and interactions with caregivers other than parents on children’s development. Research on children during the school years that measures SES as a group risk factor (measured at the school level) suggests that it has a large, significant impact on reading ability, mediating the effect of SES as an individual risk factor (Bryk and Raudenbush, 1992). Children who come from low-SES families but are in schools with students from higher-SES families are at less risk than those in low-SES schools. A plausible interpretation of these data is that schools with large populations of low-SES students are more likely to be substandard schools (National Research
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Children who were less involved in performing tasks during mother-child interaction performed less well individually at the follow-up.
Early childhood education is, among other things, a process of gradual transition from cultural and family patterns to the expectations of a new social context. It is critical that the child’s background and experience be understood and respected, that the school be responsive to the child, and that the child be introduced to school culture and practices step by step.
VARIATIONS IN PHYSICAL AND MOTOR DEVELOPMENT
Children vary substantially in many aspects of their physical development. Here we focus on those aspects that are most directly related to early childhood pedagogy: fine motor skills, gross motor skills, and disabling conditions.
Fine motor skills influence success in many of the activities in a preschool program. Lack of fine motor skills can make it difficult to hold a pencil, limiting early efforts at printing letters and drawing. Fine motor skills also influence eye movement and can predict reading, mathematics, and general school achievement (Tramontana et al., 1988).
The NCES survey of children as they enter kindergarten measured fine motor skills (with ECLS-K direct measures) involved in constructing forms with wooden blocks, copying simple figures, and drawing a person. It also assessed gross motor skills, exemplified by balancing and hopping on each foot, skipping, and walking backward on a line. The scores for gross and fine motor skills were divided into approximate thirds, referred to as lower, middle, and higher. The middle group includes those children performing at age-expected level, and the lower group at one or more standard deviations below the average.
The results suggest that girls score somewhat higher than boys on both fine and gross motor skills, but age at entry makes a far bigger difference. These findings are consistent with those obtained from the standardization of the Early Screening Inventory—Revised, from which the NCES direct motor measures were derived (Meisels et al., 1993, 1997). Mother’s education is highly correlated with fine motor skills: 42 percent of children in fami-
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lies in which the mother had less than a high school education were rated as having low fine motor skills, and 22 percent were rated as high. In families in which the mother was a college graduate, 18 percent scored low on the fine motor scale, and 46 percent scored high (Table 3–13). There is also substantial variation by race/ethnic category for both fine and gross motor skills. In the fine motor skills tests, Asian children scored highest (49 percent in the high category) and black children scored lowest (41 percent in the low category). For gross motor skills, black children scored highest, with 46 percent in the higher portion of the distribution, followed by 38 percent of Asian children and 37 percent of white and Hispanic children (Table 3–14).
TABLE 3–13 First-Time Kindergartners’ Mean Fine Motor Skills Score and Percentage Distribution of Scores, by Child and Family Characteristics: Fall 1998
Score Distribution (percent)
Characteristic
Mean Score
Lower
Middle
Higher
Total
6
29
36
35
Child’s Sex
Male
6
31
37
33
Female
6
26
36
38
Child’s Age at Entry
Born Jan.-Aug. 1992
6
20
36
44
Born Sep.-Dec. 1992
6
20
36
44
Born Jan.-Apr. 1993
6
25
37
38
Born May-Aug. 1993
5
34
37
29
Born Sep.-Dec. 1993
5
45
33
22
Mother’s Education
Less than high school
5
42
35
22
High school diploma or equivalent
5
33
36
31
Some college, including vocational/technical
6
25
37
39
Bachelor’s degree or higher
6
18
36
46
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Score Distribution (percent)
Characteristic
Mean Score
Lower
Middle
Higher
Family Type
Single mother
5
37
35
28
Single father
6
31
41
28
Two parent
6
26
37
37
Welfare Receipt
Utilized AFDC
5
44
33
23
Never utilized AFDC
6
26
37
37
Primary Language Spoken in Home
Non-English
6
31
35
34
English
6
28
36
36
Child’s Race/Ethnicity
White, non-Hispanic
6
24
37
39
Black, non-Hispanic
5
41
33
26
Asian
7
15
36
49
Hispanic
6
31
36
33
Hawaiian Native/Pacific Islander
6
27
32
41
American Indian/Alaska Native
6
31
39
30
More than one race, non-Hispanic
6
28
41
31
Child’s Race/Ethnicity by Maternal Education
High school diploma/equivalent or more
White, non-Hispanic
6
23
37
40
Black, non-Hispanic
5
39
33
28
Asian
7
14
36
50
Hispanic
6
27
35
38
Less than high school diploma or equivalent
White, non-Hispanic
5
44
34
22
Black, non-Hispanic
4
51
34
16
Asian
6
18
33
49
Hispanic
5
39
37
24
NOTE: Estimates based on first-time kindergartners. Percentages may not sum to 100 due to rounding. Scale 0–9.
SOURCE: National Center for Education Statistics (2000: Table 13).
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TABLE 3–14 First-Time Kindergartners’ Mean Gross Motor Skills Score and Percentage Distribution of Scores, by Child and Family Characteristics: Fall 1998
Score Distribution (percent)
Characteristic
Mean Score
Lower
Middle
Higher
Total
6
26
35
39
Child’s Sex
Male
6
31
36
33
Female
7
22
34
44
Child’s Age at Entry
Born Jan.-Aug. 1992
7
21
32
47
Born Sep.-Dec. 1992
7
21
33
46
Born Jan.-Apr. 1993
6
24
35
41
Born May-Aug. 1993
6
31
36
33
Born Sep.-Dec. 1993
6
37
35
28
Mother’s Education
Less than high school
6
30
35
35
High school diploma or equivalent
6
28
35
37
Some college, including vocational/technical
6
25
35
40
Bachelor’s degree or higher
5
24
34
42
Family Type
Single mother
6
26
33
41
Single father
6
33
33
34
Two parent
6
27
35
38
Welfare Receipt
Utilized AFDC
6
29
32
38
Never utilized AFDC
6
26
35
39
Primary Language Spoken in Home
Non-English
6
30
34
36
English
6
26
35
39
Child’s Race/Ethnicity
White, non-Hispanic
6
28
35
37
Black, non-Hispanic
7
21
33
46
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Score Distribution (percent)
Characteristic
Mean Score
Lower
Middle
Higher
Child’s Race/Ethnicity
Asian
6
26
36
38
Hispanic
6
28
35
37
Hawaiian Native/Pacific Islander
6
26
40
34
American Indian/Alaska Native
6
31
29
40
More than one race, non-Hispanic
6
24
38
38
Child’s Race/Ethnicity by Maternal Education
High school diploma/equivalent or more
White, non-Hispanic
6
27
35
38
Black, non-Hispanic
7
21
33
46
Asian
6
26
35
39
Hispanic
6
28
35
37
Less than high school diploma or equivalent
White, non-Hispanic
6
36
34
30
Black, non-Hispanic
7
22
35
43
Asian
6
33
34
33
Hispanic
6
29
36
35
NOTE: Estimates based on first-time kindergartners. Percentages may not sum to 100 due to rounding. Scale 0–8.
SOURCE: National Center for Education Statistics (2000: Table 14)
CHILDREN WITH DISABILITIES
At one end of the distribution of physical and motor abilities are those children with disabling conditions. These conditions range from those that are low in incidence but high in impact— such as cerebral palsy, Down syndrome, muscular dystrophy, and autism—to less disabling, but higher-incidence disorders—such as learning disabilities and attention deficit and hyperactivity disorder. The number of identifiable conditions is far too great for concise summary (see Batshaw, 1997).
Children with disabilities vary as much as all children do in temperament, personality, and family culture (Meisels and Shonkoff, 2000). Studies have shown, however, that chiefly on
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the basis of language and conversational skills, children with disabilities are incorrectly (or inaccurately) perceived as being of lower social status (Hemphill and Siperstein, 1990) and are treated as such by their peers in preschool classrooms, both those who do and who do not have disabilities (Guralnick, 1990). In preschool, children with disabilities tend to have more extensive interactions with adults than with other children, which is the reverse of their age mates without disabilities (Herink and Lee, 1985). The children are likely to initiate less often to other children, and their initiations are more likely to be ignored (Rice et al., 1991; Vandell and George, 1981). The more severe the disability, the less the amount of interaction with peers (Guralnick and Paul-Brown, 1986).
Since 1992 states have been required to make a free appropriate public education available to all children with disabilities ages 3 through 5 in order to be eligible for funding under the Preschool Grants Program of the Individuals with Disabilities Education Act (P.L. 10 1–476, 1990). The number of students in that category who are being served increased steadily over the subsequent five years, with 4.6 percent of children in this age group being served in 1996–1997 (U.S. Department of Education, 1999). A little over half of these students (51.6 percent) were served in regular preschool classrooms.
The NCES survey collected data on children at kindergarten entry who have developmental difficulties as reported by parents in the areas of activity level, attention, coordination, and articulation (Table 3–15). These difficulties are not necessarily indicators of a disability or diagnosis; parents were simply asked to rate their children in comparison to other children of the same age, and risk of developmental difficulty was indicated if the child was considered “a lot more” active, paid attention “less well or much less well,” or if coordination and word pronunciation was “slightly less or much less” than other children of that age (National Center for Education Statistics, 2000).
While only 4 percent of children were considered to be less coordinated than their peers, 11 percent were rated as being less articulate. Parents rated 13 percent of children as attending less well or much less well than their peers, and 18 percent as being a lot more active. Boys were more often identified than girls, and
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TABLE 3–15 Percentage of First-Time Kindergartners Whose Parents Reported Developmental Difficulty in Terms of Activity Level, Attention, Coordination, and Pronunciation of Words: Fall 1998
Characteristic
Activity level
Attention
Coordination
Articulation
Total
18
13
4
11
Child’s Sex
Male
20
18
5
14
Female
16
9
3
7
Child’s Age at Entry
Born Jan.-Aug. 1992
20
18
8
18
Born Sep.-Dec. 1992
19
13
4
10
Born Jan.-Apr. 1993
18
12
3
10
Born May-Aug. 1993
18
15
4
11
Born Sep.-Dec. 1993
17
14
4
11
Mother’s Education
Less than high school
24
17
4
14
High school diploma or equivalent
19
14
4
12
Some college, including vocational/technical
18
14
4
10
Bachelor’s degree or higher
14
10
5
8
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Characteristic
Activity level
Attention
Coordination
Articulation
Family Type
Single mother
25
16
4
11
Single father
22
15
4
10
Two parent
16
12
4
10
Welfare Receipt
Utilized AFDC
26
19
4
15
Never utilized AFDC
17
13
4
10
Primary Language Spoken in Home
Non-English
17
9
2
10
English
19
14
4
11
Child’s Race/Ethnicity
White, non-Hispanic
16
13
5
11
Black, non-Hispanic
30
17
3
11
Asian
16
9
3
12
Hispanic
17
11
3
10
Hawaiian Native/Pacific Islander
15
12
5
12
American Indian/Alaska Native
25
15
5
10
More than one race, non-Hispanic
20
17
2
12
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Child’s Race/Ethnicity by Maternal Education
High school diploma/equivalent or more
White, non-Hispanic
15
13
5
10
Black, non-Hispanic
28
15
3
9
Asian
17
9
3
11
Hispanic
17
12
3
10
Less than high school diploma or equivalent
White, non-Hispanic
28
23
5
17
Black, non-Hispanic
36
25
5
19
Asian
12
7
3
16
Hispanic
16
10
3
9
NOTE: Estimates based on first-time kindergartners. Developmental difficulties are defined as: activity level a lot more active than children the same age and attention, articulation and coordination are less well or much less well than children the same age.
SOURCE: National Center for Education Statistics (2000: Table 16).
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in the areas of attention and articulation they were identified at twice the rate. Mother’s education has a substantial impact on activity level, attention, and articulation ratings, as does single-parent status and welfare receipt. English speakers were identified with all characteristics more often than non-English speakers. Reported attention and activity level vary substantially by race, with black, American Indian, and mixed race children identified considerably more often than other race or ethnic groups. There were small differences in coordination and articulation by race, with black, Hispanic, Asian, and mixed race children identified less often with coordination problems than other races.
SUMMARY
While development occurs in a similar fashion for all children, developmental differences are the inevitable result of individual genetic and experiential variations and differing cultural and social contexts. In the past several decades, variability has been taken more seriously by social scientists who study children. From that research base we are learning ever more about the magnitude and sources of variation among children.
Chapter 2 suggested that development is fostered when a child is engaged in activities (both cognitive and social) that are at an appropriate level of difficulty: challenging, but within the reach of the child’s competence. We suggested further that development is very much dependent on context, and that an adult who is responsive to the child’s level of social, emotional, and cognitive development is a key feature of a supportive context. The research reviewed in this chapter suggests the variability of competencies in children by the end of the preschool years. In both cognitive and social skills, and in the physical and motor development that support those skills, young children vary enormously.
Biology’s contribution to temperament, learning style, and motor facility clearly influences children’s developmental pathways. To effectively foster growth in children with very different temperaments, learning styles, activity levels, and abilities to attend will require different types of interaction and opportunities to learn.
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We know, moreover, that the resources (books, audio recordings, and the like) and activities (book reading, story telling, verbal interaction) to which children in higher-SES categories are exposed are strong correlates of cognitive development, and that SES is correlated with social and some forms of physical development as well. By the time children reach kindergarten, these differences are already noteworthy. If preschool programs are to help all children develop their potential in early years, those from less enriched environments will need opportunities to acquire the skills of those in more enriched environments, as well as to develop to the maximum the unique skill sets they bring to the formal school setting.
Children with disabilities vary as much as all children do in temperament, learning style, and family culture. In preschool, children with disabilities tend to have more extensive interactions with adults than with other children, which is the reverse of their age mates without disabilities. Children with disabilities are likely to initiate less often to other children and their initiations are more likely to be ignored. An adult who is responsive to the developmental needs of the child with disabilities will help facilitate relationships with other children. The inclusion of children with disabilities in child care settings is required by law, but beyond meeting the legal mandate, the addition of children with disabilities can add to the diversity, and thus the richness, of all children’s experience.
Regarding cultural background, there is a solid knowledge base on variations around the world in children’s social developmental pathways, such as those needed for collectivist values and those for societies that value independence and autonomy. In the United States, research is now being conducted on the various cultural groups that make up the population, for certain developmental psychologists are paying more careful attention to the influence of cultural background on the development of children’s social and emotional capacities. Research on cultural background and schooling identify many factors as important. Among these are the effects of the knowledge base, social organization (value placed on working quietly, acceptance of help from unfamiliar adults, etc), and social rules of conversation (child initiating, “wait” time, etc).
Representative terms from entire chapter:
motor skills
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