Early language and the development of children's reading skills

Journal of School Psychology 42 (2004) 315 – 332

Early language and the development of children’s reading skills Michele D. Poe*, Margaret R. Burchinal, Joanne E. Roberts Frank Porter Graham Child Development Institute, CB 8185, University of North Carolina, Chapel Hill, NC 27599-8185, United States Received 5 February 2004; accepted 23 June 2004

Abstract There is considerable agreement that vocabulary plays a central role in reading acquisition, but there is less agreement about whether this association is direct or indirect through phonological and print-related knowledge. Longitudinal data from 77 African-American children were analyzed to examine the relationship between language skills, phonological knowledge and print processing skills at pre-kindergarten and kindergarten with reading at pre-kindergarten through second grade. Analyses indicated that home and child care experiences were related to reading indirectly through language and that language and phonological knowledge were both directly related to acquisition of reading skill. This study of African-American children and previous studies of lower- and middle-income children indicate both language and phonological skills play an important role in children becoming successful readers, and that experiences at home and in child care during in early childhood play a role in the acquisition of reading through their enhancement of early language and phonological skills. D 2004 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved. Keywords: Reading; Language; Phonological awareness; African-American; Home environment

Introduction Learning to read is essential for all children to succeed in school and later as adults. Up to one-third of children experience significant difficulties in learning to read and many of * Corresponding author. Tel.: 1 919 966 5607; fax: 1 919 962 5771. E-mail address: [email protected] (M.D. Poe). 0022-4405/$ - see front matter D 2004 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.jsp.2004.06.001

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these children continue to have problems throughout their adult lives (Adams, 1990; Shaywitz, Fletcher, Holahan, & Shaywitz, 1992). About two-thirds of the children who show sufficient difficulties to be diagnosed as disordered continue to display poor reading skills throughout their school years and into adulthood (Scarborough, 2001). Accordingly, research has focused on identifying the skills necessary for learning to read (see Neuman & Dickinson, 2001 for a comprehensive review). Understanding the role of early language and literacy in children’s development of reading skills is particularly important for African-American children from low-income families who tend score lower in language and emergent literacy skills during the preschool years and are at increased risk for literacy difficulties in school as compared to their non-minority cohorts (Byrd & Weitzman, 1994; Children’s Defense Fund, 2001; Jencks & Phillips, 1998; Snow, Burns, & Griffin, 1998; The College Board, 1999). The role of early language and literacy skills in children’s acquisition of reading has been a topic of extensive debate and research. One of the most consistent findings in the literature is that vocabulary plays a central role in reading acquisition, but there is less agreement about whether this association is direct or indirect through phonological and print-related knowledge (Neuman & Dickinson, 2001). According to one point of view, labeled here as the cumulative language approach, language skills interact with literacy knowledge and phonological knowledge, and all three are important for learning to read (Snow et al., 1998). In contrast, an alternative point of view, labeled here as the phonological approach, is that vocabulary provides the basis for the acquisition of phonological knowledge during the preschool period, and phonological knowledge underlies the acquisition of reading (Whitehurst & Lonigan, 2001). However, few studies have compared these two models with longitudinal data from the preschool through elementary school years using comparable statistical models or methods (Dickinson, McCabe, Anastasopoulos, Peisner-Feinberg, & Poe, 2003). According to the cumulative language perspective, a variety of oral language skills are critical for emergent literacy and the development of reading skills (Neuman & Dickinson, 2001; Snow et al., 1998). This approach posits that oral language skills such as vocabulary, phonological awareness, syntax, and discourse are interrelated skills that lay the foundation for emergent literacy and subsequent reading skills (Neuman & Dickinson, 2001). A recent meta-analysis by Scarborough (2001) of 61 studies on independent samples supports this view. Scarborough reported that the strongest predictor of reading in first or second grade was print processing skills at kindergarten entry. The number of letters the child could identify at kindergarten entry was the best predictor of reading skills (median r=.52), followed by measures of oral language (median r=.47) and of phonological awareness (median r=.42). Measures of nonverbal skills were the poorest predictors of later reading. For example, measures of visual memory showed only modest correlations (median r=.28). Furthermore, advocates of the cumulative language approach believe that language skills, phonological knowledge, and print processing skills impact each other in an iterative manner. For example, empirical evidence suggests that larger vocabularies bolster the emergence of phonological awareness (Goswami, 2001). A number of studies have demonstrated the interrelations among vocabulary, phonological knowledge, and the development of literacy skills during the preschool

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and early elementary years. Dickinson and colleagues (Dickinson et al., 2003) found that both receptive language and phonemic sensitivity provided about equal independent prediction of literacy skills among 533 Head Start preschoolers. Dickinson and Tabors (1991) conducted an 11-year study of 74 Head Start children, measuring language, phonemic abilities, and literacy skills beginning at 3 years of age. They found that early language skills at 3–4 years predicted both fourth and seventh grade decoding and reading comprehension. Children’s reading skills in 4th and 7th grade were predicted by narrative production, receptive vocabulary, and emergent literacy skills at 3 and 4 years, even when all three types of skills were considered together. Similarly, other studies have shown that language at entry to kindergarten showed substantial and increasing power to predict reading skills during early to middle elementary years (Cunningham & Stanovich, 1998; Mason, Stewart, Peterman, & Dunning, 1992; Snow & Dickinson, 1991). Consistent with this point of view is the literature indicating that family and child care experiences impact cognitive and language development directly and reading acquisition indirectly through language. Child care intervention studies indicate that low-income children who attended high quality child care had improved reading skills due to the impact of the child care on the children’s early language and cognitive skills (Campbell, Pungello, & Miller-Johnson, 2002). The sensitivity and stimulation available in the family environment has been implicated for reading acquisition (Bradley, 2002, 2003). In contrast, consistent with the phonological approach, other investigators argue that vocabulary and other oral language skills lay the foundation for emergent phonological processes in the preschool years, and it is the phonological processes that are necessary for learning to read (see Whitehurst & Lonigan, 2001 for a review of this literature). They argue that vocabulary and discourse skills play an important role in the emergence of phonological sensitivity (i.e., ability to detect and manipulate the sound structure of oral language), phonological memory (i.e., short-term memory for sound-based information), and phonological naming (i.e., retrieval of phonological information from long-term memory), and it is these skills that uniquely predict reading skills once children enter school. Empirical evidence comes from structural equation analyses of longitudinal reading scores for a large sample of children in Head Start (Whitehurst & Lonigan, 1998) and a large sample of lower-class and middle-class children in child care (Lonigan, Burgess, & Antony, 2000), regression analyses for a large sample of middle-class children (Senechel & LeFevre, 2002), and clinical trials focusing on phonological sensitivity (cf., Bus & van Ijzendorn, 1999). Two of these studies are described in more detail below to illustrate this point of view. The study by Whitehurst and Lonigan (1998) provided a model that is frequently cited to support the direct role of phonological processing in reading and indirect role of language. Their model posits boutside-inQ and binside-outQ skills that provide the basis for learning to read. The boutside-inQ skills reflect the ability to understand language and place the information in language within conceptual and contextual frameworks. These skills include traditional oral language skills such as vocabulary and storytelling skills. The binside-outQ skills reflect the ability to decompose units of language into sounds and units of sounds into print. Whitehurst and Lonigan followed a sample of 367 children from Head Start classrooms into second grade. They measured binside-outQ and boutside-

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in skillsQ beginning when children were in Head Start and through the early elementary school using a structural equation model to predict reading in second grade. The binsideoutQ skills assessed were phonological awareness and knowledge about print in Head Start and kindergarten and emergent writing at kindergarten entry. The outside-in skills included standardized tests of vocabulary administered in Head Start, kindergarten, and first and second grades. Reading was assessed using standardized assessments in first and second grade. They found that children’s vocabulary skills (outside-in skills) predicted their development of phonological knowledge (inside-out skills), which in turn predicted reading skills in first and second grade. Vocabulary was indirectly related to reading through its association with phonological knowledge and phonological knowledge was directly related to reading. A recent longitudinal study by Senechel and LeFevre (2002) also supports the phonological approach, but also provides evidence that vocabulary has a direct impact on higher-level reading skills as well as an indirect relation with lower-level reading skills through phonological knowledge. They studied the relation between home literacy practices and reading in 168 middle class children followed from kindergarten through third grade. They assessed receptive language (i.e., vocabulary and listening comprehension), phonological awareness, emergent literacy (i.e., print concepts, alphabet knowledge, invented spelling, and decoding) at the beginning of first grade and reading skills at the end of first and third grades. They found that receptive language indirectly, not directly, related to emergent literacy at the beginning of grade 1 and reading at the end of first grade. Like Whitehurst and Lonigan (1998), they reported that receptive language predicted early reading skills in grade 1 indirectly through phonological awareness. In contrast, both language and phonological awareness directly contributed to third-grade reading skills. Further, home literacy activities such as book reading were related to early language skills whereas direct instruction in reading by parents or teachers related to early emergent literacy skills. Early language and phonological awareness skills were interrelated as was early phonological awareness and emergent literacy skills, but language did not directly relate to emergent literacy. Finally, the literature on reading disabilities also supports the critical role of phonemic knowledge in learning to read (Lyon & Chhabra, 1996; Shaywitz et al., 1992). The literature has focused on determining how children with reading difficulties differ from typically developing children and whether subgroups of children with reading disorders show different reading profiles. One of the most consistent findings is that children with reading disorders have problems with phonological processing (Lyon & Chhabra, 1996; Shaywitz et al., 1992). These children have more trouble than children without diagnosed reading disabilities in both processing print into sounds and words and processing sounds and words into print. The work by Senechel and LeFevre (2002), Dickinson and Tabors (1991), and Mason et al. (1992) suggest that the cumulative language and phonological approaches are not as discrepant as they appear on the surface. Both approaches emphasize the role of oral language in preparing the child to begin to learn to read. The cumulative language approach argues that language has both a direct and indirect effect on early reading acquisition, whereas the phonological approach argues language prepares the child for acquiring phonemic knowledge, and the phonemic knowledge is necessary to acquire

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Fig. 1. The relationship between language and reading over time illustrated by estimated reading scores for children have language scores that are 1 standard deviation above or below the mean.

Fig. 2. The relationship between phonemic knowledge and reading over time illustrated by estimated reading scores for children have phonemic language scores that are 1 standard deviation above or below the mean.

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decoding skills. Further, there is relatively consistent evidence (e.g., Dickinson & Tabors, 1991; Senechel & LeFevre, 2002) that language skills directly promote reading comprehension skills. The purpose of the current study was to examine the extent to which language skills, phonological knowledge, and print processing skills at entry to school and kindergarten predict reading skills in second grade. These issues were studied in an African-American sample because African-American children are at greater risk than majority children for lagging behind in reading achievement (Byrd & Weitzman, 1994; Children’s Defense Fund, 2001; The College Board, 1999). A longitudinal regression model was fit to identify direct and indirect associations between vocabulary and phonological knowledge and reading skills from repeated assessments collected prior to kindergarten, at the end of kindergarten, and at the end of second grade. Family and home environments were further examined to determine if they act directly to enhance reading skills or indirectly through increasing language, phonologic skills and print awareness.

Methods Participants Seventy-seven African-American children (35 boys, 42 girls), who were included in a longitudinal study of children’s health and development, were participants in this study (see Roberts et al., 1995, 1998 for details). The Preschool to School Project has examined how child (including a history of otitis media and language skills), family, school, and neighborhood characteristics affect children’s transition into school and their later progress through school. Children were recruited from 9 center-based childcare programs in Chapel Hill or Durham, NC, at ages 6–12 months (mean age=8.2 months) over a 20-month period. No child had any known medical or genetic abnormalities when entering the study. When children entered the study, 75% of families were classified as low-income based on whether family income was less than 185% of the federal poverty threshold (less than $20,609 for a family of three). Sixty-eight percent of the primary guardians were single. The highest level of education of the child’s caregivers ranged from less than a high school degree (30.1%), high school degree (26.5%), some college or other training after high school (32.4%), or a college degree (11%). Measures Frequent assessments of the children, their families, and their child care experiences were collected, using instruments chosen for reliability and validity. Table 1 lists the measures selected for inclusion in analyses. There were three criteria used to select measures. They were selected to measure comparable constructs to those used in previous studies. We restricted ourselves to measures that were collected longitudinally so that our constructs are measured similarly at each time point. The instruments were standardized measures with good psychometric criteria. Finally, we restricted ourselves to one measure per construct due to our moderate sample size.

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Table 1 Descriptive statistics on literacy, language, and phonological knowledge measures (n=77) Maternal education Maternal IQ Child care quality Literacy environment HOME total 9–42 months HOME total 9 months HOME total 18 months HOME total 18 months HOME total 18 months MOM book Maternal Involvement 12–48 months Maternal Involvement 12 months Maternal Involvement 24 months Maternal Involvement 36 months Maternal Involvement 48 months Language measures CELF-Total Language: pre-K CELF-Total Language: kindergarten CELF-Total Language: Grade 2 Phonemic knowledge WJ-Incomplete Words: pre-K WJ-Incomplete Words: kindergarten WJ-Incomplete Words: grade 2 Literacy measures WJ-Letter Word Identification: pre-K WJ-Letter Word Identification: kindergarten W–J Broad Reading: Grade 2

Mean

SD

Range

13.1 86.5 3.4

2.0 10.3 0.9

9.0–18.0 69.0–120.0 1.3–5.1

0.8 0.8 0.8 0.8 0.8 62.0 3.5 2.6 3.8 3.9 3.8

0.1 0.1 0.2 0.1 0.1 19.2 0.5 0.6 0.6 0.7 0.7

0.6–0.9 0.5–1.0 0.4–1.0 0.4–0.9 0.5–1.0 13.7–137.0 2.1–4.5 1.4–4.4 2.5–5.0 2.3–5.0 2.0–5.0

97.3 92.7 95.9

13.2 13.1 13.5

68–123 57–120 59–115

92.3 89.1 93.6

7.6 8.7 12.6

72–114 69–116 65–122

92.4 94.9 104.4

12.6 12.3 14.6

70–125 68–127 52–135

Language Children’s language skills were assessed with the Clinical Evaluation of Language Fundamentals (CELF). The preschool version was administered prior to entry to kindergarten (CELF-P, Wiig, Secord, & Semel, 1992), and the school-age version (CELF-3, Semel, Wiig, & Secord, 1995) was administered at end of kindergarten and at the end of second grade. The CELF provides an overall measure of receptive and expressive language by examining children’s concepts, syntax, semantics and morphology. Both the CELF-P and CELF-3 examine word and linguistic concepts, word and sentence structures, and recalling sentences; the CELF-P also includes formulating labels and basic concepts and the CELF-3 includes formulating sentences word classes (CELF-3). Phonological knowledge Children’s phonological knowledge was assessed with the Incomplete Words Scale from Woodcock–Johnson Psycho-Educational Battery–Revised (WJ; Woodcock & Johnson, 1990). The Incomplete Words scale requires the child to identify a word upon hearing the word on audiotape in which one or more phonemes is missing (e.g., botatoQ for bpotatoQ).

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Reading skills Children’s reading skills were measured with the Letter–Word Identification Scale and Broad Reading score from Woodcock–Johnson Psycho-Educational Battery–Revised (Woodcock & Johnson, 1990). The Letter–Word Identification scale measures pre-reading and reading skills by asking children to identify first letters and then words of increasing difficulty. The pre-kindergarten and kindergarten assessments were regarded as a measure of emergent literacy and were highly correlated with the total score from the TERA, a standardized test of emergent literacy, r=.69. The second grade Broad Reading score includes both the Letter–Word Identification and the Passage Comprehension Scales. Letter–Word Identification tests both symbolic learning (matching a symbolic representation of an object to an actual picture of the object) and reading identification skills (identifying words and isolated letters). Passage Comprehension tests the child’s ability to point to a picture represented by a phrase (multiple choice), and to read a short passage and identify a missing word (open-ended). Literacy environment Longitudinal assessments of three measures of the family environment were collected: a semi-structured interview, ratings of maternal sensitivity, and the use of strategies in reading a book to the child. The Home Observation for the Measurement of the Environment (HOME; Elardo & Bradley, 1981) was conducted in the child’s home when he or she was 9, 18, 30, and 42 months of age. This semi-structured interview is composed of six subscales: (1) emotional/verbal responsiveness of the parent, (2) acceptance of the child’s behavior, (3) organization of the environment, (4) provision of appropriate play materials, (5) maternal involvement with child, and (6) variety in daily experience. A total score at each age was computed as the proportion of items passed, and a total across-age score was computed as the mean of the total scores from each age. Mothers were asked to read to their child when he or she was 12, 24, 36, and 48 months of age. The level of maternal responsiveness and stimulation during book-reading was rated, and a composite score was computed (Marfo, 1992). The maternal behaviors coded were warmth, sensitivity, responsiveness, encouragement of initiative, stimulation value, and elaborateness. A composite score was created from the ratings after principal components analysis indicated that these ratings could be combined into a single score. In addition, the mother’s use of strategies in reading to her child was coded. The videotaped interactions were coded for the frequency with which the mother did the following: simple description, elaborate description, links to the world, prediction of infant’s needs, book concepts, or letter/sound/word relationships. The mean of these composite scores from each age was computed. The across-time mean HOME, maternal sensitivity, and maternal book reading scores were used as indicators of the latent variable representing the home literacy environment. Child care environment The quality of center-based infant and toddler child care was assessed annually using the Infant/Toddler Environment Rating Scale (ITERS) (Harms, Cryer, & Clifford, 1990) and of preschool child care with the Early Childhood Environment Rating Scale (ECERS) (Harms & Clifford, 1980). The ITERS was collected in classrooms which included

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children under the age of 2 years, whereas the ECERS was collected in classrooms in which all children were 2 years and older. The ITERS provides an assessment of the environment, curriculum, teacher–child interactions, and teaching practices in classes of children from birth to 30 months of age. It is a downward extension of the Early Childhood Environment Rating Scale (Harms & Clifford, 1980). The ITERS consists of 35 items and the ECERS of 37 items. Each item is rated on a 7-point scale with descriptors for 1 (inadequate), 3 (minimal), 5 (good), and 7 (excellent). The total score is calculated as the mean of the child-related items (i.e., first 28 items on the ITERS and 32 items on the ECERS. Covariates The child’s gender and the mother’s IQ and education were added as covariates. At entry to the project, the mothers were administered the vocabulary and block design scales from the WAIS, and an IQ was estimated from these scores. During the assessment collected prior to entry to kindergarten, each mother was asked to list the final grade completed in high school and whether she completed any post-high school degrees.

Results Analysis plan Longitudinal regression analyses were conducted using a general linear mixed model approach to repeated measures analysis (Singer, 1998). This approach involves fitting a separate cross-sectional model to each of the repeated assessments within a single analysis model, and testing the extent to which each predictor shows consistent patterns of association over time with the outcome or shows a different pattern of association with the outcome at different ages. The model predicted repeated assessments of reading (WJ Letter–Word Identification and Broad Reading) from repeated assessments of language (CELF total score) and phonological knowledge (WJ-R Incomplete Words) and measures of the family (overall and literacy stimulation in the family environment and maternal education and IQ) and child care environments during early childhood. The model included each of these predictors, age, and interactions between age and each predictor. Age was entered as a categorical variable, thereby producing parameter estimates for each predictor for each assessment age. To account for the correlations among the repeated measures over time, this model estimated a separate variance at each of the three assessment ages and covariances across age. The analysis plan involved fitting a series of models to test for mediation using the approach advocated by Baron and Kenny (1986). Evidence of mediation is obtained if three conditions are met. First, there is a stronger association between the predictor and outcome in analyses when the model does not include the hypothesized mediator than when the model includes both the predictor and mediator. Second, the predictor is related to both the mediator and outcomes. Third, the mediator is related to the outcome variable. Efforts were made to create a single variable to represent each major construct. This was done to minimize overlap among correlated predictors, especially multiple measures

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of the same construct, and decrease the number of parameters that had to be estimated with our moderate sample size. To represent language skills over time, we used the total language score from the CELF rather than the multiple subscales used in previous research. Similarly, we selected the Woodcock–Johnson Incomplete Words scale to represent phonological knowledge because it was the only phonological assessment collected consistently at each time point. A composite representing the quality of the family environment was created by computing a within-sample standardized score on each of the three indicators (HOME, maternal sensitivity, and maternal book reading strategies) and then computing the mean of those scores. We tested for evidence of mediation by fitting a series of models (Baron & Kenny, 1986). We were interested in two potential mediators. First, we hypothesized that early family and child care environments would be related to reading indirectly though language. Second, we hypothesized that language would be related to early reading indirectly through phonological knowledge. Descriptive statistics Descriptive statistics are shown in Tables 1 and 2. The means and standard deviations for all analysis variables are listed in Table 1. About two-thirds of the sample was lowincome, qualifying for free or reduced price lunch in public schools. The children scored at or slightly below national norms on measures of language, phonemic knowledge, and reading. The correlations among the measures are listed in Table 2. Moderate to high correlations were observed among the repeated assessments of language on the CELF (.76b.rb.79), phonemic knowledge on the WJ-R (.45brb.58), and reading skills on the WJ-R (.55brb.66). Both measures of language and of phonemic knowledge were moderately correlated with reading skills in second grade (.44brb.63). Longitudinal regression model A repeated measures analysis was conducted using general linear mixed models (Singer, 1998). Longitudinal reading scores from the WJ-R were predicted from longitudinal assessments of language (CELF total score) and phonemic knowledge (WJ-R Incomplete Words). Covariates included preschool assessments of maternal IQ and education and the quality of the family and child care environments. The preliminary model included age and interactions between age and each of the predictors; however, the age interactions were dropped when reliable evidence suggesting age trends was not obtained. The first model addressed the first mediation hypothesis, and was designed to demonstrate that the predictors (family and child care environments) were related to the mediators (language skills and phonological knowledge) and the outcome (reading). This model included only the measures of family and child care and the covariates. Results are shown in Table 3, listing the unstandardized parameter estimates and their standard errors for the measures of family and child care environments and the covariates. The analysis indicated that the family environment composite was positively associated with reading skills (B=4.48, F(1,67)=1.94, p=.024), and marginally with language skills (B=3.45,

1 Maternal education 2 Maternal IQ 3 Child care quality 4 HOME Total 9–42 months 5 MOM Book 6 Maternal Involvement 12–48 months 7 CELF-Total Language: pre-K 8 CELF-Total Language: kindergarten 9 CELF-Total Language: grade 2 10 WJ-Incomplete words: pre-K 11 WJ-Incomplete words: kindergarten 12 WJ-Incomplete words: grade 2 13 WJ-Letter Word Identification: pre-K 14 WJ-Letter Word Identification: K 15 WJ Broad Reading: grade 2

Maternal characteristics Child care Family environment

CELF Total Language

WJ Incomplete Words

WJ Reading

1

2

3

4

5

6

7

8

9

10

11

12

13

1.00 .63 .07 .58 .36 .57 .30 .34 .39 .18 .14 .20 .20 .17 .28

1.00 .11 .54 .16 .49 .33 .43 .45 .25 .13 .26 .25 .15 .28

1.00 .40 .12 .23 .46 .21 .31 .31 .31 .24 .14 .01 .22

1.00 .41 .55 .55 .45 .55 .48 .39 .25 .46 .36 .55

1.00 .57 .37 .23 .35 .23 .28 .06 .22 .13 .18

1.00 .40 .32 .43 .29 .35 .34 .28 .27 .34

1.00 .79 .76 .56 .55 .47 .43 .34 .49

1.00 .77 .50 .43 .54 .32 .36 .56

1.00 .45 .45 .49 .40 .35 .63

1.00 .58 .20 .49 .47 .44

1.00 .47 .50 .58 .51

1.00 .37 .40 .45

1.00 .66 1.00 .55 .65 1.00

14

15

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Table 2 Correlations among longitudinal assessments of family, child care, language, phonological knowledge, and reading

325

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Table 3 Early childhood experiences and acquisition of reading, language, and phonological knowledge WJ Reading B (S.E.) Model 1—Family and child care factors only Male 4.73+ (2.46) a Maternal IQ .11 (.16) .01 (.89) Maternal educationa Family environmenta 4.49* (1.94) Child carea .09 (1.47)

CELF Language B (S.E.)

WJ Incomplete Words B (S.E.)

6.11** .21 (.14) .35 (.82) 3.45+ (1.78) 3.24* (1.36)

2.46 (1.43) .10 (.09) .11 (.52) 2.03+ (1.13) 1.90* (.86)

***pb.001. a Initial model included interactions between the family and child care variables and age, but those were dropped when found to be nonsignificant. * pb.05. ** pb.01. + pb.10.

F(1,67)=1.94, p=.057) and phonemic knowledge (B=2.03, F(1,67)=1.79, p=.078), and that the child care environment was related to language skills (B=3.24, F(1,67)=2.39, p=.020) and phonemic knowledge (B=1.90, F(1,67)=4.88, p=.031). The next set of analyses was designed to test the second mediation hypothesis by demonstrating the interrelations among repeated assessments of language, phonemic knowledge, and reading in analyses that considered the two of them simultaneously. Results are listed in Table 4. Table 4 lists the F-test for the main effect in the first column, the F-test for the age interaction in the second column, and the age-specific parameter estimates and their standard errors in the next three columns. If the age interaction was significant, then superscripts on the coefficients in the last three columns indicate which coefficients differed significantly. Model 2 tested the extent to which repeated assessments of phonemic knowledge skills were related to the repeated assessments of language. As shown in Table 4, language was consistently related to phonemic knowledge ( F(1,67)=13.65, pb.001), and the magnitude of this association did not vary significantly over time ( F(2,67)=2.17, p=.14). Models 3A and 3B tested the extent to which repeated assessments of language and phonemic knowledge predicted repeated assessments of reading, respectively. Language was a positive predictor of reading skills ( F(1,67)=15.48, pb.001), but the magnitude of the association changed over time ( F(2,67)=5.37, p=.007). Language skills were more strongly associated with reading skills in second grade (B=.52) than at pre-kindergarten (B=.23) or kindergarten (B=.19). Phonemic knowledge was also a positive predictor of reading skills ( F(1,67)=14.75, pb.001), and the magnitude of the association did not significantly change over time ( F(2,67)=0.15, p=.86). Phonemic knowledge was positively associated with reading skills in pre-kindergarten (B=.36), kindergarten (B=.38), and second grade (B=.30). The final analysis (Model 4) predicted reading as a function of the covariates and repeated assessments of language and phonemic knowledge. Results from this final analysis are shown in the bottom rows of Table 3 under the heading Model 4. As shown, this analysis suggests that both language and phonemic knowledge are related to the development of reading skills from preschool through second grade, but that language

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Table 4 Longitudinal regression analyses predicting reading and testing mediation Main effect F(1,68)

Time interaction F(2,68)

Pre-K B (S.E.)

KB (S.E.)

Grade 2 B (S.E.)

Model 2 a Language as a function of Phonological Knowledge WJ Phonological Knowledge 13.65*** 2.17

.12+ (.07)

.15* (.07)

.37** (.11)

Model 3A b Reading as a function of language CELF Language total 15.48***

.23* (.11)

.19* (.10)

.53*** (.11)

.37* (.16)

.38** (.12)

.30** (.10)

96.40 (1.26) 3.36 (2.26) .03 (.14) .06 (.79) 2.50 (1.76) 1.68 (1.34) .13 (.09) .44*** (.12)

104.04 (1.39) 3.36 (2.26) .03 (.14) .06 (.79) 2.50 (1.76) 1.68 (1.34) .55*** (.12) .09 (.11)

5.37**

Model 3B a Reading as a function of Phonological Knowledge WJ Phonological Knowledge 14.75*** 0.15

Model 4 Reading as a function of Language and Phonological Knowledge Age 34.19*** 91.39 (1.42) Male 2.22 3.36 (2.26) Maternal IQ 0.05 .03 (.14) Maternal education 0.81 .06 (.79) Family environment 2.07 2.50 (1.76) Child care 1.56 1.68 (1.34) CELF Language total 14.85*** 5.85** .24* (.12) WJ Phonological Knowledge 9.88** 2.70+ .31 (.19)

a Models 2 and 3 also included the same covariates (age, maternal IQ, maternal education, family environment, and child care environment). Coefficients are not included because they were very similar to those listed under Model 4. b Initial model included interactions between the family and child care variables and age, but those were dropped when clearly nonsignificant. * pb.05. ** pb.01. *** pb.001. + pb.10.

shows a different pattern of association in pre-kindergarten and kindergarten than in second grade. The main effect test for language ( F(1,67)1=14.85, pb.001) suggests that language is clearly related to reading, but the interaction between language and age ( F(2,67)=5.85, p=.005) indicate that language is more strongly related to reading in second grade than at pre-kindergarten or in kindergarten (Fig. 1). The main effect for phonemic knowledge ( F(1,67)=9.88, p=.003) also suggested that phonemic knowledge was related to reading, and that this association changed marginally over time ( F(2,67)=2.70, p=.074) (Fig. 2). The family and child care covariates did not significantly contribute to predicting reading scores in these analyses that included concurrent language and phonemic awareness measures. These analyses provide some evidence of mediation. They demonstrated that the family and child care environments were indirectly related to reading skills through enhancing language skills and phonemic awareness. Quality of family and child care environments

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related to language and phonemic awareness, and language and phonemic awareness were related to reading. These analyses also demonstrate that language and phonemic knowledge both provide independent and shared prediction of reading. However, the results suggest a direct association between language and reading at pre-kindergarten and second grade, not an indirect association through phonemic awareness. Finally, they provided evidence that language became a stronger predictor of reading skills at second grade when children should have acquired basic decoding skills than prior to entry to school or in kindergarten. In contrast, they provided a hint that phonological skills were most strongly related in kindergarten when children should be learning decoding skills and were least related in second grade.

Discussion This study provides further evidence that the development of early reading skills is related to both early language and phonemic knowledge. Longitudinal regression analyses indicate that language at entry to kindergarten through second grade has a direct association with reading, and this association became stronger in second grade when reading skills included assessment of both decoding and comprehension. Language, not phonemic knowledge, was the best predictor of reading skills in second grade, the age when children should have acquired basic decoding skills and many are reading for comprehension. Results are similar to those reported in previous work (e.g., Dickinson et al., 2003). In this study, longitudinal regression analyses suggested that both language and phonemic knowledge are directly related to the concurrent reading skills, with a hint that phonological skills were most strongly related in kindergarten and clear evidence that language skills were most strongly related in second grade. However, almost no evidence emerged suggesting that language was only indirectly related or had a mediated effect through phonological skills. The coefficients for language in models with and without phonological skills were not substantially different, thereby, failing to meet the major criterion for demonstrating mediation using the Baron and Kenny approach. The other findings from these analyses also replicate findings in previous studies. Our results provide further support for the important role of both language skills and phonemic knowledge in children’s acquisition of reading skills. Children’s language, phonological knowledge, and reading skills at 5, 6, and 8 years of age were moderately to highly correlated in this study. These results are similar to previous studies by advocates of both the cumulative language (e.g., Dickinson & Tabors, 1991; Dickinson et al., in press) and the phonemic awareness approach (e.g., Senechel & LeFevre, 2002; Whitehurst & Lonigan, 1998). In addition, similar to the extensive literature on child care quality (Lamb, 1998; Peisner-Feinberg et al., 2001), we found that children who experienced higher quality child care started school with better vocabularies, and therefore, had better reading skills because vocabulary at entry to school was related directly or indirectly to reading. Finally, our findings regarding the family literacy environment replicate findings by Senechel & LeFevre, (2002) and Bradley, Corwyn, Burchinal, McAdoo, and Garcia Coll (2001). We, too, found that the overall quality of the home environment combined with a

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measure of book-reading strategies showed an indirect effect on reading. Attempts to examine independent contributions of maternal sensitivity, home environment, and book reading failed due to the moderate to high correlations among the measures. Children who experienced more enriched literacy environments during early childhood started school with better language skills, and better language skills predicted better reading skills in second grade when children were expected to read for comprehension as well as for decoding. These findings are important, given that the study children were African-American and primarily from low-income families and at risk for reading difficulties compared to nonminority children. The data suggest the importance of children’s language development in their later reading skills as well as the role of the quality of the child care and home environment in children’s later language development. Interventions directed at improving the quality of the home and childcare environment may have important consequences for children’s language development and ultimately their reading skills. In particular, gaps in reading skills between white and African-American children observed as young as first grade (Children’s Defense Fund, 2001) are likely to be reduced or eliminated if public policies ensured that low-income African-American children have access to high-quality child care (Lamb, 1998) or to more reading and language opportunities at home (Hart & Risley, 1995). Several limitations should be considered. First, our sample size is moderate and the models are somewhat complex. We have longitudinal data, which increases the amount of information in our data, and we attempted to simplify the models as much as possible. Nevertheless, replication of results would be reassuring. Second, the WJ-R Incomplete Words Scale provides reasonable assessment of phonological knowledge, but it is not as comprehensive an assessment of phonological awareness used in many studies. Third, our use of standardized assessments with African-American children may underestimate their skill levels, although it is unlikely this substantially biased regression coefficients describing associations among measures of language, phonological knowledge, and reading (Neisser et al., 1996). In conclusion, these results provide further evidence linking children’s language skills to the acquisition of reading skills. Our results and previous work suggest that language skills may play two roles in reading acquisition. During the initial acquisition of reading skills, language skills at entry to school provide the skills needed to acquire phonological skills. Both language and phonological skills are necessary for learning decoding, the first skill needed for reading. Once children acquire sufficient decoding skills to be Table 5 Major conclusions ! Both language skills and phonological knowledge are directly related to the acquisition of reading skills. ! The relationship between language and reading changes over time, with language becoming a stronger predictor of reading skills by 2nd grade and phonological knowledge being a stronger predictor when children are beginning to read. ! Programs that ensure African-American children have access to high quality child care or responsive, stimulating care at home are likely to improve reading skills and reduce the black–white achievement gap at entry to school.

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reading to understand, language skills provide the skills needed for reading comprehension (Table 5). These findings, along with findings from previous studies, suggest that both language and phonological skills are important for children to become successful readers and may provide further evidence that early reading interventions should focus on developing both skills.

Acknowledgements This research was supported by grants from the Maternal and Child Health Program (Grants MCJ-370599, MCJ-370649, 1 R40 MC 00343, and R01-DC03817) Health Resources and Services Administration of the U.S. Department of Health and Human Services, National Institute of Health (Grant 01 R01-CD03817-01A1), and the Spencer Foundation. We are grateful to Susan Zeisel, Sandra Jackson, Anne Taylor, Sarah Henderson, and Eloise Neebe for their assistance in collecting and processing data and especially to the families and child care centers for their participation. Send correspondence to Michele D. Poe, Frank Porter Graham Child Development Institute, Sheryl Mar Bldg., CB#8185, University of North Carolina, Chapel Hill, NC, 27599-8185.

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