Development of emergent literacy and early reading skills in preschool

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  • 1. Copyright 2000 by the American Psychological Association, Inc. 0012-1649/00/S5.00 DOI: 10.1037//OOI2-1649.36.5.596 Developmental Psychology 2000, Vol. 36, No. 5, 596-613 Development of Emergent Literacy and Early Reading Skills in Preschool Children: Evidence From a Latent-Variable Longitudinal Study Christopher J. Lonigan, Stephen R. Burgess, and Jason L. Anthony Florida State University Although research has identified oral language, print knowledge, and phonological sensitivity as important emergent literacy skills for the development of reading, few studies have examined the relations between these aspects of emergent literacy or between these skills during preschool and during later reading. This study examined the joint and unique predictive significance of emergent literacy skills for both later emergent literacy skills and reading in two samples of preschoolers. Ninety-six children (mean age = 41 months, SD = 9.41) were followed from early to late preschool, and 97 children (mean age = 60 months, SD = 5.41) were followed from late preschool to kindergarten or first grade. Structural equation modeling revealed significant developmental continuity of these skills, particularly for letter knowledge and phonological sensitivity from late preschool to early grade school, both of which were the only unique predictors of decoding. in three children experience significant difficulties in learning to read (Adams, 1990). There is strong continuity between the skills with which children enter school and their later academic performance. Those children who do experience early difficulties in learning to read are likely to continue to experience reading problems throughout the school years (Baydar, Brooks-Gunn, & Furstenberg, 1993; Felton, 1998; Stevenson & Newman, 1986; Tramontana, Hooper, & Selzer, 1988) and into adulthood (Bruck, 1998). For instance, Juel (1988) reported that the probability that children would remain poor readers at the end of the fourth grade if they were poor readers at the end of the first grade was .88. Children who enter school with limited reading-related skills are at high risk of qualifying for special education services. In fact, the majority of school-age children referred for special education evaluation are referred because of unsatisfactory progress in reading (Lentz, 1988). Reading skills provide a crucial piece of the foundation for children's academic success. Children who read early and well experience more print exposure and consequent growth in numerous knowledge domains (Cunningham & Stanovich, 1997; Echols, West, Stanovich, & Zehr, 1996; Morrison, Smith, & DowEhrensberger, 1995). In contrast, children who lag behind in their reading skills receive less practice in reading than other children do (Allington, 1984), miss opportunities to develop reading comprehension strategies (Brown, Palincsar, & Purcell, 1986), often encounter reading material that is too advanced for their skills (Allington, 1984), and may acquire negative attitudes about reading itself (Oka & Paris, 1986). Such processes may lead to what Stanovich (e.g., 1986) termed a Matthew effect, in which poor reading skills impede learning in other academic areas (Chall, Jacobs, & Baldwin, 1990), which increasingly depend on reading across the school years. Although the development of skilled reading occurs without significant problems for the majority of children, an estimated one Whereas more traditional approaches to the study of reading often take as their starting point children's entry into the formal school environment, an emergent literacy approach conceptualizes the acquisition of literacy as a developmental continuum with its origins early in the life of a child, rather than as an all-or-none phenomenon that begins when children start school. An emergent literacy approach departs from other perspectives on reading acquisition in suggesting that there is no clear demarcation between reading and prereading. Emergent literacy consists of the skills, knowledge, and attitudes that are presumed to be developmental precursors to conventional forms of reading and writing (Sulzby & Teale, 1991; Teale & Sulzby, 1986; Whitehurst & Lonigan, 1998), and thus it suggests that significant sources of individual differences in children's later reading skills are present prior to school entry. Previous research has identified a number of potentially important components of emergent literacy. Whitehurst and Lonigan (1998) recently outlined different components of emergent literacy skills and identified three factors that appear to be associated with preschool children's later word-decoding abilities: oral language, phonological processing abilities, and print knowledge. Christopher J. Lonigan, Stephen R. Burgess, and Jason L. Anthony, Department of Psychology, Florida State University. Stephen R. Burgess is now at the Department of Psychology, Southwestern Oklahoma State University. Preparation of this article was supported, in part, by grants from the National Institute of Child Health and Human Development (HD36067, HD36509) and the Administration for Children and Families (90-YF0023); the views expressed herein are the authors' and have not been cleared by the grantors. We wish to acknowledge the contributions of the child-care centers, the directors, and the personnel who assisted with this project as well as the children and parents who made it possible. We thank Sarah Dyer, Brenlee Bloomfield, Crystal Carr, Tracy Ferguson, Kimberly Ingram, Danielle Karlau, Nikki Sutton, Emily Shock, and other students at Florida State University for their assistance with data collection. Correspondence concerning this article should be addressed to Christopher J. Lonigan, Department of Psychology, Florida State University, Tallahassee Florida 32306-1270. Electronic mail may be sent to lonigan@psy.fsu.edu. 596
  • 2. EMERGENT LITERACY AND EARLY READING Reading is a process of translating visual codes into meaningful language. In the earliest stages, reading in an alphabetic system involves decoding letters into corresponding sounds and linking those sounds to single words. A substantial body of research has demonstrated positive correlations and longitudinal continuity between individual differences in oral language skills and later differences in reading (e.g., Bishop & Adams, 1990; Butler, Marsh, Sheppard, & Sheppard, 1985; Pikulski & Tobin, 1989; Scarborough. 1989; Share, Jorm, MacLean, & Mathews, 1984). Whereas the connection between oral language and reading is clear for reading comprehension (e.g., Snow, Barnes, Chandler, Hernphill, & Goodman, 1991), some studies indicate that vocabulary skills also have a significant impact on decoding skills very early in the process of learning to read (e.g., Wagner et al.. 1997). Additionally, oral language appears to be related to a second emergent literacy skill, phonological sensitivity, as defined below. Studies of both preschool (e.g., Burgess & Lonigan, 1998; Chaney, 1992; Lonigan, Burgess, Anthony, & Barker, 1998) and early elementary school children (e.g., Bowey, 1994; Wagner, Torgesen, Laughon, Simmons, & Rashotte, 1993; Wagner et al., 1997) have demonstrated significant concurrent and longitudinal correlations between children's vocabulary skills and their phonological sensitivity. Phonological sensitivity refers to sensitivity to and ability to manipulate the sound structure of oral language. Research with a variety of populations and using diverse methods has converged on the finding that phonological sensitivity plays a critical and causal role in the normal acquisition of reading (e.g., Adams, 1990; Byrne & Fielding-Bamsley. 1991; Slanovich, 1992; Wagner & Torgesen, 1987). Children who are better at detecting and manipulating syllables, rhymes, or phonemes are quicker to learn to read, and this relation is present even after variability in reading skill owing to factors such as IQ, receptive vocabulary, memory skills, and social class is partialed out (e.g., Bryant, MacLean, Bradley, & Crossland, 19%; Wagner & Torgesen, 1987; Wagner, Torgesen, & Rashotte, 1994). Moreover, studies of disabled and poor readers indicate that there is a core phonological deficit in nearly all poor readers regardless of whether their reading abilities are consistent or inconsistent with their general cognitive abilities (Stanovich, 1988; Stanovich & Siegel, 1994; Torgesen, 1999). In addition to oral language and phonological sensitivity, aspects of children's print knowledge seem to be important emergent literacy skills. For example, knowledge of the alphabet (i.e., knowing the names of letters and the sounds they represent) at entry into school is one of the strongest single predictors of short- and long-term success in learning to read (e.g., Adams, 1990; Stevenson & Newman, 1986). Understanding the conventions of print (e.g., left-to-right and top-to-bottom orientation of print, the difference between pictures and print on a page; Clay, 1979a, 1979b) and the functions of print (e.g., that the print tells a story or gives directions; Purcell-Gates, 1996; Purcell-Gates & Dahl, 1991) also appears to aid in the process of learning to read. For example, Tunmer, Herriman, and Nesdale (1988) found that children's scores on Clay's (1979a) Concepts About Print (CAP) Test at the beginning of first grade predicted their reading comprehension and decoding abilities at the end of second grade even after Tunmer et al. controlled for differences in vocabulary and metalinguistic awareness. Some emergent literacy advocates have also suggested that children's faculty with environmental print (e.g., recognizing 597 product names from signs and logos) reflects their early print awareness by demonstrating the ability to derive the meaning of text within context (e.g., Goodman, 1986). Despite some evidence for associations between emergent literacy and later reading, there have been relatively few studies examining the relations between these multidimensional aspects of emergent literacy or between these components during the preschool period and later reading skills. As noted above, aspects of oral language appear to be related to phonological sensitivity. Children's letter knowledge also appears to be associated with some aspects of phonological sensitivity (Bowey, 1994; Stahl & Murray, 1994) and growth in these skills (Burgess &. Lonigan, 1998; Wagner et al., 1994, 1997). Evidence from school-age children indicates that these three components of emergent literacy are causally related to each other and to later reading (e.g., Wagner et al., 1997); however, how they relate to each other during the preschool period is not known. Consequently, it is not clear whether there are interactions between these different emergent literacy skills or whether they are relatively independent of one another, and thus a well-elaborated developmental model of preschool emergent literacy and its relation to conventional literacy cannot be advanced. Moreover, basic questions concerning the nature of preschool phonological sensitivity currently remain unanswered, as discussed below. The majority of evidence linking phonological sensitivity in prereaders with the development of reading has come from studies that have assessed phonological skills at the point of school entry but prior to formal reading instruction (e.g., Bradley & Bryant, 1983, 1985; Share et al., 1984; Stanovich, Cunningham, & Cramer, 1984; Wagner etal., 1994, 1997). Compared with research on school-age children's phonological sensitivity, there has been significantly less systematic study of preschool children's phonological sensitivity, and many of these studies have been limited by small sample sizes, use of only one or two measures of phonological sensitivity, and other methodological weaknesses. In one of the more extensive studies to date, MacLean, Bryant, and Bradley (1987) administered a rhyme detection task and a knowledge-of-nursery-rhymes task to a group of 66 three-year-old children. When the children were 4'/2 years old, their ability to read 12 simple high-frequency words was assessed. Compared with nonreaders, children who could read some of these words scored higher on the earlier rhyme and alliteration measures. Bryant et al. (1990) reported additional data on these children, who completed additional rhyme and alliteration detection tasks when they were about 4'/i years old, phoneme deletion and phoneme tapping tasks when they averaged about 6 years of age, and reading and spelling tests when they averaged about 6V2 years of age. Bryant et al. found that the rhyme and alliteration detection tests that had been administered when the children were AV2 were correlated with the later phoneme deletion and phoneme tapping tasks (average r = .48), and scores on these rhyme and alliteration tasks significantly added to the prediction of reading and spelling scores independent of mothers' educational level, child age, IQ, receptive vocabulary, and the score on either the phoneme deletion or phoneme tapping tasks. Evidence suggests that there is a developmental hierarchy of children's sensitivity to linguistic units at different levels of complexity. Children achieve syllabic sensitivity earlier than they achieve sensitivity to phonemes, and children's sensitivity to in-
  • 3. 598 LONIGAN, BURGESS, AND ANTHONY trasyllabic units (i.e., onset-rime) also precedes sensitivity to phonemes (Fox & Routh, 1975; I. Liberman, Shankweiler, Fischer, & Carter, 1974; Lonigan et al., 1998; Treiman, 1992). However, there is controversy concerning whether sensitivity to lower levels of linguistic complexity (i.e., syllables, onset-rime) represents processes important for reading. Sensitivity to phonemes is often assumed to have special status in the relation between phonological sensitivity and reading both because it is at this level that graphemes correspond to speech sounds in reading and because individual phonemes do not have separable physical reality (e.g., A. Liberman, Cooper, Shankweiler, & Studdert-Kennedy, 1967; Morais, 1991; Muter, Hulme, Snowling, & Taylor, 1997; Nation & Hulme, 1997; Tunmer & Rohl, 1991). Other authors have suggested that children's abilities to detect rhyme facilitate reading through a mechanism different than sensitivity to phonemes (e.g., Goswami & Bryant, 1990, 1992). Both of these views, however, assume that there is more than one type of phonological sensitivity and that the different types may be more or less related to reading. Most extant studies compared the ability of different phonological sensitivity measures (e.g., measures of rhyme vs. phonemic sensitivity) to predict reading. In these studies, when one measure of phonological sensitivity predicts reading better—typically defined as a significant semi-partial correlation obtained while controlling for the other measure of phonological sensitivity—the results are taken as supporting the crucial importance of the skill supposedly measured by that task (e.g., phonemic sensitivity). For example, in support of the importance of phonemic sensitivity, both Muter et al. (1997) and Nation and Hulme (1997) reported that children's abilities to perform a phoneme segmentation task were more strongly related to reading and spelling than were their abilities to detect and produce rhyme. Goswami and Bryant (1992) also reported data consistent with separate domains of phonological sensitivity. In their study, when they controlled for phonemic sensitivity, rhyming abilities facilitated children's abilities to make use of analogy in reading unfamiliar words. There are several problems with this predictive approach. First, it assumes a priori that there are different types of phonological sensitivity. Second, it ignores the fact that the most predictive element in such studies is the overlap between measures (i.e., the degree of shared predictive variance is substantially larger than the degree of unique predictive variance for a given test). Finally, these types of analyses fail to take into account the effects of differential reliability of the measures. That is, the more reliable of two variables measuring equally predictive constructs (or the same construct) generally will capture the unique predictive variance. Prior to examining differential predictive validity, therefore, it is important that we determine whether there is more than one type of phonological sensitivity. Extant evidence suggests that sensitivity to onset-rimes, syllables, and phonemes represents the same underlying ability. For example, Stahl and Murray (1994) administered to 113 kindergarten and first-grade children four different tasks varying in linguistic complexity. Separate factor analyses of the four tasks across linguistic complexity and of the four levels of linguistic complexity across tasks each yielded a single-factor solution that explained a majority of the variance in children's performance on the measures. Using confirmatory factor analysis, Anthony et al. (2000) found that a single factor provided the best fit to preschool children's scores on measures of rhyme, syllable, and phoneme sensitivity (see also Anthony & Lonigan, 2000). In contrast to these findings, however, Hoien, Lundberg, Stanovich, and Bjaalid (1995) reported evidence for the distinction between sensitivity to phonemes and sensitivity to rhyme and syllables. They found separate factors for phonemic sensitivity, syllabic sensitivity, and rhyme sensitivity in 6- and 8-year-old Norwegian children, and scores on all three factors independently predicted reading abilities for the older group of children. However, it is difficult to interpret the results of Hoein et al. because only one task defined the Rhyme Sensitivity and Syllabic Sensitivity factors. Several predictive studies also support a unitary view of phonological sensitivity. For example, Lonigan et al. (1998) demonstrated that preschool children's performance on tasks measuring phonological sensitivity at the syllable, onset-rime, and phoneme levels was associated with measures of letter knowledge and decoding. Similarly, studies of school-age children by Wagner and colleagues (Wagner et al., 1993, 1994, 1997) found that a latent variable defined by rhyme, syllable-level, and phoneme-level tasks was associated strongly, concurrently, and longitudinally with children's reading skills. These findings indicate that the variance common to phonological sensitivity tasks measuring different levels of linguistic complexity represents the predictive aspect of the phonological sensitivity construct. However, the majority of predictive studies have involved either school-age children or relatively small samples. Consequently, little is known about the nature and predictive importance of preschool children's developing phonological sensitivity. Questions concerning the nature of preschool phonological sensitivity (i.e., whether it is a unitary or a multidimensional construct), the independence of phonological sensitivity, oral language, and print knowledge, as well as the significance of these three components of emergent literacy for later reading are important because studies demonstrate that there are highly stable individual differences in these abilities from kindergarten forward (Wagner et al., 1994, 1997). Such findings suggest that the preschool period is an important source of development in skills associated with later reading. Our goals in this study were to examine the nature of preschool emergent literacy as well as the joint and unique predictive significance of preschool emergent literacy skills for later reading. We examined the development of emergent literacy and early reading longitudinally in two samples of preschool children who overlapped in age at different assessment points and in the measures they completed. We used structural equation modeling to address questions about the nature of preschool phonological sensitivity, the independence of different emergent literacy skills, and the developmental significance of these skills across time from the early preschool period to kindergarten and first grade. Method Participants Data from two groups of preschool-age children, recruited through 13 different preschools and child-care centers serving middle- to upper-
  • 4. EMERGENT LITERACY AND EARLY READING income families, were used in this study.1 One group of children consisted of 96 younger preschoolers who completed follow-up testing (i.e., Time 2) approximately 18 months after their initial (i.e., Time 1) assessments. These children ranged in age from 25 to 61 months (M = 41.02 months, SD = 9.41) at Time 1. The majority of the younger group of children were White (89.6%), and 56.3% were girls. The second group of children consisted of 97 older preschoolers who completed follow-up tests (i.e., Time 2) approximately 12 months after their initial (i.e., Time 1) testing. This group of children ranged in age from 48 to 64 months (M = 60.04 months, SD = 5.41) at Time 1. Most of the older group of children were White (96.9%), and 52.6% were girls. Only children who had completed all measures at both Time 1 and Time 2 were included in these samples. An additional 58 children (18 from the older sample) who had incomplete data on measures at Time 1 or Time 2 either because they refused continued participation or because they could not be located for the Time 2 testing were excluded from the results reported in this study. With the exception that excluded children in the younger sample scored lower on the rhyme oddity task (p = .04), excluded children did not differ from included children on any measure. These two samples of children originally were recruited for separate but related research projects, and there was substantial overlap in the primary measures administered in each project. The grouping used in this study maintained the original division between samples because of the different follow-up periods associated with each and the commonality of measures administered at each assessment within a sample. Information concerning children's family and home literacy experiences obtained on a majority of participants (85%) revealed that the samples were similar to each other on these variables. English was the primary language spoken in the home for all children, and fewer than three mothers or three fathers reported that English was not their native language. Mothers and fathers of children in both samples had completed on average 16 years of education (in both samples over 70% of mothers and over 63% of fathers were college graduates). Parents reported a significant number of children's books in the home for both the younger (M = 89.47, SD = 67.5) and older (M = 137.75, SD = 92.9) samples. Children in both samples were reported to be read to frequently at home (younger sample, M = 6.69 times per week, SD = 3.22; older sample, M = 5.71, SD = 2.35), and shared reading had started early for children in both the younger (M = 6.37 months, SD = 6.18) and older (M = 7.33 months, SD = 4.48) samples. Preschool and Child-Care Centers Although we did not conduct formal observations of the centers, our multiple opportunities for observation allowed us to identify salient features of their educational environments. There was significant variability between centers in terms of materials available to the children and activity structure. Generally, the curriculum in the centers was designed to foster social and interpersonal skill growth and to introduce the children to a variety of educationally relevant concepts such as letters, numbers, and storybooks. We never observed any explicit attempts to teach the children to read in any center. Some of the centers had at least some letter knowledge instruction, but most of this was informal. A number of directors commented that they discouraged explicit teaching. The centers had similar daily activity schedules, including free play, storytime, and smallgroup arts and crafts projects. Each of the centers incorporated some teacher-directed classroom activities (typically arts and crafts); however, the majority of children's time was spent in self-directed activities in and out of the classroom. Procedures and Measures After parents provided informed consent for their children to participate, trained research assistants tested children individually in their centers. Test administration for individual children was conducted over two to four 599 sessions within a 2-3-week period to ensure optimal performance on all tasks. Children in the younger sample completed four standardized tests of oral language, four tests of phonological sensitivity, and two tests of nonverbal cognitive ability during Time 1 testing, and they completed four tests of phonological sensitivity, two tests of letter knowledge, an environmental print task, and a print concepts task during Time 2 testing. Children in the older sample completed one test of oral language, four tests of phonological sensitivity, two tests of letter knowledge, an environmental print task, and a print concepts task during Time 1 testing, and they completed four tests of phonological sensitivity, two tests of letter knowledge, a print concepts task, and two text decoding tasks during Time 2 testing. Phonological sensitivity measures. Each of the four phonological sensitivity tasks was preceded by practice trials to teach children the task (e.g., blending or deleting word sounds). For all tasks, corrective feedback was given during the practice trials, but no feedback was given during the test trials. Many items on the phonological sensitivity tasks used pictures to reduce memory demands on the children. Except as noted below, tasks administered at Time 1 and Time 2 and to younger and older children included the same items. Previous analyses of these four tasks indicated that they had moderate to high internal consistencies for 4-year-olds (as = .47 to .96) and 5-year-olds (as = .69 to .94) but lower internal consistencies for 2- and 3-year-olds (see Lonigan et al., 1998). A rhyme oddity detection task and an alliteration oddity detection task, patterned after the tasks developed by MacLean et al. (1987) and using their word lists, required children to demonstrate awareness of rhyme or awareness of singleton word onsets. In both tasks, children were presented with three pictured words (e.g., boat, sail, nail; car, cat, sun), which were named by the examiner, and were asked to select the one that did not rhyme with (or that sounded different from) or did not sound the same at the beginning of the word as (or that sounded different at the beginning of the word from) the other two words. Two practice trials and 11 test trials were presented to all children. A blending task required children to combine word elements to form a word. Three practice items and the first eight test trials were presented both verbally and with pictures; the remaining test trials were presented verbally only. In both picture and nonpicture trials, the first five items required blending single-syllable words to form compound words, and the remaining items required blending syllables or phonemes. For picture items involving compound words, the examiner showed the child two pictures, named them, and then asked the child what word would be produced if he or she said them together (e.g., "What do you get when you say cow . . . boy together?"). All practice items required the blending of compound words, and during the practice the examiner emphasized the nature of the task by putting the pictures together. For the Time 1 assessment of the older sample and both Time 1 and Time 2 assessments of the younger sample, there were 18 test trials, consisting of 10 word-blending items, 4 syllableblending items, and 4 phoneme-blending items. At the Time 2 assessment of the older children, there were 37 test trials, consisting of all of the Time 1 items followed by 3 additional syllable-blending items and 16 additional phoneme-blending items. These additional syllable and phoneme items were included in the older children's Time 2 assessment to reduce the chances of children's scoring at ceiling levels. During both assessments, testing was discontinued after a child missed 5 consecutive trials. An elision task required children to say a word minus a specific sound. Two practice items and the first eight test trials were presented both 1 These children represent a subset of the children from middle-income families included in Lonigan et al. (1998). The results reported previously concerned age- and SES-related performance differences in phonological sensitivity tasks from the children's initial assessment (i.e., Time 1 in the present study).
  • 5. 600 LONIGAN, BURGESS, AND ANTHONY verbally and with pictures; the remaining test trials were presented verbally only. In both picture and nonpicture trials, the first four items required deleting a single-syllable word from a compound word to form a new word. Subsequent items in both picture and nonpicture trials required deletion of a syllable or a phoneme from a word to form a new word. For picture items involving compound words, the examiner showed the child two pictures, named them (e.g., "This is a bat, and this is a man."), asked the child to say the compound (i.e., "batman"), and then asked the child to delete part of it. During both practice trials, which used compound words, the examiner emphasized the nature of the task by removing the picture of the word to be deleted. For the Time 1 assessment of the older children and both Time 1 and Time 2 assessments of the younger children, there were 17 test trials, consisting of 10 word-level items, 4 syllable-level items, and 3 phoneme-level items. At the Time 2 assessment of the older children, there were 34 test trials, consisting of all of the Time 1 items followed by an additional 17 phoneme-level items. These additional phoneme items were included in the older children's Time 2 assessment to reduce the chances of children's scoring at ceiling levels. During both assessments, testing was discontinued after a child missed 5 consecutive trials. Oral language and cognitive ability measures. At Time 1, children in the younger sample completed four standardized tests of oral language. Receptive vocabulary was assessed with the Peabody Picture Vocabulary Tests—Revised (PPVT-R; Dunn & Dunn, 1981). Expressive vocabulary was assessed with the Expressive One-Word Picture Vocabulary Test— Revised (EOWPVT-R; Gardner, 1990). The Verbal Expression subtest of the Illinois Test of Psycholinguistic Abilities (ITPA-VE; Kirk, McCarthy, & Kirk, 1968) was used to assess children's descriptive use of language, and the Grammatical Closure subtest of the Illinois Test of Psycholinguistic Abilities (ITPA-GC; Kirk et al., 1968) was used to assess children's expressive grammar. At Time 1 for the older children, oral language was assessed with the ITPA-GC. In addition to these oral language measures, children in the younger sample completed the Picture Completion and Object Assembly subtests from the Wechsler Preschool and Primary Scales of Intelligence—Revised (Wechsler, 1989) at Time 1. Letter knowledge measures. For the Time 2 assessment of the younger sample and both Time 1 and Time 2 assessments of the older sample, two tasks assessed different aspects of letter knowledge. A letter-name knowledge task required children to name all 26 uppercase letters that were presented individually in random order on individual 3 X 5 in. index cards. A letter-sound knowledge task required children to name the sound made by each letter when it appeared in a word. All 26 uppercase letters were presented individually in random order on individual 3 X 5 in. index cards. If children responded with the letter name or a word that started with the letter (e.g., "dog" for D), they were prompted to provide the letter sound; however, credit for a correct response was given if children provided the long vowel sound for vowels. Environmental print measures. The older sample at Time 1 and the younger sample at Time 2 completed an environmental print task. On this task, children were shown 11 pictures of print in environmental context (e.g., a stop sign, a Coke machine, a McDonald's sign) and were asked what each said. Children were also shown the same print as printed text out of context and were asked what it said. Print concepts measure. At Time 2 for the younger sample and at both Time 1 and Time 2 for the older sample, portions of Clay's (1979a) CAP test (the"Sand" task) were used to assess the children's print knowledge. Items in this test require children to demonstrate understanding of the left-to-right and top-to-bottom direction of print in a book, the sequence and direction in which print progresses from front to back across pages, the difference between the covers and the pages of a book, the difference between pictures and print on a page, and the meaning of elements of punctuation, including spaces between words and periods at the ends of sentences. Word decoding measures. At Time 2, children in the older sample completed the Word Identification subtest of the Woodcock Reading Mastery Test—Revised (Woodcock, 1987) and a task requiring them to decode 25 frequent words printed individually on 3 X 5 in. index cards. Results Descriptive Statistics and Preliminary Analyses Separate scores for word, syllable, and phoneme items on the blending and elision tasks were computed. Descriptive statistics for raw scores on all variables for the younger sample at both Time 1 and Time 2 are shown in Table 1. Descriptive statistics for raw scores on all variables for the older sample at both Time 1 and Time 2 are shown in Table 2. The tables also list the internal consistency reliabilities for the eight phonological sensitivity scores at both assessments; with a few exceptions, these reliabilities were at least moderate. Analyses of variance (ANOVAs) revealed that the older sample scored substantially higher than the younger sample on the phonological sensitivity measures at Time 1 (all ps < .001). For all tasks that were the same between Time 1 and Time 2 assessments (i.e., all phonological sensitivity tasks for the younger sample and the letter knowledge and wordlevel phonological sensitivity tasks for the older sample), withinsubject ANOVAs revealed that there was significant growth from Time 1 to Time 2 (all ps < .001). Standardized scores for both samples were computed by regressing chronological age onto the raw score for each variable within sample and time of assessment (i.e., Time 1 and Time 2) to remove statistically the reliable variance that was due to children's chronological age from the scores on the observed variables. Inspection of the distribution of scores for each variable revealed some moderate departures from normality (i.e., skew) but no obvious outliers. Further inspection revealed that positive skew for the younger children's Time 1 scores was due to a moderate number of children scoring at low levels on the blending and elision tasks, whereas negative skew for the older children's scores was due to a moderate number of children scoring at high levels on the word blending, word elision, and letter knowledge tasks. Although these distributions accurately reflect task difficulty for the age ranges included in the samples, the use of nonnormal data may attenuate relations among variables and compromise model fits; consequently, we conducted confirmatory factor analysis (CFA) using robust maximum-likelihood estimation, the Satorra-Bentler scaled chi-square (S-B;^2), and adjustments to the standard errors to account for nonnormality in model fit statistics and significance testing (Bentler & Dudgeon, 1996). Evaluation of Measurement Models We conducted separate CFAs using EQS (Bentler, 1995) to evaluate measurement models for both samples at Time 1 and Time 2. All CFAs were conducted on covariance matrices. Prior to evaluating the adequacy of measurement models that included all emergent literacy tasks, we evaluated the adequacy of a one-factor model to explain scores on the phonological sensitivity tasks at each measurement period for both samples. In all models, task variance for the different phonological sensitivity tasks was modeled by allowing correlated residuals between similar tasks (i.e., parameter estimates for covariances between error terms for the two oddity tasks, three blending tasks, and three elision tasks were
  • 6. 601 EMERGENT LITERACY AND EARLY READING Table 1 Descriptive Statistics for Younger Sample of Children at Time 1 and Time 2 Assessments Time 1 Variable M SD Age (in months) Rhyme oddity Alliteration oddity Blending words Blending syllables Blending phonemes Elision words Elision syllables Elision phonemes PPVT-R (MA) EOWPVT-R (MA) ITPA-VE (MA) ITPA-GC (MA) WPSSI Object Assembly WPSSI Picture Completion Letter names Letter sounds Concepts About Print Test Environmental print: pictures Environmental print: text 41.05 4.54 3.45 2.57 0.68 0.25 1.77 0.43 0.22 42.54 42.71 48.54 45.48 12.40 10.48 — — — — — 9.36 2.00 1.81 4.47 1.35 0.62 2.77 0.95 0.70 11.60 12.90 13.09 14.87 5.31 6.77 — — — — — Time 2 a .30 .18 .97 .90 .52 .91 .79 .86 M SD a 57.56 6.93 5.55 7.30 1.51 1.31 5.73 1.95 1.12 — — — — — — 14.51 6.84 7.26 5.22 0.97 10.09 2.52 2.66 5.88 1.34 1.48 3.83 1.59 1.20 .90 .85 .98 .89 .87 .96 .88 .85 — — — — — 10.06 8.32 3.32 2.69 2.13 Note. N = 96. All means are for raw scores unless otherwise noted. Internal consistency reliabilities (alphas) are provided only for phonological sensitivity measures. Dashes indicate tasks not administered at an assessment period. PPVT-R = Peabody Picture Vocabulary Test—Revised; MA = mental age score; EOWPVT-R = Expressive One-Word Picture Vocabulary Test—Revised; ITPA-VE = Verbal Expression subscale of the Illinois Test of Psycholinguistic Abilities; ITPA-GC = Grammatical Closure subtest of the Illinois Test of Psycholinguistic Abilities; WPPSI = Wechsler Preschool and Primary Scales of Intelligence. specified in the models).2 For the younger sample at Time 1, S-B^CB, N = 96) = 13.15, p > .25, RCF1 (robust comparative fit index) = 1.00, and Time 2, S-Bx^B.iV = 96) = 5.23,p > .25, RCFI = 1.00, and for the older sample at Time 1, S-Bx^B, N = 97) = 17.89, p > .10, RCFI = .98, and Time 2, S - B ^ D , N = 97) = 10.78, p > .25, RCFI = 1.00, a one-factor model provided an excellent fit to the data. Following these analyses, different one-, two-, and three-factor measurement models that included all emergent literacy tasks were compared in the younger and older samples at the Time 1 and Time 2 assessments. Younger sample. Fit indices for the different measurement models for the younger sample of children are shown in Table 3. For the Time 1 assessment (upper half of Table 3), the fits of models that included different combinations of phonological sensitivity, oral language, and nonverbal IQ measures were compared. A three-factor model with separate Phonological Sensitivity, Oral Language, and Nonverbal IQ factors provided a significantly better fit than all of the alternative models (all ps < .01 for chi-square difference tests) except the model with the phonological sensitivity and oral language measures represented by one factor. The difference (diff) between the three-factor model and this two-factor model was only marginally significant, ^ iff <2, N = 96) = 4.09, p = .11; however, examination of the other fit indices (Bentler & Bonett, 1980; see Table 3) and factor loadings, which indicated that the majority of phonological sensitivity tasks did not load significantly on the factor, supported the superiority of the threefactor model. For the younger sample's Time 2 assessment (see lower half of Table 3), the fits of models that included different combinations of phonological sensitivity, letter knowledge, and environmental print measures were compared. These models also included the CAP test as a separate measured variable. A three-factor model that included different Phonological Sensitivity, Letter Knowledge, and Environmental Print factors provided a significantly better fit than the one-factor model, XdiffC5- N - 96) = 49.34, p < .001, a two-factor model with phonological sensitivity and letter knowledge measures represented by a single factor, Xdiff(3, N = 96) = 42.07, p < .001, and a two-factor model with phonological sensitivity and environmental print measures represented by a single factor, *jjiff(3, N = 96) = 39.12, p < .001. The two-factor model with letter knowledge and environmental print measures represented by a single factor was not significantly different from the three-factor model (p > .10); however, when the CAP measure was excluded from the model, the three-factor model provided a better fit to the data, xjiiff(2, N = 96) = 6.40, p < .05, supporting the use of three separate factors to represent phonological sensitivity, letter knowledge, and environmental print. Older sample. Fit indices for the different measurement models for the older sample of children are shown in Table 4. For the Time 1 assessment (see upper half of Table 4), the fits of models 2 The structure of all measurement and longitudinal models was identical whether or not these correlated residuals were included in the models; however, model fits were improved when correlated residuals were included because they accounted for significant covariance between items that was due to similar task methods (e.g., blending vs. deleting word sounds) or other sources of systematic variance.
  • 7. 602 LONIGAN, BURGESS, AND ANTHONY Table 2 Descriptive Statistics for Older Sample of Children at Time 1 and Time 2 Assessments Time 1 Time 2 Variable M SD a Age (in months) Rhyme oddity Alliteration oddity Blending words Blending syllables Blending phonemes Elision words Elision syllables Elision phonemes Letter names Letter sounds Concepts About Print Test Environmental print: pictures Environmental print: text ITPA-GC (MA) Decoding frequent words WRM Word ID 60.04 6.49 5.46 7.73 2.70 1.78 5.59 2.13 1.14 20.02 9.09 7.63 5.73 0.97 68.64 — — 5.41 2.75 2.64 2.95 1.39 1.40 2.37 1.43 1.06 7.37 8.91 3.32 2.17 1.91 16.22 — — SD 72.88 8.89 8.73 9.44 10.16 6.96 7.56 2.32 6.42 24.72 20.45 11.41 — — 5.71 2.13 2.42 1.16 2.70 3.65 0.69 0.97 3.87 3.68 6.68 1.70 — 11.98 14.32 .71 .68 .93 .69 .67 .80 .70 .57 M 8.46 12.12 a .71 .80 .75 .61 .90 .50 .44 .88 Note. N = 97. All means are for raw scores unless otherwise noted. Internal consistency reliabilities (alphas) are provided only for phonological sensitivity measures. Dashes indicate tasks not administered at an assessment period. ITPA-GC = Grammatical Closure subtest of the Illinois Test of Psycholinguistic Abilities; MA = mental age score; WRM Word ID = Word Identification subtest of the Woodcock Reading Mastery Test—Revised. that included different combinations of phonological sensitivity, letter knowledge, and environmental print measures were compared. These models also included the CAP test as a separate measured variable. Both chi-square difference tests and evaluation of the other fit indices indicated that a three-factor model that included separate Phonological Sensitivity, Letter Knowledge, and Environmental Print factors provided a significantly better fit than the one-factor model, ^ i f f ( 5 , N = 97) = 32.49, p < .001, a two-factor model with phonological sensitivity and letter knowledge measures represented by a single factor, )&i{f(3, N = 97) = 10.89, p < .05, a two-factor model with phonological sensitivity and environmental print measures represented by a single factor, Xdiff(3, N = 97) = 24.39, p < .001, and a two-factor model with letter knowledge and environmental print measures represented by a single factor, Xdiff(3, N = 97) = 18.91, p < .001, supporting the use of three separate factors to represent phonological sensitivity, letter knowledge, and environmental print. Table 3 Fit Indices for Measurement Models for Younger Sample at Time 1 and Time 2 Assessments Model (and factors) S-B*2 df CFI RCFI TLI RMSEA AIC .91 .94 .82 .91 .95 .85 .88 .82 .90 .92 .10 .09 .11 .08 .07 -9.57 -18.20 3.74 -29.98 -36.14 .88 .89 .90 .96 .96 .84 .84 .85 .94 .94 .11 .11 .11 .07 .07 7.44 5.25 2.51 -32.85 -32.26 Time 1 Assessment 1-factor 2-factor 2-factor 2-factor 3-factor (PS + OL + IQ) (PS + OL, IQ) (PS + IQ, OL) (PS, OL + IQ) (PS, OL, IQ) 102.70** 89.82* 130.77*** 99.43** 85.73 70 69 69 69 67 .89 .91 .86 .93 .94 Time 2 Assessment 1-factor 2-factor 2-factor 2-factor 3-factor (PS + LK + EP) (PS + LK, EP) (PS + EP, LK) (PS, LK + EP) (PS, LK, EP) 123.05*** 115.78*** 112.83*** 80.45* 73.71* 58 56 56 56 53 .88 .89 .90 .96 .96 Note. All models include correlated residuals between like phonological sensitivity tasks. All models of Time 2 assessment include scores on the Concepts About Print Test as a measured variable. N = 96. PS = Phonological Sensitivity; OL = Oral Language; IQ = Nonverbal IQ; LK = Letter Knowledge; EP = Environmental Print; S-B^2 = Satorra-Bentler chi-square; CFI = comparative fit index; RCFI = robust comparative fit index; TLI = Tucker-Lewis index; RMSEA = root mean square error of approximation; AIC = Akaike information criterion. *p<.05. **p<.0l. ***/><.001.
  • 8. EMERGENT LITERACY AND EARLY READING 603 Table 4 Fit Indices for Measurement Models for Older Sample at Time 1 and Time 2 Assessments Model (and factors) S-B*2 df CFI RCFI TLI RMSEA AIC .86 .91 .87 .89 .92 .82 .88 .84 .85 .90 .10 .09 .10 .09 .08 -0.34 -18.16 -4.68 -10.24 -22.76 .90 .97 .95 .95 1.00 .86 .95 .93 .92 1.00 .10 .06 .07 .07 .02 -6.59 -36.89 -30.50 -28.19 -51.38 Time 1 Assessment 1-factor 2-factor 2-factor 2-factor 3-factor (PS + LK, EP) (PS + EP, LK) (PS, LK + EP) (PS, LK, EP) 117.15*** 95.55*** 109.05*** 103.57*** 84.66** 58 56 56 56 53 .87 .91 .88 .89 .93 Time 2 Assessment 1-factor 2-factor 2-factor 2-factor 3-factor (PS + LK + RD) (PS + LK, RD) (PS + RD, LK) (PS, LK + RD) (PS, LK, RD) 103.00*** 69.08 79.18* 77.09* 51.50 58 56 56 56 53 .90 .96 .95 .95 1.00 Note. All models include scores on the Concepts About Print Test as a measured variable and correlated residuals between like phonological sensitivity tasks. N = 97. PS = Phonological Sensitivity; LK = Letter Knowledge; EP = Environmental Print; RD = Word Reading (decoding); S-B^2 = Satorra-Bentler chi-square; CFI = comparative fit index; RCFI = robust comparative fit index; TLI = Tucker-Lewis index; RMSEA = root mean square error of approximation; AIC = Akaike information criterion. * p < . 0 5 . **p<. 01. ***/><.001. For the older sample's Time 2 assessment (see lower half of Table 4), the fits of models that included different combinations of phonological sensitivity, letter knowledge, and text decoding were compared. These models also included the CAP test as a separate measured variable. Both chi-square difference tests and evaluation of the other fit indices indicated that a three-factor model that included different Phonological Sensitivity, Letter Knowledge, and Reading (Decoding) factors provided a significantly better fit than the one-factor model, ^ i f f ( 5 , N = 97) = 51.50, p < .001, a two-factor model with phonological sensitivity and letter knowledge measures represented by a single factor, Xaiff(3, N = 97) = 17.58, p < .001, a two-factor model with phonological sensitivity and decoding measures represented by a single factor, x3iff(3, N = 97) = 27.68, p < .001, and a two-factor model with letter knowledge and decoding measures represented by a single factor, ^ i f f ( 3 , N = 97) = 25.59, p < .001, supporting the use of three separate factors to represent phonological sensitivity, letter knowledge, and text decoding. Sample comparisons. To facilitate comparisons between younger and older samples and to allow preliminary hypotheses concerning the development of reading-related skills across the age range covered by both samples (i.e., continuity between the younger sample's Time 1 assessment and the older sample's Time 2 assessment), we compared raw scores and measurement models for the emergent literacy measures from the younger children at the Time 2 assessment with those from the older children at the Time 1 assessment. ANOVA revealed that children in the younger sample at Time 2 were somewhat younger than children in the older sample at Time 1, F(l, 191) = 4.54, p = .03. ANOVAs on children's raw scores also revealed that children in the younger sample at Time 2 scored lower on letter knowledge, F(l, 191) = 18.86, p < .001, syllable blending, F(l, 191) = 36.87, p < .001, and phoneme blending, F(l, 191) = 5.18, p = .02, than did children in the older sample at Time 1 (see Table 1 and Table 2 for descriptive statistics). Differences on phoneme blending were rendered nonsignificant in an analysis of covariance controlling for chronological age (p = .16); however, the differences for letter knowledge and syllable blending remained significant (ps < .001).3 Multisample CFA was carried out on the data from the younger children's Time 2 data and the older children's Time 1 data to examine structural invariance of the three-factor measurement model across samples (see Table 5). A multisample model with separate Phonological Sensitivity, Letter Knowledge, and Environmental Print factors, with the CAP test as a separate measured variable and with none of the parameters across groups constrained to equality, served as a basis for testing whether adding constraints to the model across groups would yield a significantly worse fit. A significant change in the chi-square when factor loadings were constrained across groups suggested there was a statistically significant lack of invariance. However, fit indices that are more robust to sample size supported the invariance of factor loadings, factor correlations (including correlations with the CAP measure), and correlated residuals. The comparative fit index (CFI), TuckerLewis Index (TLI), root mean square error of approximation (RMSEA), and Akaike information criterion (AIC) remained essentially unchanged when these invariance constraints were imposed, and the imposition of all of these constraints did not result in a significant reduction in the overall model chi-square from the unconstrained model, ^ i f f (25, N = 193) = 32.79, p > .10. Consequently, the majority of fit indices indicated that the slight lack of invariance noted for the factor loadings was of little 3 These significant differences may have been the result of the age range of the younger group. That is, the youngest child in the older sample was 60 months old, whereas the youngest child in the younger sample was 38 months old. Alternatively, these differences may have been a function of the different preschool environments of the younger and older samples.
  • 9. 604 LONIGAN, BURGESS, AND ANTHONY Table 5 Fit Indices for Multisample Analysis of Three-Factor Measurement Model for Younger Sample at Time 2 and Older Sample at Time 1 Model constraints x2 df CFI TLI RMSEA AIC Xdiff df None (unconstrained) Factor loadings Factor loadings and factor correlations Factor loadings, factor correlations, and correlated residuals Factor loadings, factor correlations, correlated residuals, and residual variances 156.98*** 176.89*** 106 118 .95 .94 .92 .92 .05 .05 -55.02 -59.11 19.91* 10 185.34*** 124 .94 .92 .05 -62.66 8.45 6 189.77*** 131 .94 .93 .05 -72.23 4.43 7 221.87*** 143 .92 .91 .05 -64.13 32.10** 12 Note. All models include scores on the Concepts About Print Test as a measured variable and correlated residuals between like phonological sensitivity tasks. Chi-square difference tests reflect comparison of a model with the previous model and thus reflect the change associated with the addition of the specified constraint. N = 193. CFI = comparative fit index; TLI = Tucker-Lewis index; RMSEA = root mean square error of approximation; AIC = Akaike information criterion. * p < . 0 5 . ** p < . 01. ***/?<.001. practical importance and was outweighed by the large gain in parsimony. In contrast, all fit indices decreased substantially when item residuals were constrained. Thus, the results indicated that the measurement model explained children's emergent literacy skills well across both the younger and older samples of children (i.e., the factor structure was equivalent) but that there may have been systematic sample differences in measurement errors that were of little substantive interest to the present study. Longitudinal Prediction Models Structural equation modeling in EQS was used to examine the longitudinal relations between emergent literacy and either later emergent literacy skills (younger sample) or both later emergent literacy skills and text decoding (older sample). The measurement models identified in the previous analyses served as the basis for the longitudinal models. We first calculated the cross-time zeroorder correlations between latent constructs. Because our interest was in identifying significant sources of influence on children's development, we began by examining models that included autoregressive paths (i.e., paths between the same factors at different time points). Inclusion of other paths was guided by results from analyses of zero-order correlations as well as theoretical considerations. Modifications to these base models were made by examining the results of both (a) Lagrange multiplier (LM) tests, to determine the value of adding parameters to the models that would significantly increase the model fit at the p < .05 level, and (b) Wald tests, to determine the statistical necessity of parameters whose elimination would not significantly decrease the model fit at the/? > .10 level. Younger sample. Zero-order correlations between the latent variables at Time 1 and the latent variables at Time 2 for the younger sample of children are shown in the upper half of Table 6. For the younger sample of children, the base longitudinal prediction model included paths from the Phonological Sensitivity factor at Time 1 to the Phonological Sensitivity and Letter Knowledge factors at Time 2. Paths from the Time 1 Oral Language factor to the Time 2 Phonological Sensitivity factor, the Time 2 Letter Knowledge factor, the Time 2 Environmental Print factor, and the Time 2 CAP variable also were included in the model. Finally, a path from the Nonverbal IQ factor to the Time 2 CAP variable was included. On the basis of Wald tests, we dropped the paths from the Time 1 Phonological Sensitivity factor to the Time 2 Phonological Sensitivity factor, from the Time 1 Oral Language factor to the Time 2 Environmental Print factor, and from the Time 1 Noverbal IQ factor to the Time 2 CAP variable. On the basis of LM tests, we added paths from the Time 2 Letter Knowledge factor to the Time 2 Phonological Sensitivity factor, the Time 2 Environmental Print factor, and the Time 2 CAP variable. The resultant model for the younger sample is shown in Figure 1, S-B^2(305, N = 96) = 383.05, p < .01, RCFI = .93, RMSEA = .06. Time 2 Phonological Sensitivity was significantly predicted by Oral Language at Time 1 and Letter Knowledge at Time 2 (R2 = .25). Letter Knowledge was significantly predicted by both Time 1 Phonological Sensitivity and Time 1 Oral Language (R2 = .20). Environmental Print was significantly predicted by Time 2 Letter Knowledge only (R2 = .45). Finally, scores on the CAP measure at Time 2 were significantly predicted by both Time 1 Oral Language and Time 2 Letter Knowledge (R2 = .23). Because the absence of significant cross-time stability in the Phonological Sensitivity factor suggested a problem with the measurement of phonological sensitivity at Time 1 for the younger sample, we examined a model with a Time 1 Phonological Sensitivity factor that included only those tasks with significant crosstime stability (syllable blending and all three elision measures). Evaluation of the measurement model supported three separate factors to represent Phonological Sensitivity, Oral Language, and Nonverbal Cognitive Abilities, S-B^2 (30, N = 96) = 28.83, p = .53, RCFI = 1.00. There was a significant cross-time correlation between this reduced Phonological Sensitivity factor and the Time 2 Phonological Sensitivity factor (r = .35, p < .01). We examined the full longitudinal model starting with the same base
  • 10. EMERGENT LITERACY AND EARLY READING 605 Table 6 Zero-Order Correlations Between Time I Emergent Literacy Skills and Time 2 Emergent Literacy and Reading Skills for Younger and Older Samples Time 2 variables Time 1 variables Phonological sensitivity Letter knowledge Environmental print Concepts About Print .23 .33** .19 .14 37*** .32* Reading .60*** .51** .51*** .40*** 44*** .18 .37** .62*** Younger sample Phonological sensitivity Oral language Nonverbal cognitive .14 .36*** .16 .33** .39*** .15 Older sample Phonological sensitivity Environmental print Letter knowledge Concepts About Print Test 1.00*** .59*** .64*** .60*** .48*** .42*** .80*** .35*** Note. Correlations are between latent variables for each construct, except for the Concepts About Print Test, which is a measured variable. * p < . 0 5 . **/><.01. ***/?<.001. model described previously. The resultant final model is shown in Figure 2, S-B^(212, N = 96) = 265.74, p < .01, RCFI = .94, RMSEA = .06. In this modified model, the reduced Time 1 Phonological Sensitivity factor was significantly related to Oral Language. Time 2 Phonological Sensitivity was significantly predicted by both Phonological Sensitivity and Oral Language at Time 1 (R2 = .17). Letter Knowledge was significantly predicted by both Time 2 Phonological Sensitivity and Time 1 Oral Language (R2 = .26). Environmental Print was significantly predicted by Time 2 Letter Knowledge only (R2 = .49). Finally, scores on the CAP measure at Time 2 were significantly predicted by both Time 1 Oral Language and Time 2 Phonological Sensitivity (R2 = .20). Older sample. Zero-order correlations between the latent variables at Time 1 and the latent variables at Time 2 for the older sample of children are shown in the lower half of Table 6. For the older sample of children, the base longitudinal prediction model included paths from the Time 2 Phonological Sensitivity and Letter Knowledge factors to the Reading factor, from the Time 1 Phonological Sensitivity factor to the Time 2 Phonological Sensitivity and the Time 2 Letter Knowledge factors, from the Time 1 Letter Knowledge factor to the Time 2 Letter Knowledge and Phonological Sensitivity factors, and from the Time 1 CAP measure to the Time 2 CAP measure.4 The paths between the Time 1 Phonological Sensitivity factor and the Time 2 Letter Knowledge factor and between the Time 1 Letter Knowledge factor and the Time 2 Phonological Sensitivity factor were dropped on the basis of Wald tests. On the basis of LM tests, a path between the Time 1 Phonological Sensitivity factor and the Time 2 CAP variable was added. The resultant model for the older sample is shown in Figure 3, S-B^2(276, N = 91) = 428.18, p < .001, RCFT = .87, RMSEA = .08. Time 2 Phonological Sensitivity was perfectly predicted by Phonological Sensitivity at Time 1 (R2 = 1.00). Time 2 Letter Knowledge was predicted by Time 1 Letter Knowledge only (R2 = .72). Scores on the CAP measure at Time 2 were predicted by scores on the Time 1 CAP measure and Time 1 Phonological Sensitivity (R2 = .44). Finally, Time 2 Phonological Sensitivity and Time 2 Letter Knowledge were the only significant predictors of reading (R2 = .54). 56 As would be expected from the results of the Wald and LM tests, when paths between the Time 1 Environmental Print factor, the Time 2 CAP measure, and the Reading factor were included in this model, these paths were not significant, indicating that neither the Environmental Print factor nor the CAP measure added unique variance to the Reading factor once the Phonological Sensitivity and Letter Knowledge factors were in the model. To confirm these findings and to ensure that our model development strategy was not biased against finding significant effects on reading for the environmental print and print concepts measures, we conducted model testing starting with a base model that included just the autoregressive paths and paths from both the Time 1 Environmental Print factor and the Time 2 CAP variable to the Time 2 Reading factor. The resultant final model following Wald and LM tests was the model shown in Figure 3, with the exception that the path between Time 2 Letter Knowledge and 4 The identical final model was obtained when the base model included paths for all of the Time 1 variables with significant zero-order associations with Time 2 variables. 5 As would be expected given the high correlations between the Time 1 and the Time 2 Phonological Sensitivity and Letter Knowledge factors, when the Time 1 Phonological Sensitivity and Letter Knowledge factors were used to predict the Reading Factor at Time 2, they also accounted for 54% of the variance in decoding. 6 We also tested the unique variance associated with each of the blending and elision measures by adding (in separate sequential models) a path from each measure's residual to the Reading factor. In none of these models was there an improvement in model fit or increment in the R2 for the Reading factor. These results suggest that, in these data, it was the variance common to the eight phonological sensitivity measures that was predictive of decoding rather than the variance unique to the manipulation of phonemes, syllables, or words.
  • 11. 606 LONIGAN, BURGESS, AND ANTHONY -.61 .48 Figure 1. Structural equation model of longitudinal relations between emergent literacy abilities for younger sample of children. Circles represent latent variables, and rectangles represent observed variables. Variables on the left of the figure are from the Time 1 (Tl) assessment (mean age = 41.1 months, SD = 9.4); variables on the right of the figure represent Time 2 (T2; mean age = 57.6 months, SD = 10.1), reflecting development over an 18-month period. All paths shown as solid lines are significant at p < .05. Wrd = word-level items, Syl = syllable-level items, Phon = phoneme-level items, Ltr = letter; Env = environmental; Pics = pictures; CAP = Concepts About Print Test; PPVT-R = Peabody Picture Vocabulary Tests—Revised; EOWPVT-R = Expressive One-Word Picture Vocabulary Test—Revised; ITPA-VE = Verbal Expression subtest of the Illinois Test of Psycholinguistic Abilities; ITPA-GC = Grammatical Closure subtest of the ITPA; PicComplet and ObjAssem = Picture Completion and Object Assembly subtests of the Wechsler Preschool and Primary Scales of Intelligence—Revised. Reading was not included. An additional model examined the influence of ITPA-GC scores on the Time 2 factors. In this model, ITPA-GC scores were not a significant predictor of any Time 2 factor and did not alter the significance of the paths shown in Figure 3. Finally, we also examined the independence of phonological sensitivity from oral language by regressing ITPA-GC scores from both reading measures. In this analysis, both the Phonological Sensitivity and Letter Knowledge factors continued to be significant and substantial predictors of the Reading factor (R2 = .39). Discussion The results of this study demonstrate that the developmental origins of a large component of children's reading skills in kin- dergarten and first grade can be found in the preschool period. A number of the emergent literacy skills present during the preschool period (i.e., phonological sensitivity, letter knowledge) reflect highly stable individual differences and have substantial unique predictive relations with later reading abilities. Together, phonological sensitivity and letter knowledge accounted for 54% of the variance in kindergarten and first-grade children's decoding abilities. In contrast, other emergent literacy skills, such as environmental print and print concepts, although present during the preschool period and relatively stable, do not appear to be uniquely important for children's later reading. Taken together, these results highlight the developmental continuity between emergent literacy and later reading from the early preschool period to the early elementary school period. Additionally, these results provide im-
  • 12. 607 EMERGENT LITERACY AND EARLY READING Blend Syl -.40 jElision W r d i * ^ -.16 -.39 " - ^Elision Syl -.25' Vision Phog PicComplet« ObjAssem -,g ..98. CAP 2. Structural equation model of longitudinal relations between emergent literacy abilities for younger sample of children including modified Phonological Sensitivity factor for Time 1 assessment. Time 1 measures included in the modified Phonological Sensitivity factor were those with significant cross-time stability. Circles represent latent variables, and rectangles represent observed variables. Variables on the left of the figure are from Time 1 (Tl) assessment (mean age = 41.1 months, SD = 9.4); variables on the right of the figure represent Time 2 (T2; mean age = 57.6 months, SD = 10.1), reflecting development over an 18-month period. All paths shown as solid lines are significant at p < .06. Wrd = word-level items, Syl = syllable-level items, Phon = phoneme-level items, Ltr = letter; Env = environmental; Pics = pictures; CAP = Concepts About Print Test; PPVT-R = Peabody Picture Vocabulary Tests—Revised; EOWPVT-R = Expressive One-Word Picture Vocabulary Test—Revised; ITPA-VE = Verbal Expression subtest of the Illinois Test of Psycholinguistic Abilities; ITPA-GC = Grammatical Closure subtest of the ITPA; PicComplet and ObjAssem = Picture Completion and Object Assembly subtests of the Wechsler Preschool and Primary Scales of Intelligence— Revised. portant information concerning issues of the development and the measurement of several key emergent literacy skills. Perhaps the most striking finding from the present study concerned the high level of stability in children's phonological sensitivity. The latent variable representing the phonological sensitivity of 5-year-old children attending preschool perfectly predicted the latent variable representing phonological sensitivity of 6-year-old children attending kindergarten and first grade. These results indicate that there was no change in the ordering or spacing of children's performance from preschool to kindergarten and first grade despite the fact that there was significant growth in these skills (see Table 2). These findings are similar to those found with older children by Wagner and colleagues (Wagner et al., 1994, 1997). For example, Wagner et al. (1997) reported that year-toyear stability coefficients for their latent phonological sensitivity variable ranged from .83 (kindergarten to first grade) to .95 (second grade to third grade and third grade to fourth grade). Our results indicate that this high degree of stability is present earlier in development and is not the result of formal reading instruction. In contrast to the extraordinary stability of phonological sensitivity from late preschool to early elementary school, phonological sensitivity was less stable from early preschool to late preschool. In fact, very early phonological sensitivity, represented by all eight measures of the construct we administered, was not a strong or
  • 13. 608 LONIGAN, BURGESS, AND ANTHONY Rhyme 26 ^—^Alliteration L .57 Figure 3. Structural equation model of longitudinal relations between emergent literacy abilities and reading for older sample of children. Circles represent latent variables, and rectangles represent observed variables. Variables on the left of the figure are from Time 1 (Tl) assessment (mean age = 60.4 months, SD = 5.4); variables on the right of the figure represent Time 2 (T2; mean age = 72.9 months, SD = 5.7), reflecting development over a 13-month period. All paths shown as solid lines are significant atp < .05. Wrd = word-level items, Syl = syllable-level items, Phon = phoneme-level items, Ltr = letter; Env = environmental; Pic = pictures; CAP = Concepts About Print Test; ID = identification; Freq = frequent. unique predictor of phonological sensitivity in the late preschool period. There was some developmental continuity between this early phonological sensitivity construct and later phonological sensitivity; however, this continuity appeared to be mediated by later letter knowledge, which was a significant concurrent predictor of phonological sensitivity. These results indicate that there were problems with the measures of phonological sensitivity for the early preschool group. That is, whatever variance was shared across all eight measures in the early preschool period was not phonological sensitivity. Based on the longitudinal empirical relations of this factor, it is possible that the shared variance represented letter knowledge or a proxy measure of print exposure. When we examined the longitudinal relations of a reduced Phonological Sensitivity factor that included only Time 1 measures with significant cross-time stability, there was evidence for developmental continuity of the Phonological Sensitivity factor from early to late preschool. Interestingly, the variables that defined this reduced factor were mainly those with weak relations to the factor defined by all eight measures, indicating that the variance shared between these four variables, and hence the construct represented, was distinct from that included in the original factor. Taken together, the results from these two models are similar to the results from other studies of young children that have found a predictive relation between phonological sensitivity and later letter knowledge (Burgess & Lonigan, 1998; Wagner et al., 1994) and between letter knowledge and both current and subsequent phonological sensitivity (Bowey, 1994; Burgess & Lonigan, 1998; Johnston, Anderson, & Holligan, 1996; Stahl & Murray, 1994; Wagner et al., 1994, 1997). The mechanisms by which phonological sensitivity influences the development of letter knowledge and letter knowledge influences the development of phonological sensitivity are not clear. It is possible that the development of these
  • 14. EMERGENT LITERACY AND EARLY READING skills simply indexes exposure to literacy-related activities. Alternatively, it is possible that children with greater sensitivity to the phonological structure of words and more letter knowledge may benefit more from the formal and informal exposure to print that many preschoolers receive (e.g., Lonigan, 1994; Whitehurst & Lonigan, 1998). Perhaps the ability to discriminate word and syllable boundaries makes the significance of letters more transparent. Similarly, understanding the significance of letters may facilitate the segmentation of language. In addition to the effects of letter knowledge on phonological sensitivity, oral language had direct and indirect effects (depending on the model) on phonological sensitivity in the late preschool period. This finding is consistent with results from a number of other studies of both preschool (e.g., Burgess & Lonigan, 1998; Chaney, 1992; Lonigan et al., 1998) and early elementary school children (e.g., Bowey, 1994; Wagner et al., 1993, 1997) that have demonstrated significant concurrent and longitudinal correlations between children's vocabulary skills and their phonological processing skills. These results suggest that oral language development has an influence on the acquisition of this key emergent literacy skill. Past studies of preschool children have suggested that productive phonology (i.e., speech intelligibility) is related to performance on phonological sensitivity tasks (e.g., Webster & Plante, 1995). As discussed by Metsala and Walley (1998; see also Fowler, 1991), this evidence suggests that lexical representations become more segmental in early childhood as a result of vocabulary growth. The emergence of phonological sensitivity may be limited by these speech representations. Despite direct and indirect effects of early oral language and phonological sensitivity skills, all measured factors accounted for only 17% to 25% of the variance in phonological sensitivity measured in the late preschool period. Although these results indicate that children's phonological sensitivity in the late preschool period is partially a function of early phonological sensitivity, oral language skills, and letter knowledge, they highlight the fact that the origins of the majority of children's reading-related phonological sensitivity are unknown. Like the results of our earlier cross-sectional study (Lonigan et al., 1998), these findings indicate that significant growth in phonological sensitivity occurs between 3 and 4 years of age. Consequently, efforts to identify the origins of phonological sensitivity are likely to be most productive during this period. Our results also suggest, however, that screening of children for phonological sensitivity deficits is unlikely to be productive prior to the late preschool period, at least with the present measures because of their limited predictive power for later phonological sensitivity. The results of this study are also informative concerning the nature of preschool phonological sensitivity. As noted previously, phonemic sensitivity is often given special status in relation to reading, with a number of authors arguing that phonemic sensitivity is the critical influence on reading skills (e.g., Morais, 1991; Muter et al., 1997; Nation & Hulme, 1997; Tunmer & Rohl, 1991). In contrast, we have argued elsewhere (Anthony & Lonigan, 2000; Anthony et al., 2000; Lonigan et al., 1998) that it is children's general sensitivity to the sound structure of language that is important for learning to read an alphabetic system. Our finding that children's phonological sensitivity, broadly defined (i.e., sensitivity to words, syllables, onset-rime, and phonemes), was best characterized as a unitary construct at each of the four assessments of 609 children across different ages provides strong support for this position. Even in the reduced factor for the younger children's Time 1 assessment, Phonological Sensitivity was represented by sensitivity to words, syllables, and phonemes. Across analyses from the late preschool and early grade school periods, only one index of phonological sensitivity did not have a significant association with the phonological sensitivity construct. The wordblending measure did not contribute to the latent variable at the Time 2 assessment for the older group. This effect was likely due to the fact that scores on the word-blending measure for the older children were at near ceiling levels. Regardless, this same analysis demonstrated that word-level and syllable-level blending were associated with manipulation of phonemes (i.e., alliteration, phoneme blending, phoneme elision), which supports the broadly defined phonological sensitivity construct. Two additional aspects of our results support the importance of the broader construct of phonological sensitivity. First, whereas the measures of phonological sensitivity for the younger group's Time 1 and Time 2 assessments and for the older group's Time 1 assessment were weighted heavily in favor of lower levels of linguistic complexity (i.e., words, syllables, onset-rime), the measures of phonological sensitivity for the older children's Time 2 assessment were weighted heavily in favor of higher levels of linguistic complexity (i.e., phonemes). The fact that the earlier Phonological Sensitivity factor perfectly predicted the later Phonological Sensitivity factor for the older group of children indicates that sensitivity to lower and higher levels of linguistic complexity represents a continuum rather than distinct abilities. These findings are consistent with the results obtained by Stahl and Murray (1994), who found that a single-factor solution explained a majority of the variance in kindergarten children's performance on four tasks that varied by linguistic complexity. Finally, the global construct of phonological sensitivity, defined by variance common to sensitivity to words, syllables, onset-rime, and phonemes, was a significant and strong predictor of children's decoding skills. This finding demonstrates that this global phonological sensitivity, rather than just phonemic sensitivity, is influential in the development of children's decoding skills. Moreover, like other studies (e.g., Bryant et al., 1990; Lonigan et al., 1998; MacLean et al., 1987; Wagner et al., 1994, 1997), our analyses demonstrated that this relation was not the result of variance shared between the global construct of phonological sensitivity and oral language. That is, the predictive relation between the global construct of phonological sensitivity and reading is not the result of children with more developed oral language skills, such as vocabulary, or general cognitive abilities simply having greater faculty with tasks assessing broad levels of phonological sensitivity and also having better decoding skills. It is important to note, however, that our assessment of oral language skills in the older sample was limited to a single measure. It is possible that other oral language measures may have shared more predictive variance with both decoding and phonological sensitivity. However, given the independence of these constructs demonstrated in the younger sample and the significant loading of the ITPA-GC on the broader Oral Language factor, it seems unlikely that additional oral language measures would have substantially weakened the strong relation between phonological sensitivity and decoding. Whereas a number of previous studies have interpreted findings that one measure of phonological sensitivity (e.g., phoneme seg-
  • 15. 610 LONIGAN, BURGESS, AND ANTHONY mentation) predicts reading better than another (e.g., onset-rime sensitivity) to indicate that one type of phonological sensitivity is more important to reading than another (Goswami & Bryant, 1990, 1992; Muter et al., 1997; Nation & Hulme, 1997), these analyses make the explicit or implicit assumption that there are different types of phonological sensitivity. Our results, as well as the results of other large studies (e.g., Wagner et al., 1993, 1994, 1997), demonstrate that such assumptions are incorrect, at least as explanations of the normal development of reading. That is, our analyses of different tasks that varied in linguistic complexity, which indicated that a single-factor solution provided an excellent fit to the data, established that these tasks tap the same underlying ability, phonological sensitivity. Moreover, this single factor predicted a majority of the variance in later decoding skills. These results are consistent with those of Wagner and colleagues and Stahl and Murray (1994) in demonstrating that phonological sensitivity is a unitary construct represented by sensitivity to onsetrimes, syllables, and phonemes and in showing that the variance common to children's abilities to perform tasks requiring sensitivity to onset-rime, syllables, and phonemes is a substantial predictor of decoding skills. Our results indicated that, like phonological sensitivity from late preschool to early grade school, letter knowledge was a very stable individual difference, and at every assessment, letter knowledge represented an emergent literacy skill that was independent of phonological sensitivity, environmental print, and decoding. Letter knowledge in the late preschool period, indexed by knowledge of both letter names and letter sounds, predicted 72% of the variance in kindergarten and first-grade children's letter knowledge. Moreover, this level of stability was likely attenuated because of the near-ceiling performance of the older children on both the measure of letter name knowledge and the measure of letter sound knowledge at the Time 2 assessment (see Table 2). Another significant finding of our study was that measures of variables that have been the focus of traditional emergent literacy approaches (i.e., print concepts, environmental print) had no unique predictive relation to later reading skills or other later emergent literacy skills. Some emergent literacy advocates have argued that children's faculty with environmental print demonstrates their ability to derive the meaning of text within context (e.g., Goodman, 1986); however, other research has not generally supported a direct causal link between the ability to read environmental print and later decoding skills (Gough, 1993; Masonheimer, Drum, & Ehri, 1984). Although these variables were associated with later reading and later emergent literacy when considered in isolation (see Table 6), they were not significant unique predictors in the context of letter knowledge and phonological sensitivity. Concepts of print and environmental print might reflect very early knowledge of literacy; however, our analyses demonstrated that measures of environmental print reflected a construct that was distinct from letter knowledge and phonological sensitivity. The fact that both the environmental print variable and the CAP variable were predicted by phonological sensitivity and letter knowledge suggests that they may best be conceptualized as proxy measures for these other emergent literacy skills, reflect more exposure to print and other literacy-related activities (e.g., see Purcell-Gates, 1996), or both. Two limitations to the conclusions that can be made concerning print concepts in this study are that we had only a single indicator of the construct and that we did not administer the measure to the younger children at Time 1. Consequently, we were unable to represent it as a latent variable, and we could not estimate its influence on the development of other emergent literacy skills from the early to the late preschool period. Although future studies should address these limitations, our findings indicate that what is measured by print concepts that is independent of letter knowledge and phonological sensitivity is unrelated to early decoding abilities. Our analyses revealed that both the measurement models and the scores obtained by both groups of children during the late preschool period were nearly identical. Consequently, these findings provide a preliminary means of examining the developmental continuity of emergent literacy and early reading skills from early preschool to early grade school. This cross-sample analysis highlights the significance of individual differences in both oral language and phonological sensitivity. That is, individual differences in oral language skills, such as vocabulary, appear to be an important influence on later emergent literacy skills that are crucial components for children's development of decoding skills (i.e., phonological sensitivity and letter knowledge). Individual differences in phonological sensitivity measured at an early age also appear to have a significant influence on these key emergent literacy skills that is independent of oral language abilities. Despite these significant findings, a number of caveats concerning this study are required. Although the samples used in this study were larger than those used in most prior studies of preschool emergent literacy (e.g., Bryant et al., 1990; Chaney, 1992; Fox & Routh, 1975; Maclean et al., 1987), they were marginally adequate for structural equation modeling. The broad age range in the younger sample of children may have obscured potentially important relations between some emergent literacy variables. For instance, it may be that greater stability in phonological sensitivity emerges at an earlier age but was not apparent because of the age range of our younger sample. Additionally, our reliance on different samples of children to explore the developmental continuity of emergent literacy from early preschool to kindergarten and first grade was not optimal. Although results of multisample analyses indicated that scores on the measures and the measurement models were nearly identical across both groups during the late preschool period, indicating that interpretations across samples were justified, conclusions derived from the same sample would be stronger. Importantly, it is unlikely that our main findings concerning the significant relations between emergent literacy skills within and between assessment phases were the result of the age range of children within the samples because all analyses were conducted using scores from which the reliable variance associated with children's chronological age was statistically removed. However, these results provide a preliminary examination of how these different emergent literacy skills relate to each other from the early preschool period to kindergarten and first grade. Not all domains of emergent literacy were measured in this study (Whitehurst & Lonigan, 1998). For instance, some writers have suggested that the constructs of emergent reading or emergent writing reflect children's developing conceptualizations of literacy (e.g., Pappas & Brown, 1988; Purcell-Gates, 1988; Sulzby, 1985, 1986, 1988). Although we believe that these skills are likely to be related to concepts of print and understanding of narratives, and therefore either reflect dimensions similar to letter knowledge and phonological sensitivity or relate more strongly to reading
  • 16. EMERGENT LITERACY AND EARLY READING comprehension rather than to decoding (Whitehurst & Lonigan, 1998), future studies should address the relative independence and specific influences of these emergent literacy skills. In addition to phonological sensitivity, components of phonological processing, such as phonological memory and phonological naming, have been identified in older children as significant correlates of reading skills (e.g., Bowers & Wolfe, 1993; Wagner et al., 1994, 1997; Wolfe, 1991). A complete account of emergent literacy will require an understanding of the development of these skills and their significance, if any, during the preschool years. Although the results of this study highlight the developmental continuities and discontinuities in emergent literacy and the significant linkage between emergent literacy skills and later decoding, they do not address the question of the origins of these skills. Given the significant linkages found in this study, future studies should address questions concerning the developmental origins of key skills such as phonological sensitivity and letter knowledge. Such information will expand our knowledge of emergent literacy and provide clues for the development of interventions designed to help children at risk for developing later reading difficulties. Finally, our results concern the development of emergent literacy and decoding in children from English-speaking and middle-class families. Consequently, our results are most relevant to children learning to read an alphabetic language, and the degree to which these findings translate to children who may be at risk for reading difficulties because of conditions associated with poverty or because their native language is not English is unknown. In summary, the results of this study have extended previous work on the development of emergent literacy skills and early reading in several ways. First, our results highlight the developmental continuity between early preschool emergent literacy skills, later preschool emergent literacy skills, and early reading abilities of children. Second, these results clarify the nature of readingrelated phonological sensitivity. Contrary to the dominant view that it is phonemic sensitivity that is critical for decoding, our results clearly establish that it is children's global sensitivity to phonological features of language that relates to decoding. Third, this study partially explains the status of other emergent literacy skills in explanatory accounts of the development of reading. Skills such as print concepts or the ability to "read" environmental print do not appear to have independent predictive associations with later reading; rather, their predictive relations with later reading appear to reflect the development of other emergent literacy skills such as letter knowledge and phonological sensitivity. Finally, the results of this study highlight the significance of the study of the origins of preschool emergent literacy skills. The high level of stability of emergent literacy skills from late preschool to early grade school, coupled with the lower degree of stability of emergent literacy skills from early preschool to late preschool, suggests that efforts to identify significant sources of variability between children in these skills should be directed toward the preschool years. References Adams, M. J. (1990). Beginning to read: Thinking and learning about print. Cambridge, MA: MIT Press. Allington, R. L. (1984). Content, coverage, and contextual reading in reading groups. Journal of Reading Behavior, 16, 85—96. 611 Anthony, J. L., & Lonigan, C. J. (2000). The nature of phonological sensitivity: Converging evidence from four studies of preschool and early-grade school children. Manuscript submitted for publication. Anthony, J. L., Lonigan, C. J., Burgess, S. R., Driscoll Bacon, K., Phillips, B. M., & Bloomfield, B. G. (2000). Structure of preschool phonological sensitivity: Overlapping sensitivity to rhyme, words, syllables, and phonemes. Manuscript submitted for publication. Baydar, N., Brooks-Gunn, J., & Furstenberg, F. F. (1993). Early warning signs of functional illiteracy: Predictors in childhood and adolescence. Child Development, 64, 815-829. Bentler, P. M. (1995). EQS structural equations program manual. Encino, CA: Multivariate Software. Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88, 588-606. Bentler, P. M., & Dudgeon, P. (1996). Covariance structure analysis: Statistical practice, theory, and directions. Annual Review of Psychology, 47, 563-592. Bishop, D. V. M., & Adams, C. (1990). A prospective study of the relationship between specific language impairment, phonological disorders and reading retardation. Journal of Child Psychology and Psychiatry and Allied Disciplines, 31, 1027-1050. Bowers, P. G., & Wolf, M. (1993). Theoretical links among naming speed, precise timing mechanisms and orthographic skill in dyslexia. Reading & Writing, 5, 69-85. Bowey, J. A. (1994). Phonological sensitivity in novice readers and nonreaders. Journal of Experimental Child Psychology, 58, 134-159. Bradley, L., & Bryant, P. E. (1983). Categorizing sounds and learning to read—A causal connection. Nature, 301, 419-421. Bradley, L., & Bryant, P. (1985). Rhyme and reason in reading and spelling. Ann Arbor: University of Michigan Press. Brown, A. L., Palincsar, A. S., & Purcell, L. (1986). Poor readers: Teach, don't label. In U. Neisser (Ed.), The school achievement of minority children: New perspectives (pp. 105-143). Hillsdale, NJ: Erlbaum. Bruck, M. (1998). Outcomes of adults with childhood histories of dyslexia. In C. Hulme, R. Joshi, & J. Malatesha (Eds.), Reading and spelling: Development and disorders (pp. 179-200). Mahwah, NJ: Erlbaum. Bryant, P. E., MacLean, M., Bradley, L. L., & Crossland, J. (1990). Rhyme and alliteration, phoneme detection, and learning to read. Developmental Psychology, 26, 429-438. Burgess, S, R., & Lonigan, C. J. (1998). Bidirectional relations of phonological sensitivity and prereading abilities: Evidence from a preschool sample. Journal of Experimental Child Psychology, 70, 117-141. Butler, S. R., Marsh, H. W., Sheppard, M. J., & Sheppard, J. L. (1985). Seven-year longitudinal study of the early prediction of reading achievement. Journal of Educational Psychology, 77, 349-361. Byrne, B., & Fielding-Bamsley, R. F. (1991). Evaluation of a program to teach phonemic awareness to young children. Journal of Educational Psychology, 82, 805-812. Chall, J. S., Jacobs, V., & Baldwin, L. (1990). The reading crisis: Why poor children fall behind. Cambridge, MA: Harvard University Press. Chaney, C. (1992). Language development, metalinguistic skills, and print awareness in 3-year-old children. Applied Psycholinguistics, 13, 485514. Clay, M. M. (1979a). The early detection of reading difficulties (3rd ed.). Portsmouth, NH: Heinemann. Clay, M. M. (1979b). Reading: The patterning of complex behavior. Auckland, New Zealand: Heinemann. Cunningham, A. E., & Stanovich, K. E. (1997). Early reading acquisition and its relation to reading experience and ability 10 years later. Developmental Psychology, 33, 934-945. Dunn, L. M., & Dunn, L. M. (1981). Peabody Picture Vocabulary TestRevised. Circle Pines, NM: American Guidance Service. Echols, L. D., West, R. F., Stanovich, K. E., & Zehr, K. S. (1996). Using
  • 17. 612 LONIGAN, BURGESS, AND ANTHONY children's literacy activities to predict growth in verbal cognitive skills: A longitudinal investigation. Journal of Educational Psychology, 88, 296-304. Felton, R. H. (1998). The development of reading skills in poor readers: Educational implications. In C. Hulme, R. Joshi, & J. Malatesha (Eds.), Reading and spelling: Development and disorders (pp. 219-233). Mahwah, NJ: Erlbaum. Fowler, A. E. (1991). How early phonological development might set the stage for phoneme awareness. In S. A. Brady & D. P. Shankweiler (Eds.), Phonological processes in literacy (pp. 97-117). Hillsdale, NJ: Erlbaum. Fox, B., & Routh, D. K. (1975). Analyzing spoken language into words, syllables, and phonemes: A developmental study. Journal of Psycholinguistic Research, 4, 331-342. Gardner, M. F. (1990). Expressive One-Word Picture Vocabulary TestRevised. Novato, CA: Academic Therapy. Goodman, K. S. (1986). What's whole in whole language? Portsmouth, NH: Heinemann. Goswami, U., & Bryant, P. E. (1990). Phonological skills and learning to read. Hillsdale, NJ: Erlbaum. Goswami, U., & Bryant, P. E. (1992). Rhyme, analogy, and children's reading. In P. B. Gough, L. C. Ehri, & R. Treiman (Eds.), Reading acquisition (pp. 49-62). Hillsdale, NJ: Erlbaum. Gough, P. B. (1993). The beginning of decoding. Reading and Writing: An Interdisciplinary Journal, 5, 181-192. Hoien, T., Lundberg, I., Stanovich, K. E., & Bjaalid, I. (1995). Components of phonological awareness. Reading and Writing: An Interdisciplinary Journal, 7, 171-188. Johnston, R. S., Anderson, M , & Holligan, C. (1996). Knowledge of the alphabet and explicit awareness of phonemes in prereaders: The nature of the relationship. Reading and Writing: An Interdisciplinary Journal, 8, 217-234. Juel, C. (1988). Learning to read and write: A longitudinal study of 54 children, from first through fourth grades. Journal of Educational Psychology, 80, 437-447. Kirk, S. A., McCarthy, J. J., & Kirk, W. D. (1968). Illinois Test of Psycholinguistic Abilities. Urbana: University of Illinois Press. Lentz, F. E. (1988). Effective reading interventions in the regular classroom. In J. L. Graden, J. E. Zins, & M. J. Curtis (Eds.), Alternating educational delivery systems: Enhancing instructional options for all students (pp. 351-373). Washington, DC: National Association of School Psychologists. Liberman, A. M., Cooper, F. S., Shankweiler, D., & Studdert-Kennedy, M. (1967). Perception of the speech code. Psychological Review, 74, 431461. Liberman, I. Y., Shankweiler, D., Fischer, F. W., & Carter, B. (1974). Explicit syllable and phoneme segmentation in young children. Journal of Experimental Child Psychology, 18, 201-212. Lonigan, C. J. (1994). Reading to preschoolers exposed: Is the emperor really naked? Developmental Review, 14, 303-323. Lonigan, C. J., Burgess, S. R., Anthony, J. L., & Barker, T. A. (1998). Development of phonological sensitivity in two- to five-year-old children. Journal of Educational Psychology, 90, 294-311. MacLean, M., Bryant, P., & Bradley, L. (1987). Rhymes, nursery rhymes, and reading in early childhood. Merrill-Palmer Quarterly, 33, 255-282. Masonheimer, P. E., Drum, P. A., & Ehri, L. C. (1984). Does environmental print identification lead children into word reading? Journal of Reading Behavior, 16, 257-27'1. Metsala, J. L., & Walley, A. C. (1998). Spoken vocabulary growth and the segmental restructuring of lexical representations: Precursors to phonemic awareness and early reading ability. In J. L Metsala & L. C. Ehri (Eds.), Word recognition in beginning literacy (pp. 89-120). Mahwah, NJ: Erlbaum. Morais, J. (1991). Constraints on the development of phonological aware- ness. In S. A. Brady & D. P. Shankweiler (Eds.), Phonological processes in literacy (pp. 5-27). Hillsdale, NJ: Erlbaum. Morrison, F. J., Smith, L., & Dow-Ehrensberger, M. (1995). Education and cognitive development: A natural experiment. Developmental Psychology, 31, 789-799. Muter, V., Hulme, C , Snowling, M., & Taylor, S. (1997). Segmentation, not rhyming, predicts early progress in learning to read. Journal of Experimental Child Psychology, 65, 370-398. Nation, K., & Hulme, C. (1997). Phonemic segmentation, not onset-rime segmentation, predicts early reading and spelling skills. Reading Research Quarterly, 32, 154-167. Oka, E., & Paris, S. (1986). Patterns of motivation and reading skills in underachieving children. In S. Ceci (Ed.), Handbook of cognitive, social, and neuropsychological aspects of learning disabilities (Vol. 2). Hillsdale, NJ: Erlbaum. Pappas, C. C , & Brown, E. (1988). The development of children's sense of the written story language register: An analysis of the texture of "pretend reading. " Linguistics & Education, I, 45-79. Pikulski, J. J., & Tobin, A. W. (1989). Factors associated with long-term reading achievement of early readers. In S. McCormick, J. Zutell, P. Scharer, & P. O'Keefe (Eds.), Cognitive and social perspectives for literacy research and instruction. Chicago: National Reading Conference. Purcell-Gates, V. (1988). Lexical and syntactic knowledge of written narrative held by well-read-to kindergartners and second graders. Research in the Teaching of English, 22, 128-160. Purcell-Gates, V. (1996). Stories, coupons, and the TV Guide: Relationships between home literacy experiences and emergent literacy knowledge. Reading Research Quarterly, 31, 406-428. Purcell-Gates, V., & Dahl, K. L. (1991). Low-SES children's success and failure at early literacy learning in skills-based classrooms. Journal of Reading Behavior, 23, 1-34. Scarborough, H. (1989). Prediction of reading dysfunction from familial and individual differences. Journal of Educational Psychology. 81, 101-108. Share, D. L., Jorm, A. F., MacLean, R., & Mathews, R. (1984). Sources of individual differences in reading acquisition. Journal of Educational Psychology, 76, 1309-1324. Snow, C. E., Barnes, W. S., Chandler, J., Hemphill, L., & Goodman, I. F. (1991). Unfulfilled expectations: Home and school influences on literacy. Cambridge, MA: Harvard University Press. Stahl, S. A., & Murray, B. A. (1994). Defining phonological awareness and its relationship to early reading. Journal of Educational Psychology, 86, 221-234. Stanovich, K. E. (1986). Matthew effects in reading: Some consequences of individual differences in the acquisition of literacy. Reading Research Quarterly, 21, 360-407. Stanovich, K. E. (1988). Explaining the differences between the dyslexic and the garden-variety poor reader: The phonological-core variabledifference model. Journal of Learning Disabilities, 21, 590-612. Stanovich, K. E. (1992). Speculations on the causes and consequences of individual differences in early reading acquisition. In P. B. Gough, L. C. Ehri, & R. Treiman (Eds.), Reading acquisition (pp. 307-342). Hillsdale, NJ: Erlbaum. Stanovich, K. E., Cunningham, A. E., & Cramer, B. B. (1984). Assessing phonological awareness in kindergarten children: Issues of task comparability. Journal of Experimental Child Psychology, 38, 175-190. Stanovich, K. E., & Siegel, L. S. (1994). Phenotypic performance profile of children with reading disabilities: A regression-based test of the phonological-core variable-difference model. Journal of Educational Psychology, 86, 24-53. Stevenson, H. W., & Newman, R. S. (1986). Long-term prediction of achievement and attitudes in mathematics and reading. Child Development, 57, 646-659.
  • 18. 613 EMERGENT LITERACY AND EARLY READING Sulzby, E. (1985). Children's emergent reading of favorite storybooks: A developmental study. Reading Research Quarterly, 20, 458-481. Sulzby, E. (1986). Writing and reading: Signs of oral and written language organization in the young child. In W. H. Teale & E. Sulzby (Eds.), Emergent literacy: Reading and writing (pp. 50-87). Norwood, NJ: Ablex. Sulzby, E. (1988). A study of children's early reading development. In A. D. Pelligrini (Ed.), Psychological bases for early education (pp. 39-75). Chichester, England: Wiley. Sulzby, E., & Teale, W. (1991). Emergent literacy. In R. Barr, M. Kamil, P. Mosenthal, & P. D. Pearson (Eds.), Handbook of reading research (Vol. 2, pp. 727-758). New York: Longman. Teale, W. H., & Sulzby, E. (Eds.). (1986). Emergent literacy: Writing and reading. Norwood, NJ: Ablex. Torgesen, J. K. (1999). Phonologically based reading disabilities: Toward a coherent theory of one kind of learning disability. In R. J. Sternberg & L. Spear-Swerling (Eds.), Perspectives on learning disabilities (pp. 231-262). Boulder, CO: Westview Press. Tramontana, M. G., Hooper, S., & Selzer, S. C. (1988). Research on preschool prediction of later academic achievement: A review. Developmental Review, 8, 89-146. Treiman, R. (1992). The role of intrasyllabic units in learning to read and spell. In P. B. Gough, L. C. Ehri, & R. Treiman (Eds.), Reading acquisition (pp. 107-143). Hillsdale, NJ: Erlbaum. Tunmer, W. E., Herriman, M. L., & Nesdale, A. R. (1988). Metalinguistic abilities and beginning reading. Reading Research Quarterly, 23, 134-158. Tunmer, W. E., & Rohl, M. (1991). Phonological awareness and reading acquisition. In D. Sawyer & B. Fox (Eds.), Phonological awareness in reading: The evolution of current perspectives (pp. 1-29). New York: Springer-Verlag. Wagner, R. K., & Torgesen, J. K. (1987). The nature of phonological processing and its causal role in the acquisition of reading skills. Psychological Bulletin, 101, 192-212. Wagner, R. K., Torgesen, J. K., Laughon, P., Simmons, K., & Rashotte, C. A. (1993). Development of young readers' phonological processing abilities. Journal of Educational Psychology, 85, 83-103. Wagner, R. K., Torgesen, J. K., & Rashotte, C. A. (1994). The development of reading-related phonological processing abilities: New evidence of bi-directional causality from a latent variable longitudinal study. Developmental Psychology, 30, 73-87. Wagner, R. K., Torgesen, J. K., Rashotte, C. A., Hecht, S. A., Barker, T. A., Burgess, S. R., Donahue, J., & Garon, T. (1997). Changing relations between phonological processing abilities and word-level reading as children develop from beginning to skilled readers: A 5-year longitudinal study. Developmental Psychology, 33, 468-479. Webster, P. E., & Plante, A. S. (1995). Productive phonology and phonological awareness in preschool children. Applied Psycholinguistics, 16, 43-57. Wechsler, D. (1989). Wechsler Preschool and Primary Scales of Intelligence—Revised. New York: The Psychological Corporation. Whitehurst, G. J., & Lonigan, C. J. (1998). Child development and emergent literacy. Child Development, 69, 848-872. Wolfe, M. (1991). Naming speed and reading: The contribution of the cognitive neurosciences. Reading Research Quarterly, 26, 123-141. Woodcock, R. W. (1987). Woodcock Reading Mastery Tests-Revised. Circle Pines, MN: American Guidance Service. Received December 22, 1998 Revision received March 29, 2000 Accepted April 7, 2000 Call for Papers: Violent Children Developmental Psychology will publish a special issue in 2002 on the topic of Violent Children: Bridging Development, Prevention, and Policy. The problem of chronic violence in children has reached a new level of public awareness. Developmental science has much to contribute to the understanding of this problem and how it can be addressed in the public domain. This special issue will highlight original empirical research that contributes to this understanding. Three kinds of articles will be considered: those that contribute to knowledge of how chronic conduct problems or violent behaviors develop in children or adolescents, those that evaluate rigorous experiments in the prevention or treatment of chronic aggression, and those that evaluate public policies relevant to child conduct problems. Together, these articles will provide a bridge between developmental science and public policy. Inquiries should be directed to the section coeditors, Gregory S. Pettit (gpettit@auburn.edu) and Kenneth A. Dodge (kenneth.dodge@duke.edu). Manuscripts should be standard length (fewer than 40 pages) and should be submitted for standard peer review prior to October 1,2000, to the editorial office of Developmental Psychology, University of Wisconsin, Waisman Center, 1500 Highland Avenue, Madison, WI 53705-2280. Please include the phrase "Special Issue on Violent Children" in the cover letter that accompanies the submission.