From letter names to word reading: The nascent role of sublexical fluency

Contemporary Educational Psychology 31 (2006) 301–327 www.elsevier.com/locate/cedpsych

From letter names to word reading: The nascent role of sublexical fluency Kristen D. Ritchey a,*, Deborah L. Speece b a

b

School of Education, Willard Hall, University of Delaware, Newark, DE 19716, USA Department of Special Education, University of Maryland, College Park, MD 20742, USA Available online 1 December 2005

Abstract Information processing theory suggests that sublexical fluency skills are important to word reading development, but there are few supportive data. This study investigated if sublexical fluency (letter name fluency, letter sound fluency, and phoneme segmentation fluency) contributed to the development of word reading and spelling in 92 kindergarten children. The pattern of findings suggests that, as early as kindergarten, sublexical fluency skills explain a small, but significant, amount of unique variance in literacy outcomes when also considering the influence of accuracy in these skills. Also, growth in sublexical fluency skills is related to both word reading and spelling proficiency at the end of kindergarten. We suggest that knowledge of early literacy skill development may be enhanced by attention to sublexical fluency and that these skills, specifically letter sound fluency, may provide the mechanism that supports early word reading and spelling.  2005 Elsevier Inc. All rights reserved. Keywords: Fluency; Sublexical fluency; Reading and spelling development; Kindergarten; Alphabet; Phonological awareness

1. Introduction Current models of emergent literacy and reading are unified on several points. First, reading requires knowledge of the phonological and orthographic systems of English. For beginning readers, awareness of the sound structure of oral language (phonology) and knowledge of the written system of English (orthography) are important early reading *

Corresponding author. Fax: +1 302 831 4110. E-mail address: [email protected] (K.D. Ritchey).

0361-476X/$ - see front matter  2005 Elsevier Inc. All rights reserved. doi:10.1016/j.cedpsych.2005.10.001

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skills. Second, knowledge of letter-sound relationships (graphophonemes) is essential to word decoding skill. Graphophonemic and word decoding skill, in turn, are supported by some level of phonological awareness (Adams, 1990; Chall, 1983; Ehri, 1998). Phonological awareness, letter name, and letter sound knowledge are considered ‘‘sublexical’’ skills as they operate below the word level. Other sublexical units that may be important as children gain reading competence include morphemes and multi-letter units such as blends, rimes, and spelling patterns (Berninger, Abbott, Billingsley, & Nagy, 2001; Carlisle & Nomanbhoy, 1993; Compton, 2000; Levy, 2001; Wolf & Katzir-Cohen, 2001), The sublexical skills selected for this study (phonological awareness, letter name knowledge, and letter sound knowledge) are considered to be the initial building blocks for earliest efforts at decoding and spelling. Acquiring these foundational sublexical skills does not necessarily translate to reading or spelling words. Rather, they provide children with the knowledge necessary to understand and use graphophonemic associations while reading and spelling words (Byrne & Fielding-Barnsley, 1989, 1990; Ehri, 1998). The positive relationship between individual sublexical skills and word reading in beginning readers is widely acknowledged and supported by a wealth of correlational and experimental evidence (e.g., Biemeller, 1977–1978; McBride-Chang, 1999; OÕConnor & Jenkins, 1999; Perfetti, Beck, Bell, & Hughes, 1987; Schneider, Roth, & Ennemsor, 2000). Additionally, it is generally believed that letter names provide insight to the sounds of the letters and that letter name knowledge, letter sound knowledge, and phonological awareness develop in concert (Burgess & Lonigan, 1998; Ehri, 1983; Wagner, Torgesen, & Rashotte, 1994). To date, these three skills have rarely been assessed in the same study with kindergarten children at the earliest stages of reading. Thus, their interrelationships are not known. Another factor that has received little attention is the role of fluency in sublexical competence. Sublexical fluency is the speed and accuracy with which subword skills can be accessed and produced. Just as isolated knowledge of letter names, letter sounds, and phonological awareness is unlikely to promote word decoding, slow access and production of these skills also will likely hamper word decoding and spelling. The purpose of the present study is to examine the hypothesis that sublexical fluency promotes early word reading and spelling skills in kindergarten children. 1.1. The case for sublexical fluency Reading fluency is acknowledged as a critical component of skilled reading. The recent focus on reading fluency has spawned interest in the skills that support its development (National Reading Panel, 2000; Wolf, 2001). Reading fluency is typically defined as the accuracy and speed with which one can read single words in connected text (Fuchs, Fuchs, Hosp, & Jenkins, 2001; Fuchs et al., 2001). It requires accurate and quick (often described as automatic) individual word recognition, and is characterized as developmental and occurring along a continuum (National Reading Panel, 2000). Theoretically, fluent word recognition is believed important because it frees cognitive resources for comprehension activities (LaBerge & Samuels, 1974). We extrapolate from LaBerge and SamuelsÕ (1974) information processing view of word reading fluency and comprehension to suggest that fluency in sublexical skills may free cognitive resources to allow successful word decoding and spelling in young children. Novice readers initially attempt to decode by analyzing some or all of the letters in a word (Ehri, 1992, 1997). Letter-by-letter analysis of words that is marked by inefficient connec-

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tions to letter sounds taxes working memory making successful blending of the sounds into a word difficult, if not impossible. Similarly, slow segmentation of phonemes within a word and translation to graphemes hinder beginning spelling. Children who are more fluent with the building blocks of early decoding (letter names, letter sounds, and phonological awareness) should be better decoders and spellers because they can access and use the information efficiently, thereby not excessively burdening working memory with the required translation activities. Current thinking suggests that fluent word reading is the result of fluency with sublexical processes as defined in this study but the linkages among letter names, letter sounds, and phonological segmentation are not well specified (Good, Simmons, & KameÕenui, 2001; LaBerge & Samuels, 1974; Logan, 1997; Posner & Snyder, 1975; Samuels, 1976; Wolf & Katzir-Cohen, 2001). For example, Samuels and Flor (1997) stated, ‘‘reading is simply one example of the kind of higher-order skills that rely on developing certain component skills to an automatic level’’ (p. 110). Similarly, KameÕenui and Simmons (2001) stated, ‘‘fluent reading is plainly developmental and represents an outcome of well-specified sublexical and lexical processes and skills’’ (p. 204). Although there is agreement that the fluency with which sublexical skills are accessed and coordinated should assist early word decoding, there are few investigations of the above claims. Thus, there is limited knowledge of how sublexical skills develop, the relative importance of fluency for beginning word reading and spelling, and how these skills interrelate to develop word reading and spelling. There are studies that take a component view of word reading as suggested above by Samuels and Flor (1997). These studies investigated a single sublexical process but support the theoretical stance of the current investigation. Walsh, Price, and Gillingham (1988) used a discrete-trial method of assessing separately letter name accuracy and speed with kindergarten and second grade children. They found that, for the kindergarten children, speed of letter naming contributed more variance to reading skill measured one year later in first grade than did letter name accuracy. They also showed that the speed effect was specific to letters as object naming speed was not significant in predicting later reading skill. Fredericksen, Wareen, and Roseberry (1985) tested their componential theory of reading through a training study that also used a discrete-trial method. These authors, however, were concerned with fluency (accuracy and speed) although their method allowed them to separate effects. They postulated that poor decoding skills of adolescents were due, in part, to lack of automaticity with subword, multi-letter units. Extended practice in fluent recognition of the units selected for study resulted in more fluent recognition of trained and untrained units and, importantly, either improved decoding accuracy or efficiency. Other studies used a continuous-list procedure which combines accuracy and speed in a single measure. The continuous-list procedure is a common method of assessing fluency in educational contexts and has a solid psychometric base (e.g., Deno, 1985; Fuchs & Fuchs, 1999). Speece and Ritchey (2005) found that letter sound fluency measured in January of first grade uniquely predicted both growth and level of oral reading fluency in May for children at risk of reading failure. It appeared that the at-risk children were continuing to develop fluency with letter sounds as late as the second semester of first grade whereas not-at-risk children had already acquired and consolidated this knowledge. Stage, Sheppard, Davidson, and Browning (2001) demonstrated that letter name and letter sound fluency measured at the end of kindergarten predicted first grade oral reading fluency. Also, letter name fluency predicted growth in first grade oral reading fluency. In neither study were sublexical accuracy measures administered.

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One study of kindergarten children included both accuracy and fluency measures. Speece, Mills, Ritchey, and Hillman (2003) reported that letter name fluency and letter sound fluency contributed unique variance to word reading beyond that contributed by letter name and letter sound accuracy measures. In fact, the accuracy measures (including phonological awareness accuracy) were no longer significant when the fluency measures were added to the multiple regression models. This finding indicates that traditional accuracy measurement could be enhanced, if not replaced, by fluency measures. When reading skills were assessed in the spring of first grade, kindergarten letter sound fluency and phonological awareness accuracy added unique variance to pseudoword decoding accuracy and oral reading fluency. The only accuracy measure that was a unique predictor of untimed first grade word reading was phonological awareness. The kindergarten letter names and letter sounds accuracy measures were not significant in any of the first grade analyses. These results support the findings of Walsh et al. (1988) even though a different measurement procedure was used. 1.2. Developmental issues Taken together, these correlational results suggest a role for fluency in sublexical skills at the early stages of word reading development. However, the studies spanned late kindergarten to late first grade. Longitudinal studies of literacy traditionally assess literacy skills annually (e.g., Lonigan, Burgess, & Anthony, 2000; Wagner et al., 1994), providing little understanding of the amount of growth that occurs during potentially critical, albeit relatively short, periods early in a childÕs school career. It is not known when or how sublexical fluency develops. In addition, growth may be dramatic or incremental but it is important to document what can be expected within important developmental periods, such as kindergarten. Developmental information can be gleaned when growth estimates are included as variables. For example, experimental evidence summarized by Kame’enui, Simmons, Good, and Harn (2001) showed that phonemic segmentation fluency increased between January and April of kindergarten at the rate of approximately one phoneme per week and that rates of growth differentiated literacy intervention groups. They did not report if sublexical growth was related to word reading skill. Fuchs et al. (2001) demonstrated that letter sound fluency was a reliable marker of reading growth for kindergarten children participating in a randomized field trial of early reading interventions. Thus, there is reason to believe that analysis of sublexical fluency performance and growth over time may provide insights on the development of word reading and spelling skills. 1.3. Purposes of the current study During kindergarten, especially the second semester, the instructional focus is on reading development, specifically mastering letter sounds and beginning word reading (Honig, 1996; Snow, Burn, & Griffin, 1998; SRA, 2000). The second semester of kindergarten is a time when students would be expected to exhibit significant growth in sublexical skills, and, thus, is the time period selected for this investigation. Ninety-two kindergarten children were studied to examine the role of sublexical fluency in the development of early word reading and spelling across the spring of kindergarten. In addition to receiving the fluency measures every three weeks, the children also were administered accuracy sublexical measures and literacy (word reading and spelling) measures.

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Three aspects of the developmental role of sublexical skill fluency were examined in the current study. First, we examined the unique contribution of each sublexical fluency skill in addition to sublexical accuracy in explaining word reading and spelling variance. Any claim for the developmental importance of sublexical fluency should include evidence that fluency, which measures both speed and accuracy, adds to our understanding of early literacy skills beyond the role of accuracy. That is, if accuracy is the only sublexical skill that matters in early reading then fluency measures should not contribute any unique variance to word reading or spelling. Second, we were interested in a more complex predictive model that included growth of sublexical fluency to predict end-of-kindergarten reading and spelling skills. Growth curve analysis was applied to multiple waves of data to model individual change by estimating performance level in the middle of kindergarten and determining patterns of growth across the semester. We also examined growth in sublexical fluency as a function of word reading skill in kindergarten. If sublexical fluency growth predicts the earliest stages of literacy development, it would suggest that development of speed of access as well as accuracy impacts early word reading and spelling skills. A positive and unique relationship between sublexical fluency and early literacy would provide support for our theoretical framework that links fluency in sublexical skill to beginning literacy acquisition and would suggest that fluency is an overlooked mechanism in the linkage between letter names, letter sounds, phonological awareness and word reading and spelling (Good et al., 2001; Wolf & Katzir-Cohen, 2001). The third aspect studied was the interrelationships between accuracy alone and fluency (accuracy and speed) in predicting growth in sublexical fluency. Fluency by definition includes accuracy but how these skills covary and develop has not been determined. We expected sublexical accuracy in letter names, sounds, and phonological awareness to play a role in sublexical fluency growth. Also of interest was the relative contribution of accuracy and fluency in one type of skill (i.e., letter names, letter sounds, or phonological awareness) to the development of fluency in a different sublexical skill. These analyses provide a preliminary view of how foundational sublexical skills evolve and contribute to each other. As noted earlier, it is believed that these skills are mutually supportive but how they interrelate is unknown. Specifically, the following research questions were examined. 1. Does sublexical fluency predict word reading and spelling skills of kindergarten children beyond the contributions of sublexical accuracy measures? 2. Do the sublexical fluency growth functions in addition to accuracy and fluency point estimates explain childrenÕs literacy competence (word reading and spelling) at the end of kindergarten? Do childrenÕs learning trajectories vary as a function of word reading skill? 3. What are the interrelationships among the sublexical accuracy and fluency measures and which measures explain variance in the growth of the sublexical fluency skills? 2. Method 2.1. Participants and setting 2.1.1. Students The participants were students enrolled in full-day kindergarten at two elementary schools. Information letters and consent forms were sent to the parents/guardians of all

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students enrolled in six classes (77.5% return rate). The final sample consisted of 92 students (mean age = 67.55 months, SD = 4.82). There were 40 females (43.5%) and 52 males (56.5%), and 59.8% of the students were Caucasian, 38% of the students were AfricanAmerican, and 2.2% of the students were of other ethnicities or multiracial. 2.1.1.1. Setting. The study was conducted in two schools in one metropolitan school system in the Mid-Atlantic region of the United States. Both schools were moderate in size with approximately 500 students enrolled in pre-kindergarten through fifth grade. There were three kindergarten classrooms in each school with 20–23 students per class. The teachers were all female and had an average of ten years of teaching experience (SD = 4.52). Two of the teachers had bachelorÕs degrees, two had masterÕs degrees, and two teachers had masterÕs degrees plus at least 30 additional credits of graduate coursework. The schools were selected for participation based on differences in ethnicity and socioeconomic status to obtain a diverse sample of students which was representative of the participating school system. In the first school, 57% of enrolled students received free or reduced lunch, and there were more minority students (74% African-American, 20% Caucasian, and 6.2% other backgrounds). In the second school, 28% of enrolled students received free or reduced lunch, and 94% of the enrollment was Caucasian (4% AfricanAmerican, 2% other backgrounds). There were no significant differences by school for gender, the number of students receiving special education services, or the number of students repeating kindergarten. There was a significant and anticipated difference for ethnicity (v2 (3) = 59.27; p < .0001). We also tested differences between schools on January measures to ensure that the participating students were similar with respect to achievement levels. There were no significant differences between the schools on the first fluency point variables administered in January or other predictors, with the exception of January word reading (t (90) = 2.61, p = .01) The second school had higher mean beginning word reading (raw score mean = 6.17, SD = 7.56) than the first school (raw score mean = 2.91; SD = 3.81). This variable was controlled in all regression analyses. 2.1.1.2. Reading curriculum. The school systemÕs kindergarten reading curriculum focused intensively on early reading skills. The scope and sequence of skills in the curriculum included seven reading components: concepts of print and structural factors, phonemic awareness, alphabetic principle, cueing systems (includes using sound-symbol relationships for decoding), comprehension and interpretation of text, evaluation of informational text, reading fluency, and independent reading. The adopted system-wide reading program was Open Court Phonemic Awareness and Phonics Kit (SRA, 2000). This curriculum is a comprehensive kindergarten reading program that uses a systematic, explicit approach to beginning reading instruction. Each teacher was interviewed once and observed during reading instruction so that the instructional environment could be described sufficiently to provide information relevant to generalizability. This information was not used in any analyses. Reading instruction was observed twice during the study using field notes and a modified version of the Classroom Climate Scale (Vaughn & Schumm, n.d.). The Classroom Climate Scale is a observational instrument that uses a 1–5 rating to identify classroom characteristics (e.g., number of students, number of teachers or other instructional staff, etc.), instructional characteristics (e.g., instructional grouping, types and frequencies of instructional or inde-

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pendent activities, etc.), and teacher characteristics (e.g., responsiveness to individual needs, teachers interaction style, etc.). Reading instruction occurred approximately two hours per day, and this time was divided between whole class instruction and literacy centers. Teachers relied on whole group instruction for teaching early reading skills and primarily used the Open Court curriculum to determine lesson content and procedures. The Open Court kindergarten curriculum includes 100 lessons to teach reading skills. These lessons include instructional materials and activities that include phonological awareness activities and games, big book reading, alphabetic instruction (using sound/spelling cards with accompanying poems to reinforce letter-sound associations), pre-decodable books, and word reading. Each lesson included at least one phonological awareness activity and one alphabetic activity. Following whole group instruction, students participated in literacy centers. These included centers specific to the skill or lesson taught that day or week (e.g., a specific letter-sound skill), related to a thematic unit, or general centers such as the listening center, art center, or housekeeping. Overall, the instructional program at both schools and across teachers appeared to provide a strong emphasis on the targeted skills and was implemented consistently across the six classrooms. Explicit instruction was provided to teach letter identification, letter-sound associations, phonological awareness, and beginning word reading. Although there were some slight differences in teacher implementation of the instructional program with respect to individual teaching style as would be expected, students were provided with literacy instruction that met the recommended practices for early literacy instruction (Adams, 1990; National Reading Panel, 2000). 2.2. Measures Sublexical fluency, sublexical accuracy, and word reading and spelling measures were administered to all children. The sublexical measures are presented first followed by description of word reading and spelling measures. 2.2.1. Sublexical fluency measures 2.2.1.1. Letter name fluency. Letter name fluency (LNF; DIBELS, 2001; Ritchey, 2002) measured the number of correctly identified upper and lower case letters of the alphabet per minute. Upper and lower case letters (n = 52) were presented in random order on an 8.5 · 11 in. (standard) paper. This measure was modified to include only one upper case and one lower case letter per probe. Alternate-forms reliability (r = .86–.93; Good et al., cited in DIBELS, 2001; Speece et al., 2003) and concurrent and predictive criterion-related validity with word reading (r = .50–.70; Daly, Wright, Kelly, & Meadows, 1997; Good et al., cited in DIBELS, 2001; OÕConnor & Jenkins, 1999; Speece et al., 2003) are adequate to strong. Alternate forms were randomly selected for each measurement point. Alternateforms reliability for the current sample ranged from .83 to .90 for three-week intervals. 2.2.1.2. Letter sound fluency. Letter sound fluency (LSF; Elliott, Lee, & Tollefson, 2001; Speece & Case, 2001) measured the number of correctly identified letter sounds per minute. Lower case letters (n = 26) were randomly presented on a standard size page. To ensure students understood the task demands, three practice items with corrective feedback were included. Students were required to give the sound of consonants (including either the hard or soft sound of ‘‘c’’ and ‘‘g’’) and the short sound of vowels. Short vowel

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sounds were required because the curriculum only emphasized short vowels; long vowels sounds were scored as incorrect. One of the three practice items included a short vowel item to assist students in understanding task requirements. Alternate-forms reliability (r = .82–.93; Elliott et al., 2001; Speece & Case, 2001) and predictive criterion-related validity with word reading (r = .58–.75; Elliott et al., 2001; Speece & Case, 2001) for a similar measure are judged as adequate. Alternate-forms reliability for the present sample ranged from .72 to .91 over three-week intervals. 2.2.1.3. Phoneme segmentation fluency. Phoneme segmentation fluency (PSF; DIBELS, 2001) measured a studentÕs ability to segment phonemes in orally presented words that contain two to five phonemes. For example, the examiner orally presents the child with the word ‘‘sat,’’ and the ideal response would be /s/ /a/ /t/, earning a score of three points. Scoring also allows for partial credit so a student who responds /s/ /at/ would earn a score of two. After a student segmented the first word, subsequent words are administered consecutively for 1 min. The administration procedures were modified slightly from Good et al. (DIBELS, 2001) to include additional practice items with picture cues and more explicit corrective feedback. Alternate-forms reliability (r = .60–.88; Kaminski & Good, 1996; Good et al., cited in DIBELS, 2001) and predictive and concurrent criterion-related validity with word reading and reading-related measures (r = .54–.68; Kaminski & Good, 1996; Good et al., cited in DIBELS, 2001) are adequate. Alternate-forms reliability for the current study ranged from .73 to .82 across three-week intervals. 2.2.2. Sublexical accuracy measures 2.2.2.1. Letter name accuracy. This measure was researcher-developed and required students to identify letters of the alphabet in an untimed format. Upper and lower case letters (n = 52) were presented in random order on a standard size sheet of paper (six letters per row, nine rows total), and children were asked to point to each letter and say its name Responses were scored as correct or incorrect, and the total number correct was used in analyses. For this sample, internal consistency reliability, established by CronbachÕs a, was .97. The concurrent criterion-related validity coefficient with January Woodcock Reading Mastery Test-Revised/Normative Update, Form G (WRMT; Woodcock, 1998) Word Identification subtest (standard score, see description of test below) was .53 and predictive criterion-related validity with May WRMT Word Identification subtest (standard score) was .52. Word identification measures are appropriate criterion measures because of the established linkage between letter name knowledge and word reading in young children (e.g., Scarborough, 1998). 2.2.2.2. Letter sound accuracy. This measure was researcher-developed and required students to identify letter sounds in an untimed format. Like the LSF measure, lower case letters (n = 26) were presented in random order on a standard size sheet of paper (six letters per row, five rows total). For the letters ‘‘c’’ and ‘‘g,’’ students were asked to provide both the hard and soft sound (/k/ and /s/ for ‘‘c’’ and /g/ and /j/ for ‘‘g’’) and give the short sound of the vowels (max score = 28). Students were prompted to provide both sounds for ‘‘c’’ and ‘‘g.’’ They were asked to ‘‘say the other sound the letter makes.’’ The same prompt also was used if a long vowel sound was provided for a vowel. Responses were scored as correct or incorrect, and the total number correct was used in analyses. For this sample, internal consistency reliability, established by calculating CronbachÕs a,

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was .90. The concurrent criterion-related validity coefficient with January WRMT Word Identification subtest (standard score) was .52 and predictive criterion-related validity with May WRMT Word Identification subtest (standard score) was .62. 2.2.2.3. Phonological awareness. To assess studentsÕ phonological segmentation abilities in an untimed format, the Elision subtest of the Comprehensive Test of Phonological Processing (CTOPP; Wagner, Torgesen, & Rashotte, 1999) was administered. The Elision subtest measured a studentÕs ability to delete a sound or sounds from an orally presented word and then say the resulting word. For example, students were presented with ‘‘baseball’’ and asked to say ‘‘baseball without base.’’ The correct response was ‘‘ball.’’ Items increased in difficulty and required elision at the syllable and phoneme level in initial, final, and medial positions of words. The phonological awareness subtests of the CTOPP are appropriate for students from age 5 to 25 years old and demonstrate adequate reliability (r = .88) and concurrent and predictive criterion-related validity with measures of phonological awareness (r = .75) and word reading (r = .68–.72; Wagner et al., 1999). 2.2.3. Literacy measures 2.2.3.1. Word reading. The Word Identification subtest of the WRMT was administered to assess word reading skills at the beginning of the study [word reading (Jan.)] and at the end of kindergarten [word reading (May)]. The subtest consisted of 106 words and measured the studentÕs ability to identify isolated words of increasing difficulty. Technical adequacy information is reported for first grade children (Woodcock, 1998), but the test provides norms for children of this age (i.e., six years old). Adequate reliability (split-half reliability r = .98) and criterion-related validity (r = .69–.83) for first grade children was provided in the technical manual. 2.2.3.2. Spelling. The Test of Written Spelling-Fourth Edition (TOWS-4; Larsen, Hammill, & Moats, 1999) was administered to assess beginning spelling skills. The first ten items were administered to reduce testing time. Students were encouraged to spell part or parts of the word if they were unable to spell the word. The authors report adequate reliability (internal consistency and test–retest, r = .87–.95) and concurrent and predictive validity (r = .38–.85) with word reading and written language measures. Responses were scored using a correct letter sequence scoring (CLS) to allow for more sensitive analysis of beginning spelling (Tindal & Marston, 1990; White & Haring, 1980). In CLS scoring, the total number of points possible for each word is the number of letters in the word plus one. Responses earned one point for a correct first letter, one point for a correct final letter, and one point for each correct letter sequence within the word. For example, if the word ÔsunÕ was spelled Ôsn,Õ the score would be two (first and last letter correct) but a spelling of ÔsunÕ would be four points. Similarly, a spelling of ÔsÕ would be one point. The maximum possible score was 46. A second scorer scored all responses, and interrater agreement was .97. 2.2.4. Procedure The study was conducted during the second half of the kindergarten year. The initial measures were administered in two 30 min sessions in January and early February. In session one, children received the following measures in the order listed: letter name accuracy, letter sound accuracy, word reading (Jan.), and elision. In a separate session, the children

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received the following measures, again in standard order: letter name fluency, phoneme segmentation fluency, and letter sound fluency. The measures were not counterbalanced as previous experience with the measures and kindergarten children suggested that the letter name tasks were more familiar and provided an opportunity to begin the sessions on a positive note. In the second session, we separated letter name and letter sound fluency because of childrenÕs tendency to confuse the task requirements. This separation was not necessary for the untimed letter tasks in session one as there was ample opportunity, due to the untimed format, to prompt children to provide the letter sound if they gave the letter name. Children were prompted once, if necessary, during administration of the letter sound fluency task. Fluency measures (LNF, LSF, and PSF) were then administered from late January/ beginning February to May at three-week intervals (approximately 15 school days apart, M = 14.29) for a total of five fluency data points. Word reading (May) and spelling were administered during the last two weeks of May. Stopwatches were used for all the fluency measures. 3. Results The results are organized by research question. Descriptive statistics for the fluency measures administered across the semester are presented in Table 1, and the descriptive statistics for the accuracy and literacy measures are presented in Table 2. ChildrenÕs performance on fluency measures approximated the 50th percentile based on national norms (Aimsweb, 2004). The 50th percentile scores for LNF were 33 and 43 for winter and spring, respectively. The current sampleÕs LNF mean scores at the first (Jan./Feb.) and fifth (May) points were 37.29 and 44.67. The corresponding normative winter and spring scores (and sample scores), respectively, for LSF were 17 (16.34) and 30 (29.84); for PSF 17 (17.51) and 40 (39.16). Analysis of Table 1 also indicates that the children demonstrated growth in each of the fluency measures Performance on the published, norm-referenced

Table 1 Descriptive statistics for sublexical fluency growth measures Measure

Time

Mean

SD

Range

LNF

1 2 3 4 5 1 2 3 4 5 1 2 3 4 5

37.29 42.93 42.93 44.52 44.67 16.34 20.43 26.40 27.66 29.84 17.51 23.42 28.65 36.12 39.16

15.23 15.80 16.57 17.8 15.71 8.75 11.60 16.64 14.53 14.55 11.95 13.99 14.35 18.43 16.18

2–70 2–81 2–82 0–86 3–83 0–43 0–60 0–82 0–73 2–72 0–52 0–55 2–56 0–69 6–71

LSF

PSF

Note. LNF, letter name fluency; LSF, letter sound fluency; PSF, phoneme segmentation fluency.

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Table 2 Descriptive statistics of sublexical accuracy and literacy measures Measure

Standard score1

Raw score

Letter name accuracy Letter sound accuracy Word reading (Jan.) Elision Word reading (May) Spelling (CLS)

Mean

SD

Range

44.39 14.91 4.54 3.17 10.64 18.09

10.43 6.00 6.17 2.51 9.69 9.78

2–52 0–27 0–31 0–11 0–43 0–41

Mean

SD

103.15 9.18 107.68

5.59 2.44 13.09

Note. CLS, correct letter sequence scoring. 1Standard scores for Word Reading are based on mean = 100, SD = 15, standard scores for Elision are based on mean = 10, SD = 3.

literacy measures (Word Identification, Elision) was within the average to high average normative range (Table 2). Based on the available normative evidence the sample may be characterized as in the average to above average range on a variety of literacy-related skills. Correlations of accuracy measures, fluency measures, growth estimates, and literacy measures are presented in Table 3. The accuracy measures shared approximately 50 % variance with the fluency counterpart measures (rÕs range = .69–.70). This indicates that while sublexical accuracy and fluency measures are related, they are not identical. The sublexical accuracy and fluency measures were moderately to strongly correlated with the two literacy measures (rÕs range = .34–.72), supportive of previous research (Scarborough, 1998). Table 3 Correlations among sublexical accuracy, sublexical fluency, sublexical fluency growth parameters, word reading and spelling 1 1 2 3 4 5 6 7 8 9 10

11 12 13

Letter name accuracy Letter sound accuracy Word reading (Jan.) Elision Letter name fluency LNF-slope LNF-quad Letter sound fluency LSF-slope Phoneme segmentation fluency PSF-slope Word reading (May) Spelling

2

3

4

5

—

6

7

8

—

9

10

11

12

— 0.74

—

0.36

0.54

—

0.45 0.70

0.57 0.65

0.58 0.48

— 0.45

0.38 0.41 0.62

0.41 0.43 0.76

0.32 0.36 0.50

0.29 0.28 0.58

0.14 0.19 0.78

— 0.98 0.28

— 0.30

0.55 0.36

0.65 0.57

0.52 0.47

0.43 0.69

0.70 0.43

0.62 0.11

0.63 0.12

0.65 0.64

— 0.36

—

0.19 0.46

0.26 0.65

0.24 0.89

0.39 0.66

0.20 0.58

0.31 0.46

0.27 0.51

0.21 0.65

0.42 0.68

0.21 0.53

— 0.34

—

0.58

0.72

0.65

0.65

0.60

0.44

0.47

0.65

0.70

0.62

0.43

0.78

Note. All correlations > .21, p < .05; r > .27, p < .01; r > .36, p < .001; r > .43, p < .0001; LNF, letter name fluency; LSF, letter sound fluency; PSF, phoneme segmentation fluency; Quad, quadratic parameter.

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The fluency growth parameters (LNF-Slope, LNF-Quad, PSF-Slope, described below) demonstrated moderate to strong relationships with the literacy measures (rÕs range = .34–.70). The strongest relationship was between LSF-Slope and word reading (r = .68) and LSF-Slope and spelling (r = .70). 3.1. Contribution of accuracy and fluency sublexical measures to word reading and spelling 3.1.1. Analysis strategy The first research question determined the unique contribution of the accuracy and fluency sublexical measures administered in January/early February to word reading and to spelling at the end of kindergarten. Two sets of hierarchical multiple regression analyses were conducted. These analyses preceded the more complex models tested in the next section to provide initial evidence on the variables of primary interest, sublexical accuracy and fluency. The first fluency point (LNF 1, LSF 1, and PSF 1) and the accuracy measure were entered in the regression model. For the prediction of word reading (May), word reading (Jan.) was entered in the first block to control for initial word reading skill and school differences. Then, the entry position of the accuracy and fluency measures was alternated in the second and third block to assess unique variance. The analysis strategy was repeated for spelling except that we did not have a spelling measure to control for initial skill level (autoregressor). The results of significance testing for the contribution of unique variance are presented in text. The unstandardized (b) and standardized (b) coefficients and tests of significance from the full multiple regression models are presented in Table 4. These coefficients indicate the magnitude of the relationship of the variable with word reading and spelling while controlling for other variables in the model. For each analysis, standardized residuals greater than ±3.00 were identified as outliers and removed from further analysis (several cases was eliminated across analyses). The contribution of the autoregressor (word reading) is the same for each model and is reported only for the first analysis. Table 4 Prediction of May literacy outcomes comparing accuracy and fluency measures Word reading (May)

Spelling

b

b

t

p

B

b

t

p

LNF Word reading (Jan.) Letter name accuracy Letter name fluency

1.245 0.059 0.095

0.788 0.066 0.159

15.029 1.016 2.307

0.0001 0.3120 0.0240

— 0.272 0.252

— 0.289 0.399

— 2.473 3.410

— 0.0150 0.0010

LSF Word reading (Jan.) Letter sound accuracy Letter sound fluency

1.165 0.194 0.217

0.720 0.122 0.192

13.716 1.747 2.762

0.0001 0.0840 0.0070

— 0.856 0.295

— 0.522 0.254

— 4.643 2.262

— 0.0001 0.0260

PSF Word reading (Jan.) Elision Phoneme segmentation fluency

1.217 0.760 0.025

0.752 0.201 0.031

12.984 2.841 0.469

0.0001 0.0060 0.6400

— 1.531 0.276

— 0.394 0.343

— 3.586 3.125

— 0.0001 0.0020

Note. LNF, letter name fluency; LSF, letter sound fluency; PSF, phoneme segmentation fluency. Dash indicates variable not tested in model.

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3.1.2. The contribution of letter name accuracy and fluency In predicting end-of-kindergarten word reading, word reading (Jan.) accounted for 78.7% of the variance (R2 = .787; adj. R2 = .785, p < .0001). When letter name accuracy was entered next it accounted for an additional 2.3% variance (DR2 = .023; F (1, 85) = 10.345, p = .002). Letter name fluency, entered last, accounted for an additional 1.1% variance (DR2 = .011; F (1, 84) = 5.322, p = .024). In the second set of analyses, letter name fluency was entered second and accounted for 3.2% additional variance (DR2 = .032; F (1, 85) = 15.155, p < .0001). Letter name accuracy did not account for unique variance when added last (D R2 = .002; F (1, 84) = 1.033, p = .312). Together, the three variables accounted for 82.2% of the variance in word reading (adj. R2 = .815). Letter name fluency but not letter name accuracy contributed significant unique variance. For spelling, when letter name accuracy was entered first it accounted for 32.5% variance (R2 = .325; adj. R2 = .318, p < .0001). Letter name fluency accounted for an additional 8% variance (DR2 = .08; F (1, 86) = 11.625, p < .001). In the reverse order, letter name fluency accounted for 36.3% of the variance in spelling (R2 = .363; adj. R2 = .356). Letter name accuracy then accounted for 4.2% unique variance (DR2 = .042; F (1, 86) = 6.117, p = .015). Letter name fluency and letter name accuracy were both significant, unique predictors of spelling (see Table 4) and accounted for 40.6% of the variance in spelling (adj. R2 = .392). 3.1.3. The contribution of letter sound accuracy and fluency Beyond the influence of beginning word reading, letter sound accuracy accounted for an additional 4.7% variance (DR2 = .047; F (1, 86) = 22.456, p < .0001). Letter sound fluency, when entered last accounted for 1.5% unique variance (DR2 = .015; F (1, 85) = 7.628, p = .007). In the second set of analyses, letter sound fluency was entered second, and it accounted for 5.6% unique variance (DR2 = .056; F (1, 86) = 28.092, p < .0001). Letter sound accuracy did not account for significant unique variance when entered last (DR2 = .006; F (1, 85) = 3.502, p = .084). With all variables in the model, word reading (Jan.) and letter sound fluency were significant predictors of end-of-kindergarten word reading (see Table 4) and accounted for 83.3% of the variance (adj. R2 = .827). Similar to letter name fluency, letter sound fluency contributed unique variance above and beyond letter sound accuracy in predicting word reading. For spelling, letter sound accuracy, when entered first, accounted for 51.1% variance (R2 = .511; adj. R2 = .506, p < .0001). Letter sound fluency then accounted for 2.7% unique variance (DR2 = .027; F (1, 86) = 5.116, p = .026). In the reverse order, letter sound fluency accounted for 42.3% of the variance in spelling (R2 = .423; adj. R2 = .417). Letter sound accuracy then accounted for 11.6% unique variance (DR2 = .116; F (1, 86) = 21.555, p < .0001). Letter sound fluency and letter sound accuracy both were significant predictors of spelling (see Table 4) and accounted for 53.9% of the variance in spelling (adj. R2 = .528). 3.1.4. The contribution of elision and phoneme segmentation fluency Elision accounted for 3.4% variance after accounting for January word reading (DR2 = .034; F (1, 86) = 14.989, p < .0001). When entered last, phoneme segmentation fluency did not account for significant unique variance (DR2 = .001; F (1, 85) = .220, p = .64). In the second set of analyses, phoneme segmentation fluency accounted for 1.6% variance beyond word reading (DR2 = .016; F (1, 86) = 6.472, p = .013). Entered last, elision

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accounted for 1.8% unique variance (DR2 = .018; F (1, 85) = 8.069, p = .006). Unlike the previous results for letter name fluency and letter sound fluency, phoneme segmentation fluency did not contribute unique variance to word reading. The complete model accounted for 80.5% of the variance in word reading (adj. R2 = .798; see Table 4). For spelling, elision accounted for 39.9% variance (R2 = .399; adj. R2 = .392, p < .0001). When entered next, phoneme segmentation fluency accounted for 6.1% unique variance (DR2 = .061; F (1, 86) = 9.768, p = .002). In the reverse order, phoneme segmentation fluency accounted for 37.9% of the variance in spelling (R2 = .379; adj. R2 = .372, p < .0001). Elision then accounted for 8.1% unique variance (DR2 = .081; F (1, 86) = 12.863, p < .001). Taken together, both variables were significant, unique predictors of spelling and accounted for 46% of the variance in spelling (total R2 = .460, adj. R2 = .447; see Table 4). 3.2. Role of growth in sublexical fluency in development of literacy skills The second research question determined the extent to which the full complement of sublexical skills (accuracy and fluency) and the growth functions associated with the sublexical fluency skills explained word reading and spelling variance. Two sets of analyses were conducted to (a) predict end-of-kindergarten word reading and spelling and (b) examine whether children with different levels of beginning word reading skill varied on sublexical fluency growth. 3.2.1. Analysis strategy To obtain the growth functions to use in the analyses, growth curve analysis was used to determine the unconditional growth model for each fluency measure using SAS PROC Mixed (Francis, Schatschneider, & Carlson, 2000; SAS, 1999). Growth curve analysis models development over time. Data were centered at the first point so that the rate of growth could be examined beginning in January and to examine growth while controlling initial skill level. For this study, growth functions could include the intercept parameter (indicating beginning level), the slope parameter (indicating rate of growth), and the quadratic parameter (indicating acceleration or deceleration in slope) terms. Each parameter is tested sequentially to determine if it is needed to describe the best fitting growth model (i.e., fixed effect). If the fixed effect for the parameter is significantly different from zero, the random effect is tested to determine if sufficient variance exists between children to use the term as a predictor. Different models of growth were identified for each fluency measure. Fig. 1 displays the mean growth trajectories for each of the fluency variables. As displayed in Table 5, the best fitting model of growth for letter name fluency was a random intercept, random slope, random quadratic model indicating that all three parameters were necessary for describing growth (see p column under ‘‘Fixed Effect’’) and that there was significant variance to allow each child to have a unique value for each parameter (see p column under ‘‘Random Effect’’). Growth in letter sound fluency and phoneme segmentation fluency was best described by random intercepts and slopes, although a fixed quadratic term described a constant rate of slowing in LSF growth. All parameters for letter name fluency had sufficient variance and could be used as predictors whereas only the intercept and slope parameters best described growth in letter sound fluency and phoneme segmentation fluency.

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315

50

items per minute

45 40 35 30 25 20 15 10 5 0 1

2

3

4

5

point LNF

LSF

PSF

Fig. 1. Unconditional growth models for letter name fluency, letter sound fluency, and phoneme segmentation fluency.

Table 5 Growth parameter estimates for unconditional models (fixed and random effects) Fixed effect

Random effect

Estimate

t

SE

p

Estimate

SE

p

LNF

Intercept Slope Quadratic Residual

36.92 3.62 0.41

23.29 4.31 2.12

1.59 0.84 0.19

0.0001 0.0001 0.0367

203.24 26.19 1.16 29.90

5.89 2.49 2.11 9.45

34.48 10.53 0.55 3.16

0.0001 0.0065 0.0174 0.0001

LSF

Intercept Slope Quadratic Residual

16.03 5.74 0.58

14.34 7.63 3.31

1.12 0.75 0.17

0.0001 0.0001 0.0013

80.13 3.40

5.08 3.01

15.76 1.13

0.0001 0.0013

37.95

11.61

3.27

0.0001

Intercept Slope Residual

17.62 5.62

120.04 6.50 51.24

5.30 3.62 11.60

22.66 1.80 4.42

0.0001 0.0001 0.0001

PSF

13.71 15.74

1.29 0.36

0.0001 0.0001

z

Note. df = 91; LNF, letter name fluency; LSF, letter sound fluency; PSF, phoneme segmentation fluency.

3.2.2. Prediction of word reading and spelling A second series of multiple regression analyses were conducted that included accuracy, fluency (using the first measurement point), and growth variables for each sublexical skill. The unstandardized (b) and standardized (b) coefficients and tests of significance from all multiple regression models are presented in Table 6. Significant predictors of end-of-kindergarten word reading were word reading (Jan.), elision, LSF-Slope, and LNF-Quadratic. These variables explained 89.4% of the variance (adj. R2 = .879; p < .0001) in May word reading. For spelling, letter sound accuracy, elision, phoneme segmentation fluency, and LSF-Slope were significant predictors. These significant variables explained 71.4% of the variance (adj. R2 = .678; p < .0001) in spelling. For both outcomes, accuracy, fluency, and growth variables accounted for unique variance in word reading and spelling. Growth in letter sound fluency (LSF-Slope), elision, and LNF-Quadratic were consistent predictors for both literacy outcomes.

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Table 6 Prediction of May literacy outcomes from sublexical accuracy, fluency, and growth parameters Word reading (May) b Letter name accuracy Letter name fluency LNF-slope LNF-quad Letter sound accuracy Letter sound fluency LSF-slope Elision Phoneme segmentation fluency PSF-slope Word reading (Jan.)

B 0.074 0.008 0.885 5.760 0.115 0.089 1.078 0.630 0.044 0.140 1.008

0.083 0.013 0.336 0.438 0.073 0.080 0.176 0.170 0.056 0.031 0.638

Spelling

t

p

b

1.248 0.149 1.612 2.184 1.036 1.038 2.231 2.805 0.969 0.699 12.668

0.2160 0.8820 0.1110 0.0320 0.3030 0.3030 0.0290 0.0060 0.3360 0.4870 0.0001

0.034 0.025 1.594 8.627 0.437 0.124 1.834 0.751 0.183 0.677 —

b 0.037 0.039 0.573 0.622 0.266 0.106 0.286 0.193 0.227 0.141 —

t

p

0.343 0.277 1.743 1.981 2.324 0.844 2.220 2.052 2.386 1.967 —

0.7330 0.7830 0.0850 0.0510 0.0230 0.4010 0.0290 0.0430 0.0190 0.0530 —

3.2.3. Development of fluency by reader groups The foregoing analyses indicated significant roles for sublexical fluency and accuracy skills even when word-reading skill in January and initial sublexical fluency and accuracy skills were controlled. Another way to illustrate these relationships is to compare the growth curves for children with different levels of reading competency. This was accomplished by using a conditional growth model (Francis et al., 2000) in which group membership was tested as a predictor of random parameters (e.g., intercept and slope for all fluency measures, quadratic parameter only for LNF). A significant fixed effect in a conditional model indicates that the groups are significantly different with respect to the intercept and/or growth parameters. Three groups of children were formed based on word reading skill in January and May. First, a median split for word reading (Jan.) was used to determine initial reader groups (raw score 6 three words). Thirty-eight students who read four or more words were identified as January Readers (mean = 9.11, SD = 7.44). Fifty-four students who read three or fewer words were identified as January Nonreaders (mean = 1.33; SD = 1.17). In the first conditional model, differences in initial levels (i.e., intercept) and growth parameters for students were tested, comparing January Readers (students reading > three words, n = 38) to January Nonreaders (students reading 6 three words in January; n = 54). Second, the January Nonreaders group was further divided into two groups based on May word reading performance. Students who continued to read less than three words in May (n = 31) were identified as Prereaders (Jan. mean = .39, SD = .72; May mean = 1.61, SD = 1.37). Students who read more than three words in May (n = 23) were identified as Emerging Readers (Jan. mean = 2.03, SD = .91; May mean = 7.77, SD = 3.67). In the second conditional model, differences in initial level (intercept) and growth parameters for students were tested, comparing Prereaders to Emerging Readers. For letter name fluency, the January Readers had a significantly higher initial LNF level than the January Nonreaders (Emerging + Prereaders) (t (176) = 6.41, SE = 2.68, p < .0001). January Readers identified, on average, 17.19 letters per minute more than students who were not yet reading. There was no significant difference in the slope (t (176) = .91, SE = 1.71, ns) or the quadratic parameter (t (176) = .84, SE = .39, ns). Of the January Nonreaders, Emerging Readers, compared to Prereaders, had a significantly higher initial intercept (t (103) = 3.16, SE = 3.42, p = .0021). Emerging Readers

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identified, on average, 10.79 more letter names per minute than Prereaders. Differences on the slope and quadratic parameters were not significant (slope t (103) = 1.93, SE = 2.02, p = .06; quadratic t (103) = 1.82, SE = .46, p = .07). The rate of growth of Emerging Readers was slowing slightly (i.e., negative quadratic term) while the pattern for Prereaders suggested linear growth. These patterns are illustrated in Fig. 2. For letter sound fluency, the January Readers had a significantly higher initial LSF level than the January Nonreaders (t (267) = 6.56, SE = 1.78, p < .0001) but there was no significant difference on slope (t (267) = 0.87, SE = .57, ns). January Readers identified, on average, 11.68 more sounds per minute than January Nonreaders. Of the January Nonreaders, the Emerging Readers, compared to Prereaders, had a significantly higher intercept (t (156) = 3.25, SE = 1.86, p = .0014) than Prereaders. Emerging Readers identified, on average, 14.49 sounds per minute while Prereaders identified, on average, only 8.42 sounds per minute. Emerging Readers also had a significantly higher rate of growth (t (156) = 3.31, SE = .61, p = .0011), increasing at a rate 2.017 letter sounds increase per three-week interval more than Prereaders (Emerging Readers mean slope = 5.014, Prereaders mean slope = 2.997 letter sound increase per three week interval). There was no difference in growth between January Readers and Nonreaders as a whole, but children who became readers by May (Emerging Readers) demonstrated greater gains in letter sound fluency compared to children who were still not reading by May (Prereaders). These results are illustrated in Fig. 3. For phoneme segmentation fluency, the January Reader groupÕs initial PSF level was significantly higher than that of January Nonreaders (t (268) = 4.17, SE = 2.40, p < .0001). January Readers segmented, on average, 10.03 phonemes per minute more than January Nonreaders. There was no statistically significant difference in the rate of growth (t (268) = 1.25, SE = .72, ns). Of January Nonreaders, Emerging Readers had a significantly higher initial level (t (157) = 2.81, SE = 2.17, p = .0057) than Prereaders, segmenting on average 6.09 phonemes per minute more. There was no significant difference in rate of growth (t (157) = 1.43, SE = 1.00, ns). Thus, all the children were growing at the same rate, but the Emerging Readers possessed more skill initially. These differences are illustrated in Fig. 4.

letters named per minute

60 50 40 30 20 10 0 1

2

3

4

5

time Jan. Readers (n = 38)

Prereaders (n = 23)

Emerging Readers (n = 31)

Fig. 2. Growth in letter name fluency by reader groups.

K.D. Ritchey, D.L. Speece / Contemporary Educational Psychology 31 (2006) 301–327 letters sound identified per minute

318

40 35 30 25 20 15 10 5 0 1

2

3

4

5

Time Jan. Readers (n = 38)

Prereaders (n = 23)

Emerging Readers (n = 31)

phonemes segmented per minute

Fig. 3. Growth in letter sound fluency by reader groups.

60 50 40 30 20 10 0 1

2

3

4

5

Time Jan. Readers (n = 38)

Prereaders (n = 23)

Emerging Readers (n = 31)

Fig. 4. Growth in phoneme segmentation fluency by reader groups.

To summarize across sublexical fluency skills, all of the reader groups, variously configured, differed on initial skill level. The finding of greatest interest is that the Emerging Readers and Prereaders also differed on rate of growth in LSF. 3.3. Interrelationships among sublexical fluency, accuracy, and growth 3.3.1. Analysis strategy The final set of analyses examined the interrelationships among accuracy, fluency and growth in sublexical fluency. We were interested in identifying which of these variables explained initial level (i.e., intercept) and/or growth in each sublexical fluency skill both independently and in the presence of other significant variables. Conditional growth curve models were used to determine the predictors of the random intercept and growth parameters (Francis et al., 2000). After standardizing each predictor (mean = 0, SD = 1), each variable was examined as a predictor of initial point and growth parameters in a two-stage

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model. In the first stage, the simple conditional model, each variable was tested independently to determine if it was a significant predictor of the random parameters of the unconditional model (intercept, slope, and/or quadratic). Then in the second model, the complete conditional model, only the significant variables from the simple conditional model were entered in the complete conditional model. Significant predictors in the complete conditional model indicated that the variables explain unique variance in the intercept or growth parameters (see p column under ‘‘Fixed Effect’’). Tables 7–9 contain the details of these analyses. In text, we emphasize the results from the complete conditional models. 3.3.2. Letter name fluency The intercept (initial level), slope, and quadratic parameters of letter name fluency could be predicted because each was random in the unconditional model (see Table 5). The unique predictors of letter name fluency intercept were elision, word reading (Jan.), and letter sound fluency. The unique predictors of LNF-Slope were LSF-Slope and PSF-Slope. Word reading (Jan.), and LSF-Slope predicted the LNF-Quadratic. The negative quadratic values for word reading (Jan.) and LSF-Slope indicate that children with higher values on these variables had letter name fluency growth curves that began to level off at the end of the year. Table 7 Prediction of LNF growth parameters from accuracy, fluency, and growth measures (Conditional model) Simple conditional model

Complete conditional model

Estimate

t

SE

p

Intercept

Letter name accuracy Letter sound accuracy Word reading (Jan.) Elision Letter sound fluency Phoneme segmentation fluency

10.75 10.47 8.08 7.09 11.37 6.68

9.40 8.90 5.82 4.98 10.77 4.63

1.14 1.18 1.39 1.43 1.06 1.44

0.0001 0.0001 0.0001 0.0001 0.0001 0.0001

Slope

Letter name accuracy Letter sound accuracy Word reading (Jan.) Elision Letter sound fluency Phoneme segmentation fluency LSF-slope PSF-slope

1.19 1.48 1.42 0.81 0.23 0.36

1.40 1.75 1.64 0.96 0.27 0.42

0.85 0.85 0.86 0.85 0.84 0.84

0.1620 0.0813 0.1020 0.3407 0.7888 0.6718

7.62 1.70

11.47 2.04

0.66 0.83

0.0001 0.0430

Letter name accuracy Letter sound accuracy Word reading (Jan.) Elision Letter sound fluency Phoneme segmentation fluency LSF-slope PSF-slope

0.26 0.31 0.39 0.02 0.06 0.09

1.35 1.64 2.01 0.62 0.31 0.46

0.19 0.19 0.19 0.19 0.19 0.19

0.1799 0.1035 0.0464 0.5362 0.7585 0.6467

1.44 0.21

8.67 1.10

0.17 0.19

0.0001 0.2737

Quadratic

Estimate

t

SE

p

5.62 0.73 3.05 0.19 4.86 1.24

5.37 0.56 3.09 0.18 4.07 1.18

1.05 1.30 0.99 1.06 1.19 1.05

0.0001 0.5767 0.0023 0.8560 0.0001 0.2401

4.17 0.47

5.50 2.22

0.76 0.21

0.0001 0.0241

0.18

2.88

0.06

0.0045

0.77

4.10

0.19

0.0001

Note. LNF, letter name fluency; LSF, letter sound fluency; PSF, phoneme segmentation fluency.

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Table 8 Prediction of LSF growth parameters from accuracy, fluency, and growth measures (conditional model) Simple conditional model Estimate

Complete conditional model

t

SE

p

Estimate

t

SE

P

Intercept

Letter name accuracy Letter sound accuracy Word reading (Jan.) Elision Letter name fluency Phoneme segmentation fluency

6.24 7.90 5.41 5.55 7.27 5.80

7.30 11.62 5.84 6.13 10.65 7.04

0.85 0.68 0.93 0.90 0.68 0.82

0.0001 0.0001 0.0001 0.0001 0.0001 0.0001

0.80 4.77 0.01 1.01 4.50 1.72

0.86 5.03 0.02 1.44 5.37 2.58

0.93 0.95 0.74 0.70 0.84 0.67

0.3921 0.0001 0.9879 0.1522 0.0001 0.0105

Slope

Letter name accuracy Letter sound accuracy Word reading (Jan.) Elision Letter name fluency Phoneme segmentation fluency LNF-slope LNF-quad PSF-slope

0.67 0.68 0.73 0.36 0.84 0.04

2.40 2.45 2.64 1.27 3.11 0.14

0.28 0.28 0.28 0.28 0.27 0.28

0.0171 0.0151 0.0088 0.2049 0.0020 0.8919

0.54 0.64 0.05

1.35 1.67 0.15

0.40 0.38 0.31

0.1771 0.0962 0.8790

1.33

3.64

0.36

0.0003

1.54 1.52 0.90

6.38 6.23 3.36

0.24 0.24 0.27

0.0001 0.0001 0.0009

2.46 0.70 0.48

2.39 0.68 2.30

1.03 1.03 0.21

0.0177 0.4992 0.0225

Note. LNF, letter name fluency; LSF, letter sound fluency; PSF, phoneme segmentation fluency.

Table 9 Prediction of PSF growth parameters from accuracy, fluency, and growth measures (conditional model) Simple conditional model Estimate

Complete conditional model

t

SE

p

Estimate

t

SE

p

Intercept

Letter name accuracy Letter sound accuracy Word reading (Jan.) Elision Letter name fluency Letter sound fluency

4.69 7.07 6.36 8.99 5.45 7.85

3.87 6.56 5.60 10.00 4.61 7.73

1.21 1.08 1.14 0.90 1.18 1.02

0.0001 0.0001 0.0001 0.0001 0.0001 0.0001

1.53 1.51 0.81 6.60 0.86 3.78

1.11 0.98 0.72 5.95 0.57 2.37

1.38 1.54 1.12 1.11 1.50 1.59

0.2685 0.3259 0.4707 0.0001 0.5666 0.0183

Slope

Letter name accuracy Letter sound accuracy Word reading (Jan.) Elision Letter name fluency Letter sound fluency LNF-slope LNF-quad LSF-slope

0.23 0.23 0.21 0.47 0.18 0.01 1.02 0.87 1.41

0.63 0.62 0.56 1.31 0.49 0.02 2.98 2.51 4.22

0.36 0.36 0.37 0.36 0.36 0.36 0.34 0.35 0.33

0.5303 0.5341 0.5739 0.1926 0.6241 0.9810 0.0032 0.0128 0.0001

3.47 3.34 0.93

2.12 2.03 2.12

1.64 1.65 0.44

0.0349 0.0431 0.0351

Note. LNF, letter name fluency; LSF, letter sound fluency; PSF, phoneme segmentation fluency.

3.3.3. Letter sound fluency The intercept and the slope parameters of letter sound fluency could be predicted because each was random in the unconditional model (see Table 5; the quadratic parameter was fixed indicating that childrenÕs growth was slowing uniformly). In the complete conditional model, letter sound accuracy, letter name fluency, and phoneme segmentation

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fluency were significant unique predictors of letter sound fluency intercept. Letter name fluency, LNF-Slope, and PSF-Slope were unique predictors of the letter sound fluency growth. 3.3.4. Phoneme segmentation fluency The intercept and slope parameters for phoneme segmentation fluency could be predicted because they were random in the unconditional model (see Table 5). In the complete conditional model, elision and letter sound fluency were the unique predictors of the phoneme segmentation fluency intercept, and LNF-Slope, LNF-Quad, and LSF-Slope were unique predictors of phoneme segmentation fluency growth (see Table 9). 4. Discussion The purpose of this study was to investigate if letter name fluency, letter sound fluency, and phoneme segmentation fluency help explain the development of word reading and spelling in kindergarten children just acquiring these skills. In addition to examining studentsÕ sublexical skills at a single point in time, we expanded analysis to include the growth of fluency skills over time. There are three major conclusions. First, as early as kindergarten, sublexical fluency skills explain a small, but significant and unique amount of variance in word reading and spelling outcomes beyond the contribution of accuracy. Second, growth in sublexical fluency skills is related to word reading and spelling outcomes. Third, the relationship between sublexical accuracy and fluency skills is best characterized by developmental reciprocity. We suggest that sublexical fluency, especially letter sound fluency, may act as the mechanism that connects letter names, letter sounds, and phonemic segmentation to word reading and spelling. The findings support the theoretical contention that fluency in component skills contributes to early literacy development (LaBerge & Samuels, 1974; Fredericksen et al., 1985; Samuels & Flor, 1997). 4.1. Sublexical accuracy and fluency in learning to read and spell words In this study, sublexical accuracy and fluency measures were directly compared by assessing the same skill, one in an untimed accuracy format and one in a timed fluency format. While there is shared variance between accuracy and fluency sublexical skills, the unique variance associated with the fluency improves understanding of beginning word reading and spelling development. Letter name fluency and letter sound fluency, but not phoneme segmentation fluency, uniquely predicted word reading and were stronger predictors than their accuracy counterparts. For word reading, it is not only whether students can accurately identify letter names or letter sounds that contributes to word reading, but also how quickly they can do so. This finding supports and extends an information processing perspective which suggests that sublexical fluency is important for reading fluency (Good et al., 2001; LaBerge and Samuels, 1974; Logan, 1997; Posner & Snyder, 1975; Samuels, 1976; Wolf & Katzir-Cohen, 2001). For reading connected text fluently, efficient word reading is a means to comprehension, as accurate and quick word recognition allows cognitive resources to shift to comprehension. At the sublexical level, efficient letter identification and access to letter-sound relationships appear to act as a conduit to word recognition. Fluent recognition of letter-sound associations may provide the mechanism that supports phonological recoding, blending, and accurate word identification. Sublexical

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fluency may allow children to quickly consolidate knowledge across sublexical skills and make more complete connections between letters and sounds while reading words (Ehri, 1992, 1997). Phoneme segmentation fluency, as previously stated, did not uniquely predict word reading but was uniquely predictive of spelling. Elision, which was selected as the accuracy counterpart of phoneme segmentation fluency, contributed unique variance to both word reading and spelling. This finding suggests that phonological segmentation fluency skill may have differential importance in literacy development. For word reading, what may be important is that students acquire the insight that words are composed of sounds; the speed with which they can do so may be irrelevant. On the other hand, spelling may require both accuracy and speed in segmentation skill. Stage and Wagner (1992) found that working memory is a predictor of spelling skill in young children, implicating a role for efficiency in processing the required elements. Young children often have difficulty efficiently segmenting a word into phonemes, identifying the phoneme-grapheme relationship, and then writing letters while, at the same time, trying to remember the word they are spelling. Fluent phoneme segmentation may serve to alleviate working memory limitations and help students be more successful spellers. A competing explanation may be related to measure selection. Elision was chosen to assess phonological segmentation skill (rather than a global phonological awareness ability) because it assessed a similar construct as phonemic segmentation fluency. However, it did not assess accuracy in an identical or parallel format. Phoneme segmentation fluency is a more dynamic assessment and scoring gave credit for a range of skills (e.g., onset-rime knowledge) associated with phonological segmentation. In contrast, elision is scored dichotomously and contains fewer potential stimuli. Future investigations in this line of research may benefit from selecting parallel measures of segmentation skill or a range of phonological awareness skills. 4.2. Sublexical accuracy, fluency, and growth The previous discussion demonstrated that the individual sublexical fluency skills, derived from a single measurement point, were each related to word reading and spelling at the end of kindergarten and replicated and extended previous findings (Speece & Ritchey, 2005; Speece et al., 2003; Stage et al., 2001). Next we consider the results of more complex multivariate analyses that include sublexical accuracy, fluency, and growth in fluency as predictors of word reading and spelling. 4.2.1. Word reading Using January word reading as an autoregressor, elision was the only January variable that uniquely predicted May word reading skill. The January sublexical fluency measures, letter name accuracy, and letter sound accuracy measures were not significant. This is an interesting finding given the predictive power of letter names from kindergarten to first grade and beyond (e.g., Scarborough, 1998). However, the finding is consistent with research identifying phonological awareness accuracy as important to word reading development (OÕConnor & Jenkins, 1999; Perfetti et al., 1987). Although the other January sublexical accuracy and fluency points were not uniquely predictive, letter name fluency and letter sound fluency growth were. In the case of letter name fluency, the slowing of childrenÕs rates of growth, represented by the negative quadratic term, indicated that students

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with negative rates of growth had higher word reading skill in May. Although counterintuitive, it is likely that slowing rates of growth indicate that these children had mastered this lower level skill and reached asymptote while others continued to develop competence through the end of the school year. Unlike letter name fluency growth, letter sound fluency growth was positively related to literacy outcomes. Children with higher rates of growth had stronger word reading skills (see correlations, Table 3 and b weights, Table 6). 4.2.2. Spelling More variables were uniquely predictive of spelling possibly due to the lack of an autoregressor. Letter sound accuracy, elision, and phoneme segmentation fluency were uniquely related to spelling proficiency, and growth in letter sound fluency was the only unique growth variable. We hypothesized that sublexical fluency would account for more variance than accuracy measures while, in fact, both the accuracy and fluency measures were uniquely predictive of spelling. The hypothesis requires modification since some accuracy measures maintain their predictive importance and the standardized beta weights (see Table 6) were of similar magnitude. The new finding is that growth in fluency uniquely accounted for significant variance in both literacy outcomes. It may be that growth in sublexical accuracy also contributes to early literacy, a possibility that requires further research. 4.2.3. Reader group differences The relationship between sublexical fluency growth and word reading development was explored further in the comparisons of three groups of beginning readers. Differences in initial proficiency (intercept) and growth differentiated students who could read from students who could not. For letter name fluency and phoneme segmentation fluency, these differences were primarily related to beginning skills (see Figs. 1 and 3). However, for letter sound fluency (see Fig. 2), there were significant differences in both beginning proficiency and growth between groups of children who learned to read by May (Emerging Readers) and those who did not (Prereaders). Emerging Readers had a rate of growth considerably greater than Prereaders (Emerging ReadersÕ slope = 5.01, PrereadersÕ slope = 3.00 per three week interval). Combined with differences in beginning proficiency (Emerging Readers identified nearly twice the number of letter sounds per minute), students who learned to read during the second half of kindergarten differed in letter sound fluency growth. One limitation is that these groups were defined using an arbitrary cut-off. They do, however, represent three educationally-relevant groups of kindergarten children: those who can already read words, those who learn to read words, and those who still do not read words in kindergarten. Future investigations should consider the criteria by which reader groups are defined. While the analysis does not provide evidence of causality, this finding provides preliminary support of the importance in letter sound fluency growth in learning to read. 4.3. Interrelationships among sublexical fluency growth variables The significant role of sublexical fluency in the development of early literacy skills prompts the analysis of how these skills interrelate. As would be expected, the significant contribution of accuracy to fluency was confirmed. For each sublexical fluency measure, the accuracy counterpart was positively related to beginning skill level (e.g., letter sound accuracy in January predicts letter sound fluency level in January). However, accuracy was not the only variable that contributed to the development of sublexical fluency. It

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was also the case that sublexical fluency in one skill contributed unique variance to the January level of another sublexical fluency skill. Letter name fluency predicted letter sound fluency; letter sound fluency predicted both letter name and phonemic segmentation fluency, and phonemic segmentation fluency predicted letter sound fluency. This pattern suggests letter sound fluency has a central role in precursor literacy skills. With respect to predicting growth, the accuracy measures were never uniquely predictive. Instead, growth in one sublexical fluency skill correlated with growth in another fluency skill. Letter sound fluency growth uniquely predicted both letter name and phonemic segmentation fluency growth, which strengthens the conjecture about the central role of letter sound fluency. These findings replicate and extend bi-directional relationships identified for accuracy measures of sublexical skills (e.g., Burgess & Lonigan, 1998; McBride-Chang, 1999; Wagner et al., 1994). Interestingly, January word reading scores only predicted the letter name fluency quadratic term. Children who read more words in January tended to have slower growth in letter name fluency at the end of the year most likely because they had reached a ceiling in this lower level skill. Importantly, studentsÕ beginning proficiency did not uniquely predict studentsÕ rate of growth in letter name fluency, letter sound fluency, and phoneme segmentation fluency. Development of these skills is related to entering proficiency, but growth provides variance that is independent of initial skill. This is evident in the variability associated with growth rates, as indicated by the random slope parameter (see Table 5) and relatively weaker correlations between level and slope estimates (see Table 3) for each fluency skill. For example, the correlation between the first phoneme segmentation fluency assessment and rate of growth is 0.42. This also may explain the relatively low reliability over time for this sample (e.g., for PSF r = .73–.82 across three-week intervals). If studentsÕ rates of growth were determined by their beginning level, one would expect higher (r = .90 range) reliability estimates. Lower coefficients suggest that children exhibit rates of growth that are not predicted by initial skill level. This implies that measuring proficiency at a single time in the kindergarten year may yield insufficient information about studentsÕ subsequent development and strengthens the rationale for systematic progress monitoring of foundational reading skills (Good et al., 2001). In any event, the current findings suggest that letter sound fluency for reading and phonemic segmentation fluency for spelling are appropriate and valid progress monitoring tools and capable of capturing growth in kindergarten children. This recommendation may be limited to reading curricula that are similar to the one experienced by this sample. 4.4. Limitations and directions for future research There are several limitations that should be taken into consideration when interpreting these findings and setting directions for future sublexical research. This study was conducted in classrooms where students received explicit instruction in sublexical skills. These findings may not generalize to other instructional settings or reading curricula. However, one might still expect that other kindergarten children would develop sublexical fluency, even in classrooms with less systematic reading instruction. Some support for this expectation was provided by Speece et al. (2003) who found that letter sound fluency accounted for unique variance in both the prediction of concurrent kindergarten word reading skills and first grade oral reading fluency skills in a sample of kindergarten children who did not receive explicit instruction in code-based reading.

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ChildrenÕs progress is related to the scope and quality of classroom instruction. We observed classroom instruction and interviewed teachers to provide descriptive information about the nature of reading instruction. We did not examine the role of classroom instructional variables in predicting literacy skills and, thus, cannot specify their effect. Observation of classroom instruction and the specificity of the reading curriculum suggest that the instructional environments for these students were more similar than different. Examination of the effect of curriculum, instructional, and teacher differences on the development of sublexical skills are important extensions of the current study. A second limitation of this study is the exclusion of repeated assessment of sublexical accuracy and analysis of accuracy growth. It also would be important to include measures of sublexical accuracy over time to observe patterns of growth and the contribution to literacy development. It may be that growth in sublexical accuracy would emerge as important as or more important than growth in sublexical fluency. Related, extending the present design to include analysis of reading outcomes (timed and untimed) through first grade would provide a perspective on how sublexical skills contribute to the development of fluency with connected text. Regarding the relative importance of accuracy and fluency, a more fine-grained analysis would be possible through a discrete trial method that would allow inspection of accuracy, speed, and fluency. 5. Summary and implications Analyses of the correlates of early literacy routinely include accuracy measures with no attention to the potential of fluency measures. Similar to assumptions that word reading fluency is a later developing skill, most informed observers would likely suggest that sublexical fluency, if important at all, also develops later. The results of this study challenge this assumption. Sublexical fluency skills demonstrate growth in kindergarten, are linked in important ways to word reading and spelling, and are mutually supportive. Also, they contribute unique variance when accuracy counterpart measures are in the model. These findings support our theoretical perspective that sublexical fluency operates to free cognitive resources required for accurate word identification and word spelling (Fredericksen et al., 1985; Walsh et al., 1988). Sublexical fluency appears to support childrenÕs earliest efforts to decode and encode in untimed formats. Experimental training studies would be important to test further this hypothesis. In sum, beginning word reading and spelling development is a complex phenomenon that defies a simple explanation. Sublexical accuracy, sublexical fluency, and growth are interrelated, dynamic, and vary across students. Further research on the evolution and contribution of sublexical accuracy and fluency skills is necessary to understand early literacy development. References Adams, M. J. (1990). Beginning to read: Thinking and learning about print. Cambridge, MA: MIT Press. Aimsweb (2004). Early literacy growth tables [website]. Retrieved September 13, 2005. . Berninger, V., Abbott, R., Billingsley, F., & Nagy, W. (2001). Processes underlying timing and fluency: Efficiency, automaticity, coordination, and morphological awareness. In M. Wolf (Ed.), Dyslexia, fluency, and the brain (pp. 383–414). Baltimore: York Press. Biemeller, A. (1977–1978). Relationships between oral reading rates for letter, words, and simple text in the development of reading achievement. Reading Research Quarterly, 13, 223–253.

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