Diversity among Spanish-speaking English language learners: profiles of early literacy skills in kindergarten

Diversity among Spanish-speaking English languagelearners: profiles of early literacy skills in kindergarten

Karen L. Ford • Sonia Q. Cabell •

Timothy R. Konold • Marcia Invernizzi •

Lauren B. Gartland

Published online: 12 July 2012

� Springer Science+Business Media B.V. 2012

Abstract This study explored heterogeneity in literacy development among 2,300

Hispanic children receiving English as a Second Language (ESL) services at the

start of kindergarten. Two research questions guided this work: (1) Do Spanish-

speaking English language learners receiving ESL services in the fall of kinder-

garten demonstrate homogeneous early literacy skills, or are there distinct patterns

of achievement across measures of phonological awareness, alphabet knowledge,

and orthography? and (2) if there are distinct profiles, to what extent do they predict

literacy achievement at the end of kindergarten and the beginning of first grade?

Using cluster analysis, the authors identified four distinct literacy profiles derived

from fall kindergarten measures of phonological awareness, alphabet knowledge,

and phonetic spelling. These profiles were found to be associated with literacy

outcomes in spring of kindergarten and fall of first grade. The two profiles that were

associated with greater success on later measures of concept of word in text, letter

sound knowledge, word reading, and spelling were the two that included stronger

performance on orthographic skills (i.e., alphabet knowledge and phonetic spelling).

These findings demonstrated that there is heterogeneity among Hispanic ESL stu-

dents at kindergarten entry and suggested that literacy instruction must be differ-

entiated from the very beginning in order to meet students’ individual needs. The

findings also suggested that orthographic skills should be assessed and taught early

on. While phonological awareness may be a necessary precursor to reading, pho-

nological awareness in the absence of orthographic skills may not be sufficient.

Keywords English language learners � Spanish–English bilinguals � Reading

development � Literacy profiles � Cluster analysis

K. L. Ford (&) � S. Q. Cabell � T. R. Konold � M. Invernizzi � L. B. Gartland

Curry School of Education, University of Virginia, P.O. Box 800785, Charlottesville,

VA 22908-8785, USA

e-mail: [email protected]

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Read Writ (2013) 26:889–912

DOI 10.1007/s11145-012-9397-0

Introduction

Much attention has been given to the achievement gap that exists between Hispanic

English language learners (ELLs) and their native English-speaking peers. Hispanic

ELL students as a group have consistently scored lower than native English

speakers on the National Assessment of Educational Progress (NAEP) (National

Center for Education Statistics [NCES], 2010), and they have the highest school

dropout rate of any group in the nation (NCES, 2007). This disparity in achievement

is well documented and presents a very real concern for all who are dedicated to

helping these children succeed in school. Nevertheless, this emphasis on the

achievement gap sometimes results in Hispanic ELL students being regarded as a

homogeneous at-risk group, characterized simply by limited English proficiency. It

is likely, however, that Hispanic ELL students exhibit the same variance in content

area skills, including early literacy skills, as native English-speaking students. If

such variance exists, revealing and understanding it could lead to improved literacy

instruction and better learning outcomes for Hispanic ELL students.

There is little doubt that ELL students’ English language proficiency impacts

their reading development. Research has clearly demonstrated the relationship

between first-language (L1) oral language development and emergent literacy skills,

such as print knowledge and phonological awareness, as well as the relationship

between language skills and reading comprehension in elementary school and

beyond (Storch & Whitehurst, 2002). Moreover, delays in language development in

kindergarten have been shown to be associated with later difficulties in both word

reading and reading comprehension (Catts, Fey, Tomblin, & Zang, 2002).

Studies have also demonstrated a relationship between English oral language

development and both word reading (Gottardo, 2002; Quiroga, 2002) and reading

comprehension (Geva, 2006) among ELL students learning to read in English.

Typically, however, English proficiency has been found to account for a relatively

small percentage of the variance in word reading (Geva, 2006). As with English

L1 speakers, oral language likely makes its contribution early on as emergent

literacy skills are being developed, and thus by the beginning of formal schooling,

its effect on word reading is indirect (i.e., through such skills as phonological

awareness) rather than direct (Storch & Whitehurst, 2002). In a longitudinal study

that followed 626 English speaking children from preschool through fourth grade,

Storch and Whitehurst (2002) found that there was a strong relationship between

oral language and early literacy skills in preschool; however, in kindergarten

through second grade, the effect of oral language was found to be mediated by

skills such as phonological awareness and print knowledge. By third and fourth

grade, language came into prominence once again because of its direct relationship

with reading comprehension. These findings are consistent with research with

English language learners. Although the relationship between English language

proficiency and early word reading is usually not found to be robust, multiple

language components, including vocabulary skills, syntactical knowledge, and

listening comprehension, have all been shown to be associated with reading

comprehension among English language learners of elementary-school age

through adulthood (Geva, 2006).

890 K. L. Ford et al.

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Metsala and Walley’s (1998) Lexical Restructuring Model suggests a unique

relationship between English oral language development and reading. According to

this model, in early childhood, when children’s oral lexicons are relatively small,

their lexical representations are largely holistic and based on units larger than

phonemes, such as syllables. As children learn more words, however, representa-

tions become more fine-grained, which allows them to distinguish between the

increasing number of words in their lexicons and to develop the phonemic

awareness necessary for beginning reading. It stands to reason that limited English

vocabulary might cause ELL students to experience an initial delay in developing

the finer lexical representations that support early reading in English. Once ELL

children start school, however, they tend to develop age-appropriate social English

relatively quickly (Cummins, 1979). Since texts for beginning readers by design

include only vocabulary that would be in the lexicon of a typical kindergartner or

first grader, it may be that many ELL students are able to develop sufficient

vocabulary to support early reading by the time they begin reading instruction. By

third grade, however, when comprehension of more sophisticated texts places

greater language demands on the reader, ELL students often begin to experience

difficulty.

Thus, although oral language skills are clearly foundational for children’s early

literacy learning, evidence suggests that language ability pays bigger dividends to

reading later in the developmental process when the characteristics of texts place

greater demands on the reader for comprehension (Lindsey, Manis, & Bailey, 2003;

Storch & Whitehurst, 2002). Moreover, although early language and literacy skills

are interrelated (Catts & Kamhi, 2005; Storch & Whitehurst, 2002), children require

different kinds of instruction to support development in these two areas. For

example, the instruction provided to support children’s language development is

very different from that designed to improve early decoding skills, and children who

may require intensive literacy support may not always have the poorest language

skills (e.g., Cabell, Justice, Konold, & McGinty, 2011; Lesaux & Geva, 2006).

Currently, however, decisions regarding early literacy instruction for ELL students

are often guided by students’ English language proficiency rather than by their

specific literacy needs. In many cases, ELL students receive most or all of their

literacy instruction in their English as a Second Language (ESL) classes. In ESL,

instruction is entirely in English. Some schools follow a ‘‘pull-out’’ model, in which

students leave the mainstream classroom to work with an ESL teacher in small groups.

Other schools use a ‘‘push-in’’ model, in which the ESL teacher joins the mainstream

classroom to support ELL students as they participate in classroom activities with

other students. In a study that examined instructional practices among 164 ESL

teachers in 16 school divisions across the Commonwealth of Virginia (Bowerman,

2007), ESL teachers reported among their daily routines activities related to guided

reading, reading comprehension, writing, spelling, reading fluency, decoding, and

read-alouds, in addition to oral language and vocabulary. Literacy instruction was

most often reported as undifferentiated and offered in whole-group formats.

Although placement in ESL services varies from state to state, it is almost

uniformly based on tests of English oral proficiency (Ragan & Lesaux, 2006). Thus,

literacy instruction may be differentiated by language proficiency level without

Early literacy ELL profiles 891

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considering strengths and weaknesses in foundational literacy skills. This practice

could very well place these students at additional risk for reading difficulties if there

are significant differences in literacy development among Hispanic ELL students

who are classified at the same level of English language proficiency. To design

instruction that will effectively meet students’ needs, teachers must understand their

progress toward developing specific foundational literacy skills. The first step is

determining whether there is, indeed, the same level of heterogeneity among

Hispanic ELL students as there is among monolingual English speakers.

Research has demonstrated this heterogeneity both in overall literacy develop-

ment and in development of specific literacy skills in the English-speaking

population in kindergarten and first grade (Connor, Morrison, & Katch, 2004;

Kaplan & Walpole, 2005). Research has also shown differential effects for type of

instruction, based on specific student literacy profiles (Connor et al., 2004). For

example, Kaplan and Walpole (2005) employed latent transition analysis to define

five latent classes, representing various combinations of skills related to alphabet

knowledge, phonological awareness, and word reading. They were then able to

determine the likelihood that children in each of these latent classes would transition

from lower to higher developmental literacy stages during three specific time

periods (i.e., fall kindergarten to spring kindergarten, spring kindergarten to fall first

grade, and fall first grade to spring first grade). Connor et al. (2004) also

demonstrated differences in fall literacy profiles among English-speaking first

graders and further found that matching instructional activities to these profiles

resulted in greater achievement in decoding skills over the first-grade year. It is

likely that this same scenario exists among Hispanic ELL students, even at

kindergarten entry, due to such factors as English language proficiency and

preschool attendance. As discussed above, English language proficiency has a

strong relationship to emergent literacy development during the preschool years.

Research has also demonstrated differential benefits of preschool attendance in

general on early literacy skills, especially for Hispanic students (Huang, Invernizzi,

& Drake, 2012). The benefits to early literacy are most pronounced at kindergarten

entry and appear to persist through first grade. If Hispanic ELL students indeed

prove to be a heterogeneous group, even at kindergarten entry, the practice of

delivering early literacy instruction in ESL classes that are grouped solely according

to English language proficiency may be misguided.

Foundational literacy skills

Research supports the importance of phonological awareness, alphabet knowledge,

and orthographic knowledge as predictors of English literacy development, both for

native speakers (Catts, Fey, Zhang, & Tomblin, 2001; Scarborough, 1998, 2000)

and for ELL students (Chiappe, Siegel, & Wade-Woolley, 2002; Lesaux, Koda,

Siegel, & Shanahan, 2006). Phonological awareness may be defined as the ability to

attend to and reflect on the sounds of oral language, such as syllables, rhymes, and

onsets. Early phonological awareness skills include the ability to identify words that

rhyme or begin with the same sound. The latter, often referred to as phoneme


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awareness, a subset of phonological awareness, is particularly predictive of early

literacy development (Hulme et al., 2002). Alphabet knowledge includes both

alphabet recognition (i.e., the ability to identify by name the letters of the alphabet)

and letter-sound knowledge (i.e., the ability to identify the sounds that particular

letters make). Orthographic knowledge refers to knowledge about words in their

written form and includes the application of grapheme-phoneme correspondences as

well as an awareness of allowable and unallowable spelling patterns within a

language (e.g., qu is an acceptable letter combination in English, but qg is not).

Orthographic knowledge also includes awareness of morphemes or meaning units in

semantically related words (e.g., hid, hide, hidden). Children who have developed

skills in these three domains by the end of kindergarten, either in English or in

another alphabetic language, are likely to experience success in learning to read in

English (Durgunoglu, Nagy, & Hancin-Bhatt, 1993; Hammill, 2004; Lesaux &

Siegel, 2003; Scarborough, 1998).

Although research has demonstrated that phonological awareness, alphabet

knowledge, and orthographic knowledge are inter-related (Schatschneider, Fletcher,

Francis, Carlson, & Foorman, 2004; Warley, Landrum, Invernizzi, & Justice, 2005),

the relative importance of skills within these domains tends to change once formal

literacy instruction begins. As children start to develop a more sophisticated

understanding of written language, knowledge of the writing system quickly

replaces sound-related skills as the most accurate predictor of later reading

achievement (Hammill, 2004; Scarborough, 1998). Research has shown, for

example, that from fall to spring of the kindergarten year, print-related skills replace

phonological awareness skills as more robust predictors of reading achievement one

and two years later (Morris, Bloodgood, & Perney, 2003b; Warley et al., 2005).

Nevertheless, the combination of phonological awareness, alphabet knowledge,

and orthographic knowledge provides a more ecological and comprehensive view of

literacy achievement than any single measure alone because acquiring the

alphabetic principal requires the melding of all three. The alphabetic principle,

defined as the understanding that written words are composed of letters that

represent speech sounds and that the systematic relationship between letters and

sounds can be used to retrieve the pronunciation of printed words, is generally

accepted as a universal prerequisite for learning to read an alphabetic orthography

(Liberman, Shankweiler, & Liberman, 1989). Thus, even though individual

variables in each of these domains are accurate predictors of reading achievement,

constructs that include multiple variables considered together tend to be more

powerful in predicting reading outcomes than any single variable alone (Morris,

Bloodgood, Lomax, & Perney, 2003a; Scarborough, 1998). Schatschneider et al.

(2004), for example, demonstrated that three variables (phonological awareness,

letter sound knowledge, and rapid automatized naming of letters), measured in fall

or spring of kindergarten, together accounted for more variance in first- and second-

grade reading outcomes than any single variable alone.

In a similar study with Spanish-speaking ELL students, Manis, Lindsey, and

Bailey (2004) found that four variables (print knowledge, expressive language,

phonological awareness, and rapid naming of objects), measured in Spanish at the

end of kindergarten, together accounted for 26.3 % of the variance in second-grade


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letter-word identification in English. Print knowledge, which included knowledge

about print concepts and letter names and sounds, was the strongest single predictor,

explaining 19 % of the variance in letter-word identification; however, each of the

other variables also explained a statistically significant portion of the variance. Taken

together, research on the importance of phonological awareness, alphabet knowledge,

and orthographic knowledge as predictors of successful English literacy development

for native speakers and Hispanic ELL students suggests that multiple measures are

better than single measures and that the predictive power of these measures shifts

gradually over time from phonological awareness to print-related skills.

Empirical profiling of English language learners’ early literacy skills

The existing research base on English literacy development among Spanish-

speaking ELL students has primarily focused on variable-centered approaches, such

as those described above. Variable-centered approaches to data analysis focus on

relationships among variables with the goal of predicting outcomes. Although these

approaches provide valuable information about the types of early literacy skills that

predict success for ELL students, they can potentially mask important subgroups

within the population that could be expected to be more or less at risk for reading

difficulty (Konold & Pianta, 2005). In contrast, person-centered approaches to data

analysis focus on relationships among individuals with the goal of identifying

categories in which members are similar to each other but different from others in

other categories. Person-centered approaches are also useful in analyzing longitu-

dinal data to explore heterogeneity in developmental trajectories (Muthen &

Muthen, 2000). Despite the potential usefulness of person-oriented approaches,

there are few, if any, published person-centered studies that examine profiles of

early literacy skills among Spanish-speaking ELL students entering kindergarten.

In this study, we use cluster analysis to explore the heterogeneous nature of ELL

students’ literacy development and to identify profiles of children that display

similar patterns of strengths and weaknesses across multiple constructs of early

literacy: phonological awareness, alphabet knowledge, and orthographic knowl-

edge. Unlike procedures that reflect variation in single variables, cluster analysis

accounts for the full network of relationships among multiple variables (Sternberg,

1984) and can provide greater insight into early literacy development. The use of

cluster analysis could be an important methodological and conceptual advance in

research on second-language literacy because it describes within-group variability

rather than treating ELL students as a homogeneous group.

Purpose of the present study

The purpose of this study was to examine the within-group individual differences of a

Spanish-speaking ELL population. We use cluster analysis to identify profiles across

children’s early literacy skills and explore the extent to which these profiles predict

the achievement of early literacy milestones at the end of kindergarten and the

beginning of first grade. We address two major questions: (1) Do Spanish-speaking


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ELL students receiving English as a Second Language (ESL) services in the fall of

kindergarten demonstrate homogeneous early literacy skills, or are there distinct

patterns of achievement across measures of phonological awareness, alphabet

knowledge, and orthography? and (2) If there are distinct profiles, to what extent do

they predict early literacy milestones at the end of kindergarten and the beginning of

first grade? Based on research on native English-speaking children’s varying abilities

at kindergarten entry (Dickinson & Neuman, 2006; Snow, Burns, & Griffin, 1998), we

hypothesized that several different core profiles would emerge, reflecting different

patterns of early literacy development. Further we hypothesized that differential

profiles would be weakly related to demographic characteristics such as age, gender,

and socio-economic status (SES) and more strongly related to preschool attendance

and English oral proficiency.

We cross-validated the measures used to establish the fall profiles by incorporating

both internal and external validity into the analytic method. Internal validity was

addressed by demonstrating the tightness of individual clusters (internal cohesion)

and the distance between clusters (external isolation). External validity was addressed

by comparing children within clusters to children in other clusters on early literacy

measures external to the derivation of the profiles. The first milestone used to validate

the fall kindergarten profiles at the end of kindergarten was PALS-K Concept of Word

in Text (COWT). COWT has been described as a ‘‘pivotal event’’ in the development

of early reading that requires the application of beginning sound awareness, automatic

recognition of letters and letter-sounds at the beginning of word boundaries, and the

ability to coordinate these skills to finger point accurately to words in a printed text

representing a memorized rhyme (Flanigan, 2007). Some experts argue that COWT is

the closest approximation to reading of any of the early literacy skills (Morris et al.,

2003). The milestone used to validate the fall kindergarten profiles in the fall of first

grade was the PALS 1–3 first-grade composite score, made up of word recognition of

beginning first-grade words, letter sounds, and a qualitative spelling assessment that

inventories specific phonics features associated with successful beginning reading,

including: beginning and ending consonants, consonant digraphs and blends, short

vowels, etc. The first-grade composite does not include contextual reading or

comprehension since many first graders are unable to read at the very beginning of the

year. The National Center for Response to Intervention rates the evidence for

classification accuracy, reliability, and validity of the PALS 1–3 as ‘‘convincing’’ with

moderately-high ratings for generalizability based on these composite scores

(http://www.rti4success.org/screeningTools/). By the end of first grade, when more

children have become readers, contextual reading and reading comprehension would

be more important.

Method

Participants

This study sampled children from a longitudinal archival database representing the

literacy scores of 98 % of the total population of children in Grades K-3 in the state


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http://www.rti4success.org/screeningTools/

of Virginia (n = 79,169). Children were included based on the following criteria,

using data gathered during the 2007–2008 school year: (a) They were designated

Hispanic1 by their parents during kindergarten registration, (b) they received ESL

services in kindergarten,2 (c) they had no diagnosed disabilities, and (d) they had a

complete data set for fall of their kindergarten year.

Participants were 2,351 children (49 % females, 51 % males) attending

kindergarten in 436 Virginia public schools. The average age in the fall of

kindergarten was 69 months (SD = 4.6). Based on data entered into a secure,

statewide Internet database (http://pals.virginia.edu) and verified by the Virginia

Department of Education, very few children in the sample (6 %) received supple-

mental reading support (e.g., Title I services) in addition to their classroom

instruction, and 48 % of children had attended preschool the previous year (30 %

unreported).

General procedures

Children were administered the Phonological Awareness Literacy Screening (PALS)

for kindergarten (PALS-K, Invernizzi, Juel, Swank, & Meier, 2007a) in the fall and

spring of kindergarten, and PALS for grades 1–3 in the fall of first grade (PALS 1–3,

Invernizzi, Meier, & Juel, 2007a). During a four-week testing window, the

assessment was administered by classroom teachers in a familiar, quiet setting.

Total time for the assessment was approximately 30–40 min per child. PALSassessments do not require extensive training for teachers. Training videos, online

streaming footage related to each subtask, and clear, accessible teachers’ manuals

are provided, and previous studies have documented a high degree of inter rater

reliability when teachers administer the assessment (Invernizzi, Justice, Landrum, &

Booker, 2004). An online score entry reporting system allows teachers to enter

children’s scores into an encrypted, password-protected database via the Internet.

The reliability of online score entry is regularly checked against a randomly selected

sample of original, hand-scored protocols (see Invernizzi, Swank, Juel, & Meier,

2007b).

Measures

The ELL profiles were derived from five PALS-K fall measures, representing three

constructs: (1) phonological awareness, (2) alphabet knowledge, and (3) ortho-

graphic knowledge. Two additional measures were used to determine the external

and predictive validity of the profiles. The technical adequacy of both PALS

1 Hispanic is one of nine ethnicities available for parents to choose at kindergarten registration. The

Commonwealth of Virginia does not collect information on the country of origin, but recently published

U.S. census data indicate that 22 % of Hispanics in Virginia identify themselves as Mexican, 13 % as

Puerto Rican, 3 % as Cuban, and 63 % as ‘‘other Spanish/Hispanic/Latino (www.census.gov/population/

www/cen2000/briefs.html).’’2 At the time of this study, assignment to ESL services was based primarily on scores on the Stanford

Test of English Proficiency (SELP), in some cases supplemented by additional assessments chosen by

individual schools and/or school divisions.


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http://pals.virginia.edu

http://www.census.gov/population/www/cen2000/briefs.html

http://www.census.gov/population/www/cen2000/briefs.html

instruments has been demonstrated through piloting, field testing, and ongoing

statistical analyses of assessment scores in the PALS database. Inter-rater reliability

is reported to be stable for all tasks (r = .96–.99). Content validity was supported

through the use of advisory and review panels, and criterion-related validity was

deemed adequate through examination of both concurrent and predictive validity.

Internal consistency (Cronbach’s alpha) for Hispanic children ranged from .82 to

.89 on PALS-K tasks across 6 years (Invernizzi et al., 2007b) and from .82 to .84 on

PALS literacy composite scores across 2 years (Invernizzi, Meier, & Juel, 2007b).

Concurrent and predictive validity for PALS-K has been established using the

Stanford-9 and the Stanford-10, and the National Center on Response to

Intervention (2010) rates the disaggregated reliability, validity, and classification

accuracy for diverse populations as ‘‘convincing’’ (http://www.rti4success.org/

screeningTools).

Cluster identification variables (fall of kindergarten measures)

Phonological awareness and orthographic knowledge

The PALS-K Beginning Sound Awareness and Rhyme Awareness tasks measured

phonological awareness in English. For the Beginning Sound Awareness task,

children were presented with a target picture (e.g., fish) next to a row of three

additional pictures (e.g., mop, bell, fence). The teacher named each picture as

children compared it to the target. Children identified the picture that shared the

same beginning sound as the target (maximum score = 10). No initial sounds were

used that do not also exist in Spanish. The PALS-K Rhyme Awareness task followed

a similar administrative procedure on a different day. Children were shown a target

picture (e.g., sun) next to a row of three additional pictures (e.g., mop, run, ball) and

were asked to identify the picture that rhymed with the target (maximum

score = 10). The PALS-K Phonetic Spelling task measured children’s early

attempts at phonetic spelling, which encompasses both orthographic knowledge

and phonological awareness. For this task, children spelled five words with a

consonant–vowel-consonant (CVC) pattern. The teacher modeled writing the

sounds heard in the word mat and then asked children to spell fan, pet, rug, sit, and

mop. Points were awarded for providing phonetically acceptable representations of

each sound in a word (i.e., beginning, middle, and ending sounds), an aspect of

scoring that captures phoneme segmentation in addition to phoneme-grapheme

correspondences. Another point was given for each word spelled conventionally

(maximum score = 20), an aspect of scoring that relates to awareness of the CVC

structure of short vowels in English orthography.

Alphabet knowledge

Alphabet knowledge was measured using the Lower-Case Alphabet Recognition

task and the Letter Sounds task. For the Lower-Case Alphabet Recognition task, the

child pointed to and named each of the 26 letters of the alphabet, presented in

random order on a single 8- by 11-inch page (maximum score = 26).


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http://www.rti4success.org/screeningTools

http://www.rti4success.org/screeningTools

For the Letter Sounds task, the child produced the sounds of 23 upper-case letters

and 3 digraphs (sh, th, ch), presented in random order on a single 8- by 11-inch page

(maximum score = 26). The child was encouraged to provide the most common

sounds for ambiguous letters (i.e., the lax, or short, sounds for vowels and the hard

sounds for the letters c and g). Three letters were not included in the task: The letter

M was omitted because it was used as an example, and X and Q were eliminated

since neither can be pronounced in isolation.

Given that the scaling of variables entering a clustering algorithm can influence

their relative contributions in the final solution, all PALS-K measures were

standardized to the same T-score metric (M = 50; SD = 10) prior to analyses.

External/predictive validity variables

Concept of word in text

The individually administered PALS-K Concept of Word in Text task requires

children to integrate their knowledge of phonological awareness, alphabet

knowledge, and orthographic knowledge as they match spoken language to the

printed words in a memorized text. Using picture support, the teacher first helped

the child memorize a short rhyme (e.g., Little Bo Peep). Once the child could

accurately recite the rhyme from memory, the teacher presented the printed version

of the rhyme and modeled finger point reading by pointing to each word while

reciting it. The teacher then engaged the child in choral and echo reading of the text

to further demonstrate the process of fingerpoint reading. In the assessment phase of

the task, the child was asked to ‘‘read’’ the rhyme while pointing to each word in the

text (the Pointing subtask). One point was awarded for each line of text in which the

child accurately pointed to each word while reciting the poem (maximum score = 5

points). Next, the teacher pointed to 10 target words within the text and asked the

child to identify them (the Word Identification in Context subtask; maximum

score = 10). Finally, the child was shown a list of 10 words from the rhyme,

presented in random order, and was asked to identify each one (the Word List

subtask; maximum score = 10). Scores from the three subtasks were then summed

to create the COWT total score (maximum total score = 25).

First-grade literacy composite

The first-grade literacy composite is made up of three tasks from PALS 1–3:

Word Recognition, Spelling, and Letter Sounds (see description above). For the

Word Recognition task, children were asked to read a list of twenty words from

a beginning-first-grade word list (maximum score = 20). Children were encour-

aged to read the words without stopping to ‘‘sound out.’’ The first-grade Spelling

task differed from the kindergarten Phonetic Spelling task in that children spelled

a list of words carefully selected to represent phonics features usually learned in

first grade (e.g., beginning and ending consonants, blends and digraphs, medial

short vowels, and the silent e long vowel marker). In a group setting, the teacher

called out each word, along with a sentence using the word in context. Children


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received one point for each correctly spelled phonics feature plus an additional

point if they spelled the entire word correctly (maximum score = 44). To create

the literacy composite score used in the current study, scores from the Word

Recognition in Isolation, Spelling, and Letter Sounds tasks were summed

(maximum score = 90).

Results

Table 1 presents descriptive statistics related to early literacy skills, namely

phonological awareness, alphabet, and orthographic knowledge, for the ELL sample

in the current study, as well as for a statewide sample consisting of all children who

were administered PALS tasks in Virginia during the three targeted time periods

(i.e., fall of kindergarten, spring of kindergarten, and fall of first grade). The

Spanish-speaking ELL students in our sample collectively scored lower across all

measures of early literacy when compared with the average performance reported

for children in Virginia. In the fall of their kindergarten year, the ELL students, on

average, named approximately 12 lowercase letters, produced seven letter sounds,

and demonstrated above-chance phonological awareness ability. In addition,

spelling assessment scores indicated that the average child in the sample was using

only beginning sounds to spell CVC words. However, the large standard deviations

and wide ranges across measures indicate that there was much variability in the

early literacy skills within the sample. For example, children’s phonetic spelling

ability in the average range (i.e., within 1 SD of the mean) varied from children not

representing any sounds in words to children spelling with both beginning and

ending sounds. Moreover, the actual range indicated that some children in the

sample were able to correctly spell all CVC words on the assessment in the fall of

kindergarten.

Table 1 Raw score descriptive statistics: ELL sample and statewide sample

Variable ELL samplea Statewide sampleb

M SD Range M SD Range

1. Beginning sounds 5.5 3.0 0–10 7.4 2.8 0–10

2. Rhyme awareness 5.9 2.8 0–10 8.0 2.7 0–10

3. Letter-name knowledge 12.5 9.2 0–26 19.0 7.7 0–26

4. Letter-sound knowledge 6.7 7.2 0–26 12.5 7.9 0–26

5. Phonetic spelling 3.5 4.4 0–20 7.3 6.0 0–20

6. Concept of word in text 17.8 7.1 0–25 20.4 6.0 0–25

7. Literacy composite 50.1 15.5 0–89 57.1 15.78 0–90

The statewide sample represents all Virginia children who were administered PALS tasks in each of the

three targeted time periods (i.e., fall of K, spring of K, and fall of 1st grade)a n = 2,300 for variables 1–5; 2,143 for variable 6; and 1,549 for variable 7; b N = 77,193 for variables

1–5; 77,617 for variable 6; and 60,999 for variable 7


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Table 2 provides the correlations among the Fall-K, Spring-K, and Fall-1st grade

variables. The Fall-K measures used to form the clusters were moderately to highly

correlated (r = .43–.79). These measures were also moderately correlated with

Spring-K Concept of Word in Text and the Fall-1st grade literacy composite

(r = .33–.48), with the following exception. Fall-K letter-name knowledge was

highly correlated with Spring-K and Fall-1st scores (r = .54 and .52, respectively).

Cluster analysis

The clustering strategy we adopted was similar to the one used elsewhere for

identifying normative profiles (Glutting, McDermott, & Konold, 1997; Konold &

Pianta, 2005), as detailed in McDermott (1998). This procedure involved three

steps. In the first step, the total sample (n = 2,351) was randomly divided into four

approximately equal sub samples and Ward’s (1963) hierarchical-agglomerative

procedure was performed on a Euclidean distance matrix that is sensitive to level,

shape, and scatter. Decisions regarding the number of clusters to retain within each

of the four samples were based on a number of indices: pseudo-F (Calinski &

Harabasz, 1985), pseudo t2 (Duda & Hart, 1973), and R2. This step also utilized a

‘‘trim’’ procedure that removed a maximum of 2 % of the outlier cases from

consideration in the analysis (McDermott, 1998). Consequently, 51 cases were

eliminated, resulting in 2,300 children assigned to cluster membership.

Information from the clusters identified in Step 1 was pooled to form an overall

similarity matrix that was used for Step 2. Thus, Step 2 clustering began with a

proximity matrix whose diagonal elements held error sums of squares (ESS) statistic

values for respective Step 1 clusters, with off-diagonal elements corresponding to

potential ESSs for merging each pair of first-stage clusters. Ward’s method was

employed on the resulting similarity matrix from Step 1 to assess the extent to

which cluster profiles from sub samples of the data matched those found for the total

sample (i.e., replication). Each of the aforementioned statistical indices was again

considered when determining how many clusters to retain at Step 2. Steps 1 and 2

led to the identification of four clusters. All clusters yielded replication rates of

Table 2 Intercorrelations: cluster identification and external/predictive validity variables

1 2 3 4 5 6 7

1. Beginning soundsa _ .58* .53* .57* .58* .44* .40*

2. Rhyme awarenessa _ .44* .45* .46* .40* .33*

3. Letter-name knowledgea _ .79* .64* .54* .52*

4. Letter-sound

knowledgea_ .73* .48* .48*

5. Phonetic spellinga _ .42* .43*

6. Concept of word in textb _ .70*

7. Literacy compositec

a Fall kindergarten (n = 2,300); b spring kindergarten (n = 2,143); c fall 1st grade (n = 1,549)

* p = \.01


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100 % (see Table 3). These replication rates indicate that each of the four Step-2

clusters was also identified in each of the four subsamples of Step 1.

Group centroids from the Step-2 solution served as starting seeds for the stage

three iterative partitioning analysis conducted using K-means passes. This third step

was necessary because hierarchical-agglomerative procedures (Steps 1 and 2) do not

allow subjects to shift clusters after their original assignment, despite the fact that

they may fit better in a different profile later in the solution. By contrast, iterative

partitioning procedures allow subjects to migrate to neighboring clusters, following

Table 3 Early literacy mean score patterns (standard deviations), psychometric properties, and demo-

graphic variables of core clusters

Profile types

Profile 1 Profile 2 Profile 3 Profile 4

Kindergarten literacy variablesa

Beginning sound awareness 62 (4) 53 (7) 51 (6) 39 (6)

Rhyme awareness 60 (6) 53 (8) 52 (7) 40 (6)

Letter names 62 (3) 58 (5) 43 (5) 42 (6)

Letter sounds 66 (6) 54 (7) 43 (3) 42 (3)

Phonetic spelling 66 (9) 51 (6) 45 (4) 43 (3)

Psychometric properties

Prevalence 17.5 % 25.9 % 28.0 % 28.6 %

Independent replication across four blocks 100 % 100 % 100 % 100 %

Internal profile cohesion (H) 0.80 0.77 0.86 0.86

External isolation (Rp) -0.15 0.26 0.27 0.14

Demographic variables

Eligibility for FRPLb 46.5 % 47.5 % 46.2 % 48.2 %

Child genderb

Boys 47.6 % 51.8 % 52.8 % 51.3 %

Girls 52.4 % 48.2 % 47.2 % 48.7 %

Preschool attendanceb

Attended 72.5 % 63.3 % 43.0 % 35.8 %

Did not attend 10.7 % 14.1 % 24.8 % 31.7 %

Unknown 16.9 % 22.7 % 32.1 % 32.6 %

Child age in monthsc 71.1 (5.0) 69.7 (4.7) 68.9 (4.4) 68.1 (4.1)

English proficiency (fall 1st grade)b

Level 1 27.1 % 27.1 % 33.0 % 38.6 %

Level 2 71.1 % 71.6 % 65.6 % 61.0 %

Level 3 \1.0 % \1.0 % \1.0 % \1.0 %

Level 4 \1.0 % \1.0 % \1.0 % 0.0 %

a Means (and standard deviations) rounded to nearest whole number for ease of presentationb Free or reduced-price lunch (FRPL), child gender, preschool attendance, and English proficiency level

percentages within a given profile typec Means (and standard deviations) of child age by profile type


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identification of the number of suspected clusters (Steps 1 and 2), and generally

result in tighter solutions.

Mean profile configurations for the resulting four-cluster solution are presented in

Table 3 and illustrated in Fig. 1. The four profiles represent the natural variation of

Spanish-speaking ELL students on early measures of phonological awareness,

alphabet knowledge, and phonetic spelling and are typical of what we would expect

in the beginning months of kindergarten. Table 3 also provides other psychometric

properties for each profile. The final cluster solution from Step 3 was required to

retain the dual properties of internal cohesion and external isolation (Aldenderfer &

Blashfield, 1984). Both internal cohesion and external isolation address the issue of

internal validity. Internal cohesion refers to the tightness of a cluster, or the

closeness of objects around the cluster centroid. External isolation refers to the

distance between clusters in multivariate space. Thus, subjects within a given cluster

should be similar to one another, whereas clusters composed of homogeneous

individuals should be distinct from one another. The average H coefficient (Tryon &

Bailey, 1970) across profiles satisfied a priori expectations for internal cluster

cohesion C.60 (Average H = .82), thereby providing evidence in support of

homogeneous within-cluster representation. In addition, the average Rp (Cattell

1949) across profiles also satisfied a priori expectation in support of external

isolation \.40 (Average Rp = .21). Descriptions of the four emergent clusters are

provided below.

Fig. 1 Early literacy profile configurations expressed in standardized T-scores. Profile 1: highest earlyliteracy skills (n = 403, prevalence = 17.5 %); profile 2: average phonological awareness and phoneticspelling, strength in alphabet knowledge (n = 596, prevalence = 25.9 %); profile 3: average phonologicalawareness, weakness in alphabet knowledge and phonetic spelling (n = 644, prevalence = 28 %); profile4: lowest early literacy skills (n = 657, prevalence = 28.6 %)


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Patterns of early literacy skills among Hispanic children receiving ESL services

Figure 1 depicts the cluster profiles, representing children’s patterns of performance

in the fall of kindergarten. The clusters were named based on their relative patterns

of early literacy strengths and weaknesses. Clusters were ordered from the highest to

lowest literacy ability.

Cluster 1: Highest early literacy skills (n = 403; prevalence = 17.5 %)

The children in Cluster 1 demonstrated strong literacy performance relative to their

peers, scoring approximately one to one and one-half standard deviations above the

sample mean across skills. On average, children in this cluster exhibited 90 %

accuracy on measures of phonological awareness. They produced 24 letter names

and 18 letter sounds in fall of kindergarten. A mean phonetic spelling score of 11

indicated that on average children spelled CVC words with acceptable phonetic

representations of beginning and ending sounds.

Cluster 2: Average phonological awareness and phonetic spelling, strengthin alphabet knowledge (n = 596; prevalence = 25.9 %)

Cluster 2 was characterized by average phonological awareness and phonetic

spelling, with alphabet knowledge approximately one-half of a standard deviation

above the mean. Children in this cluster performed with 60–70 % accuracy on

phonological awareness tasks and produced 20 letter names and 10 letter sounds in

fall of kindergarten. A mean phonetic spelling score of 4 indicated that, on average,

these children were likely spelling using beginning sounds only.

Cluster 3: Average phonological awareness, weakness in alphabet knowledgeand phonetic spelling (n = 644; prevalence = 28 %)

Children in Cluster 3 demonstrated average performance on phonological awareness

comparable to that of Cluster 2, scoring with 60-70 % accuracy. However, children

exhibited a weakness in alphabet knowledge (one-half to one standard deviation

below the mean), producing only six letter names and two letter sounds in fall of

kindergarten. Phonetic spelling was also weaker than that of children in Cluster 2,

with a mean score of 1, indicating that children did not consistently represent any

sounds while spelling words.

Cluster 4: Lowest early literacy skills (n = 657; prevalence = 28.6 %)

Children in Cluster 4 exhibited relatively low performance in the sample, with

scores on all measures approximately one standard deviation below the mean.

Children in this cluster scored, on average, below chance level on phonological

awareness tasks (i.e., 20–30 % accuracy). They produced five letter names and one

letter sound in fall of kindergarten. Phonetic spelling scores suggested that the

average child in the cluster did not represent any sounds while spelling words.


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Demographic variables

Contrasts between the four clusters were evaluated in terms of differences in

compositions of school-level socioeconomic status (SES), as well as child gender,

preschool attendance, age, and English language proficiency. Children in the study

attended 436 different schools in 91 school divisions across the state of Virginia.

Table 3 reports school-level SES by cluster, calculated as the percentage of students

receiving free or reduced-price lunch (FRPL). Percentages ranged from 46.2 % (Cluster

3) to 48.2 % (Cluster 4). A one-way ANOVA showed that there were no statistically

significant differences in SES between clusters, F(3,2280) = 1.25, p = .29.

The categorical demographic variables of child gender and preschool attendance

were evaluated by contrasting the observed demographic proportions within each

cluster to what would be expected if these characteristics were proportionately

distributed across the four profiles in accordance with their representation in the

total sample. For example, the total sample following the trim procedure used in the

clustering algorithm (n = 2,300) included 51.2 % males and 48.8 % females.

Cluster 1 contained 17.5 % of the total sample (n = 403). Accordingly, we would

expect 51.2 % of the n = 403 to be male, and 48.8 % to be female. Violations of

these hypotheses were evaluated within each cluster. Type I error rates were

controlled through Bonferroni adjustments. Results indicated that gender did not

differ from expectancy across any of the four clusters (all ps [ .05/4 = .013) (see

Table 3). By contrast, the two strongest profiles (i.e., Clusters 1 and 2) contained

statistically more students who had attended preschool than would be expected, and

the two weaker profiles (i.e., Clusters 3 and 4) included statistically fewer than

expected proportions of children who attended preschool (all ps \ .05/4 = .013)

(see Table 3).

A one-way ANOVA showed statistically significant age differences across

clusters, F(3,2296) = 41.26, p \ .01, with the average age declining slightly in

order from Cluster 1 to Cluster 4 (see Table 3). Although Tukey tests revealed these

pair-wise comparisons to be statistically significant, the overall effect size for age

(x2 = .049) was relatively small and indicated that only 4.9 % of the between

cluster differences could be attributed to age.

English language proficiency was compared across clusters, based on a four-level

designation that was used statewide at the time of this study (Level 1 = lowest level

of oral and written proficiency; Level 4 = highest). Language proficiency levels

were provided by the students’ schools and were based on scores on the Stanford

English Language Proficiency Test (SELP, 2007) administered by school personnel

according to standard protocol. For the SELP assessment, p-values provided as a

measure of test difficulty ranged from .78 to .84 across the three primary forms. The

alpha for the entire primary test was .94, indicating acceptable internal consistency.

Criterion validity was established by correlating the SELP and the Stanford

Diagnostic Reading Test (SDRT) given to the same students; the correlations were

strong. The construct validity of the oral proficiency levels was established through

the use of a modified Angoff procedure (Abedi, 2007; Angoff, 1971).

Language proficiency data from fall of first grade were available for 57.5 % of

students in Cluster 1 (n = 232), 69.1 % in Cluster 2 (n = 412), 68.6 % in Cluster 3


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(n = 442), and 65.2 % in Cluster 4 (n = 429). In each of the four clusters, over

98 % of students with available data were designated as either Level 1 or Level 2 in

English proficiency (see Table 3). Chi-square results showed statistically significant

differences in language proficiency between clusters, v2(6) = 19.26, p \ . 01.

(Proficiency Levels 3 and 4 were combined for this analysis to avoid low cell

frequencies). The lowest performing cluster had a higher concentration of students

at the lowest English proficiency level and also had a lower concentration of

students at higher proficiency levels. Despite this difference, however, the overall

effect size for language was very small (x2 = .009), indicating that language

proficiency accounted for less than 1.0 % of the between cluster differences.

External/predictive validity of clusters

To explore the external and predictive validity of our four-cluster solution, we

compared the fall of kindergarten clusters to children’s literacy milestones at two

future time points: (a) spring of kindergarten and (b) fall of first grade.

Spring of kindergarten

Of the 2,300 children who were assigned to a cluster, scores on the Spring-K

Concept of Word in Text measure were available for 2,143 children. The

distribution of children among clusters in this subsample was similar to that in the

total sample: 18.2 % (n = 390), 26.4 % (n = 566), 27.5 % (n = 589), and 29.7 %

(n = 598), respectively. We also compared children for whom spring kindergarten

data were available (n = 2,143) with children for whom these data were unavailable

(n = 157) on the initial Fall-K clustering variables, as well as gender and age. There

were no significant differences between groups on gender, age, or Fall-K rhyme

awareness. Children with available Spring-K scores performed significantly higher

on Fall-K beginning sound awareness, letter names, letter sounds, and phonetic

spelling (all ps \ .01). However, these differences were not substantial; effect sizes

ranged from .23 to .33 (Cohen’s d).

Results of a one-way ANOVA revealed statistically significant differences among

clusters in Spring-K Concept of Word in Text (COWT), F(3,2139) = 272.95,

p \ .001 and demonstrated that 27.6 % of the variance in Spring-K literacy scores

could be attributed to between cluster differences (x2 = .276). Further, post hoc

Tukey tests indicated that all pair-wise comparisons between clusters were statistically

significant, all ps \ .001. As shown in Table 4, COWT scores at this time point

reflected the ordering in the fall clusters, with large effect sizes for differences between

children in Clusters 1 and 3, Clusters 1 and 4, and Clusters 2 and 4.

Fall of first grade

Of the 2,300 children who were assigned to a cluster in the fall of kindergarten, first

grade literacy composites were available for 1,549 children. The distribution of

these children among the four Fall-K clusters also roughly reflected the original

distribution: 17.5 % (n = 306), 25.6 % (n = 449), 28 % (n = 412), and 28.6 %


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(n = 382), respectively. Children for whom data were available in fall of first grade

(n = 1,549) exhibited significantly better performance than children without

available data (n = 751) on all Fall-K clustering variables (all ps \ .001), but

effect sizes were small (d = .21–.37). There were no gender differences, and the

children with available data were slightly older (i.e., less than 1 month).

Results of a one-way ANOVA indicated statistically significant differences

among clusters in the first grade literacy composite, F (3,1545) = 156.84, p \ .001

and demonstrated that 23.2 % of the variance in first-grade literacy scores could be

attributed to between cluster differences (x2 = .232). Post hoc comparisons among

the four clusters revealed statistically significant pair-wise differences between all

groups (all ps \ .01). Effect sizes were similar to those from the spring kindergarten

time point, with differences between disparate clusters resulting in large effect sizes

(see Table 4). The difference in the literacy composite scores between the children

in Clusters 3 and 4 was less pronounced in fall of first grade (d = 0.22) than in

spring of kindergarten.

Upon closer examination of the component skills tested within the literacy

composite, significant differences between all clusters in the expected order were

evident for word recognition, spelling, and letter sounds (all ps \ .001), with the

exception of Clusters 3 and 4. Children in Cluster 3 significantly outperformed

children in Cluster 4 only in the area of spelling; there were no differences between

these clusters on word recognition and letter sounds (see Table 5).

Table 4 Spring of kindergarten and fall of first grade literacy means (standard deviations) by cluster and

results of post hoc tests

Cluster 1 Cluster 2 Cluster 3 Cluster 4 Post hoc Effect sizes (d)

M (SD) M (SD) M (SD) M (SD)

COWT (Spring-K) 22.88 20.54 16.64 12.88 1 [ 2, 3, 4 0.56, 1.13, 1.58

(3.22) (4.67) (6.62) (7.68) 2 [ 3, 4 0.68, 1.20

3 [ 4 0.52

LC (Fall-1st) 61.65 53.95 44.79 41.53 1 [ 2, 3, 4 0.64, 1.25, 1.46

(11.72) (12.22) (14.66) (15.25) 2 [ 3, 4 0.68, 0.90

3 [ 4 0.22

COWT Concept of word in text, LC literacy composite. All ‘[’ indicate statistically significant (p \ .01)

between group differences

Table 5 Fall of first grade subtest literacy means (standard deviations) by cluster

Cluster 1 Cluster 2 Cluster 3 Cluster 4

M (SD) M (SD) M (SD) M (SD)

Word recognition 17.40 (3.52) 15.21 (4.71) 11.69 (5.74) 10.81 (5.93)

Letter sounds 23.85 (2.34) 22.70 (2.83) 20.74 (4.46) 20.05 (5.01)

Spelling 20.40 (7.89) 16.01 (6.89) 12.36 (6.59) 10.67 (6.28)

All tasks are from the Phonological Awareness Literacy Screening for grades 1 through 3, maximum

scores (respectively) = 20, 26, 44


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Discussion

The results of this study demonstrate that Hispanic children receiving ESL services

at the start of kindergarten are not a homogeneous group when it comes to

foundational literacy skills. Further, the heterogeneity of their early literacy

development is associated with distinct patterns of strengths and weaknesses across

dimensions of phonological awareness, alphabet knowledge, and orthographic

knowledge. Children’s distinct literacy profiles in fall of kindergarten were also

found to be associated with later literacy milestones. Specifically, the two clusters

that were associated with greater success on later measures of concept of word in

text and a composite measure of letter sound knowledge, word reading, and

spelling, were the two that included stronger performance on alphabet knowledge

and phonetic spelling, the two tasks that measured orthographic knowledge.

The performance of the two middle clusters in this study clearly illustrates the

effect of higher versus lower orthographic skills. While children in both these

clusters had adequate phonological awareness skills in fall of kindergarten, they

differed significantly on orthographic skills. Children in Cluster 2, on average, had

stronger orthographic skills than children in Cluster 3, and Cluster 2 children also

performed significantly better on the spring kindergarten and fall first-grade

outcome measures. Cluster 3 children’s performance on the orthographic tasks was,

in fact, comparable to that of children in the lowest-performing cluster, Cluster 4,

and their performance on the spring kindergarten and fall first-grade measures was

also comparable to that of children in Cluster 4. Although Cluster 3 children

performed slightly higher than Cluster 4 children on the first-grade spelling task,

neither group was able to represent even half of the grade-level phonics/spelling

features tested. Thus, the orthographic skills of alphabet knowledge and phonetic

spelling were the skills most closely associated with success on the later literacy

milestones, suggesting that while phonological awareness may be a necessary

precursor to reading, phonological awareness in the absence of orthographic skills

may not be sufficient.

Our findings that Hispanic kindergarteners in ESL do not represent a

homogeneous group in terms of literacy development suggest that it may not be

appropriate to design literacy instruction based on English language proficiency

alone. As with native English speakers, best practice in early literacy instruction for

ELL students requires differentiation to meet individual students’ specific needs.

When students are grouped together for literacy instruction based on language

proficiency alone, teachers may not be aware of their students’ individual strengths

and weaknesses in literacy development. Since this study demonstrates that

foundational literacy skills are associated with important literacy milestones a year

later, it is important to assess ESL students’ literacy development early and to

differentiate instruction accordingly.

The results of the current study are consistent with previous research

demonstrating that while phonological awareness is an important precursor to

learning to read, it may not be sufficient in and of itself (Morris et al., 2003; Warley

et al., 2005), and, in fact, once children begin formal literacy instruction, skills

related to written language may become more highly related to later reading


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achievement than are sound-related skills alone (Hammill, 2004; Scarborough,

1998). In the current study, it was the orthographic skills of alphabet knowledge and

phonetic spelling that were most closely associated with later literacy milestones.

Our results also support existing research showing that multiple variables,

considered together, can better predict later reading development than any single

variable, taken alone (Manis et al., 2004; Scarborough, 1998; Warley et al., 2005).

By looking at phonological awareness, alphabet knowledge, and phonetic spelling

together, we were able to identify distinct profiles related to early literacy

development in Hispanic ELL students. We then used those profiles to demonstrate

heterogeneity in literacy development among Hispanic ELL students, a finding that

is consistent with research demonstrating similar heterogeneity among English-

speaking children in kindergarten and first grade (Connor et al., 2004; Kaplan &

Walpole, 2005).

Our results also support existing research suggesting that while English language

proficiency is clearly associated with reading achievement, early literacy develop-

ment among ELL students should not be exclusively determined by English

language proficiency (Geva, 2006; Lesaux & Geva, 2006). Although Cluster 4 had a

higher concentration of students at the lowest English proficiency level and a lower

concentration of students at the higher levels, Cluster 4 students’ performance on

the literacy composite in first grade was, on average, very similar to that of students

in Cluster 3. Notably, language proficiency accounted for less than 1.0 % of the

between cluster differences. Clearly, oral language proficiency plays a role in

English literacy acquisition, but in this study, the early literacy predictor skills (e.g.,

beginning sound knowledge, letter sound knowledge, alphabet recognition, phonetic

spelling, and concept of word) made a greater contribution. This is consistent with

Storch and Whitehurst’s (2002) findings that oral language development has a

strong relationship to emergent literacy skills in preschool, but that relationship

weakens significantly in kindergarten and only becomes important again in third

grade, when reading comprehension becomes the focus of instruction. Our findings

are also consistent with Metsala and Walley’s (1998) Lexical Restructuring Model,

which suggests that once children’s lexicons grow to a sufficient size to require

attention to language at the phoneme level, they are able to use their developing

phonemic awareness to support early reading. It is likely that language proficiency

accounted for such a small percentage of the between cluster differences in the

current study because all of the children were beginning readers who were not yet

encountering the types of texts that would require highly developed language and

vocabulary to ensure comprehension.

The findings of this study could have implications for literacy instruction for

Hispanic ELL students. Because these students represent a heterogeneous group in

terms of early literacy skills, even at the start of kindergarten, our findings suggest

that literacy instruction should be differentiated from the very beginning in order to

meet their individual needs. As we have shown, phonological awareness is a

necessary but not sufficient precursor skill to reading, and some children arrive in

kindergarten already having developed adequate phonological awareness skills. The

middle two clusters, for example, were rather equal in phonological awareness skill

but differed substantially in orthographic skills (i.e., letter sound knowledge,


123

alphabet recognition, phonetic spelling). Children who had stronger orthographic

skills in fall of kindergarten had better performance on the literacy composite in fall

of first grade. Thus, instruction that over-emphasizes phonological awareness at the

expense of orthographic skills in kindergarten may waste valuable time for many

children.

The results of this study do suggest, however, that orthographic skills need to be

assessed and taught early on. Fall kindergarten alphabet knowledge and phonetic

spelling were the factors that distinguished children who would have stronger versus

poorer performance on later outcome measures. Our finding that children in the

higher-performing clusters also had higher rates of preschool attendance may

suggest that those children had an earlier start on developing the orthographic skills

that would support their early literacy development. The fact that the children with

the poorest performance on orthographic skills in fall of kindergarten continued to

perform significantly lower on spelling, even in fall of first grade, further suggests

that ongoing instruction and assessment in written word knowledge would be

beneficial.

The goals of the current study were (a) to determine whether ELL students

receiving ESL services in the fall of kindergarten demonstrate distinct patterns of

achievement across measures of phonological awareness, alphabet knowledge, and

orthographic knowledge, and (b) to determine whether any distinct profiles that do

exist can predict early literacy milestones at the end of kindergarten and the

beginning of first grade. These goals were adequately addressed by this research;

however, certain limitations must be considered when interpreting the results. First

of all, information on child-level SES and home language use (i.e., the extent to

which English and/or Spanish were used in the home) were not available. It is

possible that variance in one or both of these factors could have affected cluster

membership and/or performance on the outcome measures. We also lacked

measures of both Spanish language proficiency and Spanish literacy development;

possible variation on these measures may have been associated with our English

literacy profiles, and controlling for these variables would have strengthened our

claim that Hispanic students are not a monolithic group. We also had limited

information about students’ English language proficiency. Having data beyond

simply their SELP levels might have allowed us to address the effect of oral

language more thoroughly. There was also no information available on the type of

instruction children received during the kindergarten year. Participants’ perfor-

mance on the milestone measures may have been affected by the literacy instruction

they received, either in their ESL classes or in their regular classrooms.

Nevertheless, the potential effects of instruction are likely negligible since our

participants attended over 400 schools that represented a range of urban, rural,

suburban, and SES demographics.

Further research is needed to determine whether the results of the current study

can be replicated with other samples of Hispanic ELL students and with native

English speakers. If future person-centered research results in the same profiles for

native English speakers as for ELL students, it might be advisable to consider

instructing ELL students with native English speakers who have similar literacy

needs rather than segregating students based on English language proficiency.


123

Future studies should also include Hispanic ELL students in spring of first grade and

beyond to determine whether the identified profiles are associated with contextual

reading and reading comprehension, once children are reading connected text.

Future research might also use Spanish assessment data along with English data to

explore possible cross-linguistic transfer of literacy skills.

To conclude, we have demonstrated that there is, indeed, heterogeneity in literacy

development among Hispanic ELL students receiving ESL services, even as early as

kindergarten entry. These children arrive at school with very different sets of skills

in place, and literacy instruction can only be successful if it is designed to address

each child’s individual needs. If we treat Hispanic ELL students as a homogeneous

group characterized primarily by a lack of English language proficiency, we may be

placing them at greater risk for developing reading difficulties.

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Documents

Diversity among Spanish-speaking English language learners: profiles of early literacy skills in kindergarten