Reading Efficiency in Native English- Speaking and English-as-a … · 2014. 11. 9. · Reading Efficiency in Native English-Speaking and English-as-a-Second-Language Children: The

Reading Efficiency in Native English-Speaking and English-as-a-Second-

Language Children: The Role of OralProficiency and Underlying

Cognitive-Linguistic Processes

Esther GevaUniversity of Toronto

Zohreh Yaghoub ZadehCanadian Council on Learning

The research examined the extent to which (a) Grade 2 English-as-a-second-lan-guage (ESL) and English-as-a-first-language (EL1) children resemble each other onword and text reading efficiency and (b) whether individual differences in word andtext reading efficiency in the two language groups can be understood in terms of sim-ilar underlying component processes. Despite an oral language proficiency advan-tage in the EL1 group, no EL1 advantage existed on any of the cognitive and readingmeasures. Oral language proficiency, phonological awareness, rapid automatizednaming, and accurate word recognition were significant predictors of word and textefficiency in the ESL group. Only rapid automatized naming and word recognitionwere significant in the EL1 group. Overall, with the exception of English-languageoral proficiency skills, EL1 and ESL profiles of three efficiency subgroups (poor de-coders, low efficiency, and high efficiency) were highly similar.

The goal of this article is to investigate the development of word and text reading effi-ciency in young children learning to read in their second language (L2). Because almostnoresearchhasbeenconductedonthedevelopmentoffluencyandefficiencyinL2read-ing,webeginbyprovidingabriefoverviewofthefirst language(L1)-basedliterature.

SCIENTIFIC STUDIES OF READING, 10(1), 31–57Copyright © 2006, Lawrence Erlbaum Associates, Inc.

Correspondence should be sent to Esther Geva, The Department of Human Development and Ap-plied Psychology, Ontario Institute for Studies in Education of the University of Toronto, Toronto, On-tario, Canada M5S 1V6. E-mail: [email protected]

No consensus exists in the reading literature with regard to the concept of read-ing fluency (Wolf & Katzir-Cohen, 2001). Terms such as fluency, efficiency, andautomaticity overlap to some degree and are often used as synonyms (NationalReading Panel, 2000). Some use the term automaticity to refer to various aspects ofword identification that can be processed with little effort and attention. Theoriesof automaticity (LaBerge & Samuels, 1974) assume that accuracy develops beforespeed and that an efficient reader is one who can read words both accurately andfast. Theories of verbal efficiency (Perfetti, 1985) emphasize the importance of ef-fective lexical retrieval processes and their impact on individual differences inreading comprehension. Researchers have suggested that comprehension can beenhanced when lexical access processes are executed efficiently and automati-cally, so that cognitive-processing resources are not overtaxed (Bowers, Golden,Kennedy, & Young, 1994; Bowers & Wolf, 1993; Carver, 1997; LaBerge &Samuels, 1974; Perfetti, 1985; Shany & Biemiller, 1995; Stanovich, 1992). TheNational Reading Panel (2000) expanded the concept of reading fluency to include“the ability to group words appropriately into meaningful grammatical units for in-terpretation” (pp. 3–6). In this article we use the term word reading efficiency to re-fer to accurate and fast reading of isolated words, and text reading efficiency to re-fer to accurate and fast reading of text.

Recent models espouse a more dynamic, developmental, and componential ap-proach to the study of reading fluency (e.g., Berninger, Abbot, Billingsly, & Nagy,2001; Kame’enui, Simmons, Good, & Harn, 2001; Levy, 2000; Wolf & Katzir-Co-hen, 2001). Kuhn and Stahl (2000) discussed how the development of reading flu-ency relates to the stages of development described by Chall (1996). Wolf andKatzir-Cohen suggested that in the early stages of reading development fluencyentails the gradual development of accurate and automatic execution of lower levelcomponents involving orthographic, phonological, lexical, morphological, andsyntactic skills. To be efficient readers, children need to increase their repertoire oflarge orthographic units that are easily accessible from memory and to carry outthese lower level operations with speed. Once readers have developed efficiencywith these basic aspects of reading and word decoding becomes effortless and fast,text reading efficiency is reflected in paralinguistic features such as prosody. Effi-cient text reading allows for the allocation of attentional resources to higher levelreading skills involved in comprehension.

Wolf and Katzir-Cohen maintained that dysfluent reading can be the result ofimpairment in any component process (Meyer & Felton, 1999; Wolf, Bowers, &Biddle, 2000). Overall, less skilled L1 readers are described in the L1 reading liter-ature as recognizing printed words more slowly than skilled readers (Biemiller,1977/78; Carver, 1997; Denckla & Rudel, 1976; Ehri, 1998; Manis, Seidenberg,Doi, McBride-Chang, & Patterson, 1996; Perfetti, 1985; Torgesen, 2001; Wagneret al., 1997). Two underlying processes that have been implicated in efficient wordreading are phonological awareness and naming speed. Some theoreticians main-

32 GEVA AND YAGHOUB ZADEH

tain that naming speed and phonological awareness tap common underlying pho-nological processes (e.g., Wagner et al., 1997). Others maintain that naming speedmay involve problems with a distinct phonological and visual timing mechanismnecessary for establishing unitized orthographic and phonological codes (e.g.,Bowers & Wolf, 1993; Breznitz, 2001, 2002; Wolf & Bowers, 1999; see Savage,2004, for a review). Notwithstanding this unresolved theoretical debate, L1-basedstudies on the speed of naming various stimuli indicate that individual differencesin speed of letter, digit, or word naming predict fluent reading in L1 (Kirby et al.,2003; Stage, Sheppard, Davidson, & Browning, 2001; Wimmer, Maryinger, &Landerl, 2000; Young & Bowers, 1995).

READING DEVELOPMENT IN L2

Research on L2 reading development in L2 children is not as extensive as the liter-ature on L1 reading development. However, in the last decade the database on L2reading development has expanded. It has shown that (a) accuracy indexes of wordrecognition and spelling skills in young L2 children are often identical to those ofL1 children (e.g., Geva, Yaghoub Zadeh, & Schuster, 2000; Lesaux & Siegel,2004; Lipka, 2003; Wade-Woolley & Siegel, 1997; Wang & Geva, 2003); (b) cog-nitive-linguistic components such as phonological awareness and rapid automa-tized naming (RAN) can be measured reliably and utilized to predict performanceon word reading skills in L1 and L2 children alike (e.g., Chiappe & Siegel, 1999;Comeau, Cormier, Grandmaison, & Lacroix, 1999; Durgunoglu, Nagy, &Hancin-Bhatt, 1993; Geva et al., 2000; Gottardo, Yan, Siegel, & Wade-Woolley,2001; Lesaux & Siegel, 2003; Lindsey, Manis, & Bailey, 2003; Wade-Woolley &Siegel, 1997); and (c) once individual differences in phonemic awareness andrapid naming have been taken into account, oral language proficiency skills do notadd substantially to the variance in accurate basic reading skills in L2 children(Arab-Moghaddam & Sénéchal, 2001; Durgunoglu et al., 1993; Geva & Siegel,2000; Geva et al., 2000; Gholamain & Geva, 1999; Lindsey et al., 2003).

Although L2 oral proficiency may not make a unique contribution over andabove other basic reading components to accuracy in L2 word recognition andspelling skills, it is reasonable to expect that it should play a more pronounced rolewhen word and text reading efficiency are targeted. This issue has received verylittle attention in the L2 literature and has been largely limited to the reading per-formance of adult L2 readers (e.g., Nassaji & Geva, 1999; Segalowitz, 1986;Shimron & Sivan, 1994; Wade-Woolley & Geva, 1999). To date, only a handful ofL2 studies have systematically examined the development of word and text effi-ciency in L2 children (e.g., Geva & Clifton, 1994; Geva, Wade-Woolley, & Shany,1997; Quiroga, Lemos-Britton, Mostafapour, Abbott, & Berninger, 2002). Thestudies by Geva and her colleagues focused primarily on L1–L2 transfer. Both

READING EFFICIENCY IN ESL CHILDREN 33

studies have shown that primary-level poor decoders were less fluent than good de-coders in reading texts in English, in their L1, and in their L2 (French and Hebrew,respectively). Of particular relevance in the present context is the Geva et al.(1997) study in which performance on both accuracy and speed indexes of wordreading in L1 (English) and L2 (Hebrew) were very similar. This result is consis-tent with the observation that oral language proficiency did not make a unique con-tribution to word recognition in L2 children. In addition, in a result replicatingJackson and Donaldson (1989), Geva et al. reported that in their L1 (English), chil-dren’s text reading time was faster than reading the same words presented out ofcontext. However, context did not have a facilitating effect in Hebrew, as their He-brew proficiency was minimal.

Questions concerning the role of language proficiency in enhancing reading ef-ficiency are particularly pertinent in L2 contexts. Carlisle and Beeman (2000) re-ported that primary-level Spanish–English bilingual children’s vocabulary knowl-edge predicted reading comprehension in the same language. An intuitivelysensible hypothesis is that word recognition skills of L2 children should be slowerthan those of their L1 counterparts because their vocabulary is not as developedand because they may be slower in accessing linguistic information (e.g., phono-logical, semantic, morphological) than their L1 counterparts. The same would beexpected to be true for text reading fluency in young L2 learners.

The question then becomes to what extent are L1-based theories of reading effi-ciency, which attribute slower reading to less efficient word recognition skills andto reduced access to linguistic information, applicable to L2 learners? Are individ-ual differences in reading efficiency related to individual differences in underlyingprocesses such as phonological awareness and rapid naming just as they appear tobe in L1 children? Alternatively, are oral proficiency and the ability to benefit fromlinguistic context the driving forces in enhancing L2 word reading efficiency andtext efficiency? According to the latter explanation, L2 children would be expectedto have less efficient word recognition skills than their L1 counterparts and to beless fluent readers because of limitations in the efficiency of retrieving phonologi-cal, semantic, and grammatical information.

In summary, although recent research has shed some light on the cognitive, lin-guistic, and orthographic underpinnings of accurate word recognition skills in L2children, a dearth of knowledge exists about the development of reading efficiencyin L2 children. This study focuses on the emergence of reading efficiency inyoung, primary-level English-as-a-second-language (ESL) children who havemastered the basic principles of word reading. The study’s first objective is to com-pare ESL and English-as-a-first-language (EL1) children on word and text readingefficiency and to examine the effects of context on reading efficiency. A compari-son of reading efficiency in EL1 and ESL children would shed light on the assump-tion that EL1 children should be more efficient readers than ESL children due totheir better command of the language. A second objective is to examine the extentto which a similar set of underlying processes drive word and text reading effi-


ciency in EL1 and ESL children. To achieve this objective, we explore the relativecontribution of individual differences in oral language proficiency, underlyingcognitive-linguistic processes (e.g., nonverbal ability, rapid serial naming, phono-logical awareness), and word recognition to text and word reading efficiency inEL1 and ESL children. The third objective is to examine similarities and differ-ences in profiles of EL1 and ESL groups that differ in their reading efficiency.

METHOD

Participants

ESL and L1 participants were recruited from three subsequent cohorts of children in12 schools in four school boards in a large, multiethnic metropolis in Canada, where4 of 10 residents were born outside the country. It is not the objective of this researchto examine the impact of socioeconomic status on reading achievement in ESL chil-dren.Moreover,wedidnothaveaccess to individual family level socioeconomicsta-tusdata.The2001CanadianCensusdata1 indicate that,onaverage,anonofficial lan-guage (i.e., neither English nor French) was the language spoken by 58% of thepeople living in the communities feeding into the participating schools (the percent-ages ranged from 43% to 73%). On average, 68% of the families living in these com-munities immigrated to Canada when they were at least 20 years old (with little vari-ability between the communities); another 23% indicated that they immigratedbetween the ages of 5 and 19. In other words, the majority of the residents werefirst-generation immigrants. The incidence of poverty2 varied somewhat among thecommunities. Whereas in 2 of the communities no incidence of poverty was re-ported, in each of the other communities a certain proportion (12%–50%) were clas-sified as poor; the average incidence of poverty was 23%. It is also important to notethat themedianfamily incomeineachof the12communitieswassubstantially lowerthan the median reported for the metropolis. Another key index of socioeconomicstatus is parental education. Quite a bit of variability exists in terms of the highestlevel of education achieved, reflecting immigration trends and Canadian immigra-tion policies. On average, 17% of the individuals in the census district had less than 9years of education, 27% obtained at least some secondary education, 13% had a highschoolcertificate,8%hadtraining ina trade,another19%hadcollegeeducation,and20% had obtained a bachelor’s degree or a higher university degree.


1It is possible to access the census demographic data for dissemination areas from Statistics Can-ada. Dissemination areas are small, relatively stable geographic units, composed of one or more blocks,which respect the boundaries of census subdivisions and census tracts. They are uniform in terms ofpopulation size (400–700), and they are the smallest standard geographic area for which all census dataare disseminated. The demographic information provided is based on the data from the disseminationareas in which the participating schools are located.

2Poverty is defined as a family income of $30,000 (Canadian) or less for a family of four.

The initial sample consisted of 183 ESL children and 70 EL1 children. The dataof 3 (4.3%) EL1 children and 18 (8.8%) ESL children who had a standard score be-low 80 on a measure of nonverbal ability (Matrix Analogies Test [MAT]; Naglieri,1989) were not included in the analyses, leaving final samples of 183 Grade 2 ESLchildren (46% girls) and 67 (62% girls) EL1 children.

The native language groups represented in the ESL sample are Cantonese(19%), Punjabi (41%), Tamil (18%), and Portuguese (22%). The ESL childrencome from 12 schools, and the EL1 children from 7 of these schools. The mean agewas 88.43 months for the EL1 sample and 87.32 months for the ESL sample.

Consent forms in English and children’s home language were distributed ineach of the participating classrooms. Only children with parental consent partici-pated in the study. Interviews of parents about home literacy and the extent towhich the native language was used at home were not conducted due to languagebarriers, budgetary constraints, and reluctance by the school districts to allow ac-cess to parents. However, information about the EL1 or ESL language status ofchildren was determined through information about each child recorded in schoolfiles and parent responses included in the consent forms. This information wassubsequently validated during interviews with classroom teachers. Only childrenwhose school records and teacher interviews indicated an ESL status were consid-ered as such in the study. In addition, children who had not lived in an Eng-lish-speaking country for at least 4 months at the onset of Grade 1 were not in-cluded. This precaution was taken to ensure that children who were included hadsome systematic exposure to the rudiments of language and literacy instruction.

In English-speaking Canada, school-age children who are recent arrivals from anon-English-speaking country typically attend school-based ESL classes for up to2 years. In the school districts where this study was conducted, ESL instruction,which is provided on a withdrawal basis, typically occurs in daily 30- to 40-minsessions with groups of three to five children. In these small groups all childrenhave similar levels of English language proficiency but not necessarily the sameL1. Teachers with ESL specialist training conduct these classes. ESL classes focuson the development of spoken English and on readiness for literacy skills. Besidesthe ESL tutoring, new immigrant children attend regular classrooms, in which allinstruction takes place in English.3

Classroom teachers are expected to provide appropriate adaptations to the curric-ulum. Some of the ESL children in this study were attending ESL classes at the timeof testing or had attended such classes in the recent past. Except for pull-outs forsmall-groupESLtutoring, theESLchildrenwerecompletely integrated into the reg-ular classroom.


3Classrooms in large urban centers in Canada are ethnically and linguistically diverse. Therefore,providing systematic language and literacy instruction in the home language is not feasible. In somecommunities, however, children may attend heritage language programs. Typically, these classes takeplaces after school or on weekends.

Measures

Cognitive and Linguistic Measures

Nonverbal intelligence. Children completed the MAT (Naglieri, 1989), ameasure of nonverbal intelligence. In this test, children are presented with an illus-tration of an incomplete visuo-spatial matrix and asked to complete it by locatingthe missing piece among five or six patterned segments. The test has four subtests(pattern completion, reasoning by analogy, serial reasoning, and spatial visualiza-tion), each of which consists of 16 matrixes. Testing within each subtest is discon-tinued after four consecutive errors. Results are reported in standard scores.

RAN. The RAN task, developed by Denckla and Rudel (1976), was used tomeasure speed of rapid serial naming. In this continuous naming task, children areasked to name five letters as fast as they can. Each letter appears 10 times in ran-dom order within 10 sets of five items. Prior to administering the RAN task, thechild is asked to name each of the five letters to ascertain familiarity with the let-ters. The RAN measure is not administered to those children who cannot name allfive letters without assistance. The children’s time (in seconds) to name all the let-ters on the board is used as the naming speed measure. Note that the lower thescore is the faster is the naming speed.

Phonological awareness (PA). PA was measured with a task adapted fromthe Auditory Analysis Task developed by Rosner and Simon (1971). In this seg-mentation-deletion task, children must isolate and delete syllables or phonemesand indicate the resulting word (e.g., “Say meat. Now say it without the /m/.”).Methodological considerations guided us in adapting this task to the ESL popula-tion. In particular, it was necessary to minimize the possible confounding of lan-guage proficiency with performance on this phonological awareness task. Our pri-mary concern was that many of the words or the resulting words on the originalAuditory Analysis Task are not likely to be familiar to young ESL children (e.g.,stale). The items on the adapted task are all high-frequency words, and the result-ing words after the child deletes the phoneme or syllable are also high-frequencywords (e.g., “Say leg. Now say it without the /l/.”). Of the 25 items on the task, thefirst 4 involve syllable deletion, and the remainder require phoneme deletion inword initial, word final, or word medial position. Some items require the deletionof a phoneme in a consonant cluster. Four practice items precede the administra-tion of the test items. Administration is discontinued after five consecutive errors.The total correct scores are reported. The Cronbach α is .92.

Expressive One-Word Picture Vocabulary Test–Revised. The Expres-sive One-Word Picture Vocabulary Test–Revised (Gardner, 1990) was used to as-sess language proficiency. It is a standardized measure of expressive vocabulary inwhich children are asked to provide one-word labels to line drawing pictures pre-


sented to them one at a time. The test, which includes 100 nouns and verbs, is dis-continued once a criterion of six consecutive errors has been established. The totalnumber of correct responses was used in the analyses.

Grammatical judgment. Children’s syntactic knowledge was assessed us-ing items adapted from a grammatical judgment measure developed by Johnsonand Newport (1989). In this 40-item measure of receptive syntactic skills, the childlistens to prerecorded taped sentences that are either grammatically correct (e.g.,“We ate the whole pizza by ourselves.”) or incorrect (e.g., “January is the most coldmonth of the year.”). Half of the sentences are syntactically correct, and the otherhalf are syntactically incorrect. Each sentence is played twice on a tape recorder,and the child is asked to indicate whether the sentence is said “the right way” or“the wrong way.” No discontinue rule is used on this test. The total score was basedon the number of correctly judged sentences. The Cronbach α value is .77.

Basic Reading Skills Measures

Word Attack. The Word Attack subtest of the Woodcock Reading MasteryTest–Revised (Woodcock, 1987) was used to assess children’s ability to utilizetheir knowledge of grapheme–phoneme correspondence rules and orthographicrepresentations to decode or “attack” pseudowords in English. This test consists of50 pronounceable pseudowords that comply with English orthographic rules (e.g.,plip, cigbet). Children read the pseudowords one at a time, and testing is discontin-ued when the child makes six consecutive errors. Results are reported in terms oftotal correct scores.

Word Recognition. To assess children’s English word recognition skills theWord Recognition subtest of the Wide Range Achievement Test–Revised (Jastak& Wilkinson, 1984) was used. This test consists of 42 unrelated words. It beginswith highly familiar, short words (e.g., cat), and gradually the words become lessfrequent and more complex orthographically (e.g., pseudonym). Testing is discon-tinued when the child makes 10 consecutive errors. Results are reported in terms oftotal correct scores.

Reading Efficiency Measures

The Biemiller Test of Reading Processes (Biemiller, 1981) was used to measureword and text reading efficiency. The test yields measures of accuracy and speed inreading isolated words and connected text. The isolated word lists come from thecorresponding texts.

Word efficiency. This subtest, which requires children to read isolatedwords, provides an indication of children’s ability to identify unrelated words ac-curately and quickly. Children are presented with two lists, each consisting of 50


randomly ordered, single-morpheme words (taken from the two correspondingtexts; see the following discussion) and asked to read them as fast as possible. Thefirst list has easier words than the second.

Text efficiency. The Text Reading subtest focuses on text reading efficiency.Participants are presented with two narrative texts (containing 100 words each).They are required to read each text aloud as quickly as they can. The subtest in-cludes two narratives, an “easy” text, which, according to Biemiller (1981) usesprimer-level words (e.g., bear, thank, no, they, water, fish, tried, and father), and arelatively more “difficult” text, which consists of words that are typical of middleelementary-level reading (e.g., register, asked, interested, saw, things, wood, tour-ists, and also). The reading materials are easy to minimize confounding of speedand accuracy (Jackson & Donaldson, 1989).

Test administration. The child first reads the easy text and then the corre-sponding word list. The more difficult text and the corresponding word list are ad-ministered next. Both sets contain words that were chosen because they can be de-coded with minimal difficulty. As Biemiller (1981) pointed out, the goal of the testis to ascertain not how many words children can read but rather the speed at whichthey read these words. Assessment of reading efficiency, however, can be compro-mised if children make too many errors. The assessor is thus instructed to aid thechild who stumbles on a word by providing without delay the unknown word aswell as the subsequent two words. The Biemiller test stipulates that if a childmakes more than 25% errors on the first text they should not be administered thesecond text. Accordingly, in this study, when children failed to read the first pas-sage with an acceptable degree of accuracy (75% accuracy regardless of speed),they were considered to be poor decoders and were not administered the secondpassage and corresponding word list.4

Speed scoring. To obtain a speed score in the isolated words condition, wedivided the total number of seconds that a participant took to read the easy and hardlists by the total number of correct words read across the two lists. The same proce-dure was repeated to calculate text speed scores. The EL1 and ESL groups did notdiffer on word accuracy (85% and 88%, respectively) or on text accuracy (89% and90%, respectively).


4A comparison of efficiency scores in the EL1 and ESL groups with those published by Biemiller(1981) revealed that the speed scores reported by Biemiller for the same age group were higher thanthose obtained in this study. However, Biemiller excluded data of children who made more than threeerrors on the tasks because he focused on the relationship between speed and accuracy in children whoread with accuracy. The objective of this study is to compare ESL and EL1 children, and, therefore, theexclusion criterion was different—only children who made more than 25% errors when they read thefirst and easy text were excluded.

Reading efficiency scores. Two dependent measures were derived—aword efficiency score and a text efficiency score. Efficiency scores were computedbased on a procedure used by Stanovich and West (1989). First, for each partici-pant the number of errors on each task and the time to perform each task were con-verted into their respective Z scores. The resulting accuracy and speed Z scores foreach task were then combined and averaged to yield a single composite efficiencyscore. The two word-based composite efficiency scores (based on the easy and dif-ficult lists) were averaged to yield an overall score that represents the child’s abil-ity to read words efficiently. The same procedure was applied to develop an overalltext efficiency score that represents the child’s ability to read with accuracy andspeed the two narratives. Note that the lower the Z score, the more efficient thechild’s reading.

Procedures

As part of a larger project (which began when the children were in Grade 1), chil-dren were administered a series of tests in the first half of their 2nd year in elemen-tary school. At that time children in the EL1 and ESL groups have spent 1½ to 2½years in schools in which English is the language of instruction (i.e., senior kinder-garten and Grade 1). These tasks were part of a larger battery of tests, which wasadministered across four testing sessions, each lasting approximately 30 min. Al-though the batteries were administered in a random order, tests within the batterieswere administered according to a fixed random order. Children were tested on anindividual basis by one of a number of experienced graduate students. For theMAT, standardized scores were used. However, raw scores were used when otherstandardized tests such as the Expressive One-Word Picture Vocabulary Test(Gardner, 1990) and the Woodcock Reading Mastery Test–Revised (Woodcock,1987) were used, because the norms were not developed for ESL children.

RESULTS

Of the 67 EL1 children, 12 (18%) were deemed to be poor decoders, as they madetoo many decoding errors on the easy story and were, therefore, not able to prog-ress to the difficult story. Of the 183 ESL children, 32 (17%) were not able to prog-ress to the difficult story and were likewise considered poor decoders. Fifty-fourEL1 and 151 ESL children met the minimum requirements for becoming efficientreaders because they were able to complete both the easy and difficult subtasks ofthe Biemiller (1981) test. A cross-tab chi-square analysis was done to examinewhether the proportion of poor decoders was higher in the ESL group than in theEL1 group. This analysis reveals that the proportion of poor decoders in the EL1and ESL groups was similar, χ2(1, N = 250) = .07, p = .460.


The focus of this article is on a comparison of underlying processes associatedwith reading efficiency in ESL and EL1 children. The bulk of the Results sectionfocuses on a comparison of EL1 and ESL children who were able to read both sto-ries with relative accuracy and speed. At the end of the Results section we revisitthe poor decoders group, when we compare the profiles of the relatively efficientreaders with the profiles of the poor decoders. Bonferoni correction was applied toadjust the alpha level for multiple analyses. An alpha of .01 was selected as theminimum acceptable level.

Comparison of EL1 and ESL Groups on Cognitive,Language, and Reading Measures

Table 1 provides summary statistics by language group associated with all the cog-nitive, linguistic, reading, and oral proficiency measures. A multivariate analysis


TABLE 1Differences Between EL1 and ESL Groups on Age, MAT, SyntacticKnowledge, Vocabulary, PA, and RAN: Descriptive Statistics and

Multivariate Analysis of Variance Summary Table

Measures

EL1a ESLb

M SD M SD Language Group, Fc

Age (months) 88.43 3.61 87.32 3.58 3.79MAT 101.50 7.25 101.03 9.46 0.11GramJudg 29.63 4.76 26.05 5.34 18.92***ExpVoc 61.81 11.53 46.42 14.80 47.92***PA 12.04 4.74 13.63 6.15 2.99RAN 34.66 7.71 29.98 6.44 18.85***WordRec 11.00 4.50 12.00 4.27 2.11WordAtt 15.83 8.66 17.95 10.59 1.73WordAcc 84.74 11.82 87.67 11.97 2.40TextAcc 88.56 15.45 89.66 17.99 0.64WordSp 1.50 .71 1.13 .61 14.02**TextSp 1.17 .55 .99 .55 4.83

Note. EL1 = English as a first language; ESL = English as a second language; MAT = MatrixAnalogies Test; PA = Phonological Awareness; RAN = Rapid Automatized Naming (in seconds);GramJudg = Grammatical Judgment Test; ExpVoc = Expressive One-Word Picture Vocabulary Test;WordRec = Total words read correctly on Wide Range Achievement Test–Revised word recognition;WordAtt = Total correct on Pseudoword reading; WordAcc = % words read correctly on 2 Biemillerword lists (out of 100); TextAcc = % correct words over 2 Biemiller texts (out of 200); WordSp = speedper word (in seconds) over 2 Biemiller word lists (lower is faster); TextSp = speed per word (in seconds)to read 2 Biemiller texts (lower is faster).

an = 54. bn = 151. cAnalysis is based on low- and high-efficiency groups only.**p < .001. ***p < .0001.

of variance (MANOVA) revealed that the language groups did not differ from eachother on the MAT, and the MANOVA did not reveal significant differences be-tween the two language groups on age. However, as can be seen in Table 1, on thetwo oral language proficiency indexes (Expressive One-Word Picture VocabularyTest and the Grammatical Judgment task) the mean in the EL1 group was signifi-cantly higher than in the ESL group. In this regard, it is useful to note as well that acomparison of group means with grade equivalent norms revealed that the Expres-sive One-Word Vocabulary mean in the EL1 group was within the average range(with a mean age equivalent of 7 years 10 months), whereas the age equivalentscore in the ESL group was about 2 years below that of the EL1 group (with a meanage equivalent of 5 years 9 months).

On the naming speed measure (i.e., RAN), children in the ESL group were sig-nificantly faster than their EL1 counterparts. On the phonological awareness (i.e.,PA) task, the word recognition task and the word attack task no differences existedbetween the ESL and EL1 children.

As can be seen in Table 1, despite the differences in oral language proficiency,ESL and EL1 groups did not differ on accuracy indexes of basic reading skills (i.e.,word recognition and word attack). Based on the test norms, the group means ob-served for both the EL1 and ESL groups were within the normal range for theirgrade in school (grade equivalent = 2.1–2.2). In the same vein, a comparison of thegroup means on the word attack task revealed that the ESL group was slightlyhigher (grade equivalent = 2.2) than the EL1 group (grade equivalent = 1.9).

To examine context effects on accuracy and speed in the EL1 and ESL groups,two-way analyses of variance (ANOVAs) were conducted with context (words vs.text) as a repeated measure and group (EL1 vs. ESL) as a nonrepeated, independ-ent variable. Results pertaining to reading accuracy indicated that a main effect ex-isted for context, F(1, 248) = 64.32, p < .0001, suggesting that in both languagegroups reading in context was somewhat more accurate than reading isolatedwords. The language group effect was not significant, indicating that the twogroups read at the same level of accuracy. However, a significant Language Group× Context interaction exists, F(1, 248) = 6.59, p < .01, indicating that context wasmore facilitating in the EL1 group. Results of the two-way ANOVA pertaining tospeed show that a significant main effect exists for context, F(1, 248) = 162.26, p <.0001, indicating that in both language groups texts were read faster than isolatedwords. A main effect was also found for language group, F(1, 248) = 8.28, p <.005, indicating that ESL children were faster, and a significant Context × Lan-guage Group interaction, F(1, 248) = 26.02, p < .0001, indicating again that con-text was more facilitating in the EL1 group than in the ESL group.

To summarize, the EL1 group outperformed the ESL group on the languageproficiency measures, but the ESL group outperformed the EL1 group on let-ter-naming speed (i.e., RAN) and word-naming speed. The groups did not differ onPA, word recognition, and pseudoword reading. Finally, the context effect wasmore pronounced in the EL1 group than in the ESL group.


Correlates of Reading Efficiency

To examine patterns of individual differences in reading efficiency in the EL1 andESL groups, we first examined intercorrelations among the reading efficiencyscores and the potential predictor variables. Table 2 provides a summary of theseanalyses within each language group. In general, it is noteworthy that in the ESLgroup most variables correlated significantly with each other, whereas in the EL1group this correlation was not consistent. The results of the correlational analysescoupled with theoretical considerations guided us in the selection of predictor vari-ables in subsequent hierarchical regression analyses and in determining the orderin which variables were entered into the regression. In particular, potential predic-tor variables that are of a more general nature, such as nonverbal ability and lan-guage proficiency indexes, were entered first. The variables of interest (i.e., basicprocessing indices such as phonemic awareness and naming speed) were enteredin subsequent steps. Word recognition was entered last to examine the extent towhich accurate word recognition makes a unique contribution to reading effi-ciency over and above the contribution of the general and basic processing vari-ables listed above. Note the positive and significant correlation between Expres-sive One-Word Picture Vocabulary and Grammatical Judgment (r = .48).

Predictors of Reading Efficiency

As can be seen in Table 2, very high correlations exist between the two (untimed)basic word reading measures (word attack and word recognition) and the word andtext efficiency measures. To avoid multicolinearity, word attack was not includedin the regression analyses, but word recognition was entered last for theoreticalreasons. In particular, the word recognition task includes a large array of wordsvarying in frequency and regularity, and it correlates with spelling and ortho-graphic skills. In these hierarchical regression analyses, conducted separately forthe EL1 and ESL samples, text efficiency and word efficiency were the dependentmeasures. In the first set of regression analyses, all potential predictors were in-cluded. In subsequent analyses nonsignificant predictors were omitted if a givenvariable was not significant for both language groups.

Predictors of Reading Efficiency in the ESL Group

Thefirst setofhierarchical regressionanalysesexamined the roleofMAT,oralprofi-ciency (as measured by vocabulary knowledge and grammatical judgment), phono-logical-processing skills (as measured by PA and RAN), and word recognition skillsin explaining individual differences in word and text reading efficiency in the ESLgroup. In general, the percentage of variance explained by each of the predictor vari-ables was similar for both the word and text reading efficiency measures. As can beseen in Table 3, MAT did not play a significant role in explaining variance in word


44

TAB

LE2

Inte

rcor

rela

tions

Am

ong

Age

,MAT

,Lan

guag

eM

easu

res,

PA,R

AN

,Wor

dEff,

and

Text

Eff

inth

eE

L1an

dE

SL

Gro

ups

ESL

12

34

56

78

910

EL

11.

Age

1.00

0–.

225*

–.12

1.0

96.0

01.0

33–.

064

–.09

0.0

29.0

172.

MA

T1

.030

1.00

0.3

68**

.466

***

.356

***

–.16

9–.

193

–.14

2.3

39**

*.3

69**

*3.

Gra

mJu

dg–.

112

.280

1.00

0.4

79**

*.4

01**

*–.

147

–.27

3**

–.23

9*.3

80**

*.3

45**

*

4.E

xpV

oc.0

65.2

98.3

67*

1.00

0.2

93**

–.24

3*–.

378*

**–.

337*

**.4

16**

*.3

68**

*

5.PA

.199

.184

.268

.248

1.00

0–.

267*

*–.

508*

**–.

493*

**.6

93**

*.7

31**

*

6.R

AN

–.12

4–.

084

–.21

6.1

08–.

149

1.00

0.6

04**

*.6

24**

*–.

543*

**–.

447**

*

7.Te

xtE

ff–.

073

–.23

8–.

307

–.08

4–.

327*

.590

***

1.00

0.9

67**

*–.

838*

**–.

739**

*

8.W

ordE

ff–.

073

–.22

8–.

250

–.01

4–.

279

–.61

0***

.966

***

1.00

0–.

813*

**.7

19**

*

9.W

ordR

ec.1

53.2

46.3

46.2

54.5

62**

*–.

556*

**–.

798*

**–.

790*

**1.

000

.850

***

10.W

ordA

tt.2

46.2

93.3

81*

.127

.662

***

–.58

1***

–.68

0***

–.66

1***

.826

***

1.00

0

Not

e.E

L1

n=

54,a

ndE

SLn

=15

1.E

L1

corr

elat

ions

are

abov

eth

edi

agon

alan

dE

SLar

ebe

low

the

diag

onal

.MA

T=

Mat

rix

Ana

logi

esTe

st;P

A=

phon

o-lo

gica

law

aren

ess;

RA

N=

Rap

idA

utom

atiz

edN

amin

g;W

ordE

ff=

wor

def

fici

ency

;Tex

tEff

=te

xtef

fici

ency

;EL

1=

Eng

lish

asa

firs

tlan

guag

e;E

SL=

Eng

lish

asa

seco

ndla

ngua

ge;G

ram

Judg

=G

ram

mat

ical

Judg

men

tTes

t;E

xpV

oc=

Exp

ress

ive

One

-Wor

dPi

ctur

eV

ocab

ular

yTe

st;W

ordR

ec=

tota

lwor

dsre

adco

rrec

tlyon

Wid

eR

ange

Ach

ieve

men

tTes

t–R

evis

ed;W

ordA

tt=

tota

lcor

rect

onPs

eudo

wor

dR

eadi

ng.

*p<

.01.

**p

<.0

01.*

**p

<.0

001.

and text reading efficiency in the ESL group. Of the two oral language proficiencymeasures, grammatical judgment was marginally significant (p = .014), explaining4% of the variance in word reading efficiency, and it was significant, explaining 5%of the variance in the case of text reading efficiency. Vocabulary, the second measureof oral language proficiency, was significant, explaining an additional 7% of thevariance in both word efficiency and text reading efficiency. PA explained an addi-tional 18% of the variance in word reading efficiency and 16% of the variance in textreading efficiency. RAN added a further 23% to the explained variance in word read-ing efficiency and 20% to text reading efficiency. It is noteworthy that RAN and PAexplained together 41% of the variance in word reading efficiency and 37% of thevariance in text reading efficiency, even though they were entered after MAT and theoral proficiency indexes. Finally, word recognition, entered last, explained an addi-tional 19% of the variance in word reading efficiency and 22% in text reading effi-ciency. Altogether, 73% of the variance in word efficiency, and 75% of the variancein text efficiency was explained by the predictor variables.

Predictors of Reading Efficiency in the EL1 Group

As was the case in the ESL group, the hierarchical regression analyses examine therole of MAT oral proficiency, PA, RAN, and word recognition in explaining wordand text reading efficiency in the EL1 group. Due to power constraints in the EL1sample, in the first step the predictor measures were entered in three blocks: MATin the first block, the two oral proficiency measures in the second block, and thetwo phonological-processing measures (RAN and PA) and word recognition in thethird block.


TABLE 3Hierarchical Regression Analyses Predicting Reading Efficiency in ESL,

With MAT, Syntactic Knowledge, Vocabulary, PA, and RANas Independent Variables

Word Efficiency Text Efficiency

Variable R2 ∆R2 ∆F p β R2 ∆R2 ∆F p β

MAT .02 .02 3.03 ns .12 .03 .03 5.10 ns .07GramJudg .06 .04 6.21 .014 .09 .09 .05 8.54 .005 .07ExpVoc .13 .07 10.72 .001 –.08 .16 .07 12.43 .001 –.09PA .31 .18 36.21 .0001 –.01 .32 .16 33.90 .0001 .03RAN .54 .23 69.05 .0001 .24 .53 .20 60.34 .0001 .19WordRec .73 .19 96.33 .0001 –.72 .75 .22 120.76 .0001 –.77

Note. ESL = English as a second language; MAT = Matrix Analogies Test; PA = phonologicalawareness; RAN = Rapid Automatized Naming; GramJudg = Grammatical Judgment Test; ExpVoc =Expressive One-Word Picture Vocabulary Test; WordRec = total words read correctly on Wide RangeAchievement Test–Revised.

Results of the first set of analyses pertaining to word and text reading efficiency(see top panel of Table 4) show that only the third block—consisting of PA, RAN,andwordrecognition—wassignificant.Because the first twoblockswerenot signif-icant for either word or text efficiency, we eliminated these variables from subse-quent analyses. The lower panel of Table 4 provides a summary of these results. InthesecondsetofanalysesPA,RAN,andwordrecognitionwereenteredoneata time.These analyses revealed that PA was not significant for word or text reading effi-ciency, and RAN was highly significant, explaining an additional 34% of the vari-ance for word efficiency and 31% for text efficiency. Word recognition, entered last,explained an additional 28% of the variance in word efficiency and 27% in text effi-ciency.Altogether,62%of thevariance inwordefficiencyand58%of thevariance intext efficiency were explained by RAN and accurate word recognition.5


5It should be noted that multiple regression analyses, using speed of word and text reading as a de-pendent variables (rather than efficiency scores) and the identical set of predictor variables reported inthe text, yielded similar results to those reported in this article, with only slight fluctuations in the per-centage of variance explained by each additional variable.

TABLE 4Hierarchical Regression Analyses Predicting Reading Efficiency in EL1,With MAT, Vocabulary, Syntactic Knowledge, Vocabulary, PA, and RAN

as Independent Variables

Word Efficiency Text Efficiency

Variable R2 ∆R2 ∆F p R2 ∆R2 ∆F p

Block 1MAT .06 .06 2.82 ns .06 .06 2.89 ns

Block 2GramJudgExpVoc .13 .08 1.99 ns .14 .09 2.27 ns

Block 3PARANWordRec .71 .57 27.37 .0001 .69 .54 24.12 .0001

PA .08 .08 4.04 ns .11 .11 5.66 nsRAN .42 .34 26.44 .0001 .41 .31 24.10 .0001WordRec .69 .28 40.08 .0001 .68 .27 37.08 .0001

Note. EL1 = English as a first language; MAT = Matrix Analogies Test; PA = phonological aware-ness; RAN = Rapid Automatized Naming; GramJudg = Grammatical Judgment; ExpVoc = ExpressiveOne-Word Picture Vocabulary Test; WordRec = total words read correctly on Wide Range Achieve-ment Test–Revised.

By definition, it is not possible to measure reading efficiency in children whosereading skills are not sufficiently developed. At the same time, it is useful to exam-ine profiles of EL1 and ESL children to better understand the underlying mecha-nisms that distinguish subgroups of children that differ in reading efficiency. Weturn to this topic in the next section.

Subgroup Reading Efficiency Profiles

The efficient EL1 and ESL readers (i.e., those who completed both texts on theBiemiller, 1981, task) were divided further into two subgroups, high efficiency andlow efficiency, based on the median of the reading efficiency distribution. To ex-clude borderline cases around the cutoff point, data of children whose text readingefficiency Z scores were between –.05 and .05 were dropped. To this end, the dataof 6 (9%) EL1 participants were excluded, as were the data of 5 (3%) ESL partici-pants. The high-efficiency group consisted of children whose Z scores were at least.05 above the median on the text reading efficiency index. The low-efficiencygroup consisted of children whose Z scores were at least –.05 below the median onthe text reading efficiency index. The EL1 low-efficiency group consisted of 20(30%) children, and the EL1 high-efficiency group consisted of 29 (43%) children.The ESL low-efficiency group consisted of 42 (24%) children, and the ESLhigh-efficiency group consisted of 104 (57%) children. The third subgroup inte-grated into this analysis consisted of the poor decoders who were not able to com-


FIGURE 1 ESL and EL1 profiles of poor decoders, low-efficiency, and high-efficiency read-ers (Z scores).

plete the two stories. The poor decoder subgroup consisted of 12 (18%) children inthe EL1 group and 32 (17%) children in the ESL group.

Figure 1 provides a visual depiction of the EL1 and ESL high-efficiency,low-efficiency, and poor decoder profiles. To examine the reading efficiencygroup and language group effects on the cognitive, linguistic, and reading mea-sures, a MANOVA with Scheffé post hoc analyses was carried out. The resultsof these analyses are summarized in Table 5. Consistent with the previous analy-ses, a significant language–group effect exists on the two oral language indexesas well as on RAN but not on MAT, PA, or any of the reading measures. A sig-nificant reading efficiency subgroup effect occurs on all the measures except forthe Expressive One-Word Vocabulary Test, which was marginally significant (p= .015). Post hoc analyses indicated that the poor decoder subgroup and thelow-efficiency subgroup were significantly lower than the high-efficiency groupon MAT and on the language proficiency measures. The efficiency groups alsodiffered from each other on RAN, PA, word recognition, and word attack. Theinteraction between language group and reading efficiency group was not signif-icant for any of the variables.


TABLE 5The Effect of Language Group, Efficiency Group, and the Language Group× Efficiency Group Interaction on MAT, Syntactic Knowledge, Vocabulary,PA, RAN, Word Recognition, Word Attack, Word and Text Accuracy, andWord and Text Speed: Multivariate Analysis of Variance Summary Table

Language GroupEffect Efficiency Group Effect (a,b,c)a

Language ×Efficiency

Effect

F F Post Hoc F

MAT 1.03 8.03*** a < c***; b < c** 0.02GramJudg 22.64*** 8.28*** a < c**; b < c** 0.34ExpVoc 84.17*** 5.67* a < c***; b < c** 3.18RAN 26.41*** 68.88*** a < b < c*** 1.79PA 0.05 31.80*** a, b < c***; a < b** 4.01WordRec 0.26 165.07*** a < b < c*** 0.82WordAtt 0.76 83.24*** a, b < c***; a < b** 2.45

Note. All measures converted to Z scores. MAT = Matrix Analogies Test; PA = phonologicalawareness; RAN = Rapid Automatized Naming (in seconds); GramJudg = Grammatical Judgment;ExpVoc = Expressive One-Word Picture Vocabulary Test; WordRec = total correct on Wide RangeAchievement Test–Revised; WordAtt = total correct on Pseudoword Reading.

aa = poor decoders, b = low-efficiency readers, c = high-efficiency readers.*p < .01. **p < .001. ***p < .0001.

DISCUSSION

ESL and EL1 Differences on Cognitive-Linguistic andReading Measures

Results of this study are in line with previous research that has shown that eventhough EL1 and ESL children differ on their oral proficiency, they can perform at thesame level on accuracy indexes of basic reading skills such as word recognition andword attack (e.g., Geva et al., 2000; Gottardo et al., 2001; Lesaux & Siegel, 2003).This study takes the research in this area one step further by examining reading effi-ciency of ESL children at the primary level. Results of this study suggest that ESLchildren can read words and simple texts with the same efficiency as EL1 children.These findings challenge the intuitive belief that ESL children would read isolatedwords and text less efficiently because of lower command of the L2.

Surprisingly, the ESL children read isolated words significantly faster than thechildren in the EL1 group, and they were also faster than the EL1 group on a se-quential letter-naming task. This finding is consistent with the findings of Lesauxand Siegel (2003), who found an ESL advantage on naming speed. The ESL ad-vantage on word reading speed and letter-naming speed can be approached fromthree different angles.

First, these differences could be attributed to socioeconomic status factors.However, children in the EL1 and ESL groups were sampled from schools locatedin the same working-class neighborhoods, thus reducing the strength of this argu-ment. Second, given that EL1 and ESL children were selected from the sameschools, the argument that the results might reflect systematic differences in in-structional approaches can be ruled out. Third, group differences in speed could beattributed to group differences in ability in one of two ways. One argument is thatthe groups might differ in general cognitive ability. However, results indicate thatthe EL1 and ESL groups did not differ on nonverbal aspects of cognitive ability.Relatedly, some might argue that the differences reflect the positive impact of bi-lingualism on underlying basic cognitive processes that are essential for readingdevelopment (Bialystok, 2001; Bialystok & Herman, 1999). To date, this argumenthas been examined with regard to metalinguistic skills, and no sound theoretical orempirical evidence exists to suggest that bilingualism might have a facilitating ef-fect on basic naming speed processes.

In this context it is important to be mindful of Cummins’s (2000) threshold hy-pothesis that attempts to reconcile research evidence on positive and negative ef-fects of bilingualism. This hypothesis suggests that language and cognitive devel-opment might be enhanced in bilinguals, provided that relatively high levels ofproficiency have been attained in both languages. Clearly, this hypothesis is not ap-plicable to young ESL learners. None of these explanations are satisfactory, and


further research is necessary to explore the factors that might contribute to the ESLadvantages, reported in this article and elsewhere (e.g., Lesaux & Siegel, 2003).

It is noteworthy that ESL children are similar to their EL1 counterparts in theirability to read simple narratives with accuracy and speed. In other words, pri-mary-level ESL children can develop accuracy and speed in L2 reading and, in-deed, achieve efficiency similar to that of their EL1 counterparts, provided thatthey are exposed to systematic instruction in language and literacy in English(Gersten & Baker, 2003; Gersten & Geva, 2003; Lesaux & Siegel, 2003; Stuart,1999) and that they have well-developed word recognition skills. As Chall (1996)remarked, in Stage 2 most children learn to use their decoding knowledge and uti-lize the “redundancies of the language and the stories they read” (p. 19), which canbe the case for ESL children as well, provided that the language of the narratives isnot too demanding. At the same time, it is important to remember that the route tra-versed by EL1 and ESL children is not identical: The EL1 children come to schoolalready equipped with the language they need to enable them to read simple texts(Chall, 1996), whereas the ESL children develop their language skills in parallel tothe development of their reading skills. It is also important to bear in mind that,notwithstanding home language, reading efficiency is a construct whose very na-ture changes with development and that it is not an all-or-none phenomenon.

Previous literature on context effects (e.g., Jackson & Donaldson, 1989) hasshown that context enhances word reading efficiency. Likewise, in this researchmonolingual and ESL children are found to read words faster and more accuratelywhen the words are presented in context than when the same words are presentedin isolation. However, the context facilitation was more pronounced in the EL1group than in the ESL group, presumably due to the fact that the EL1 children havebetter command of the English language than the ESL children. A better commandof the language helps children to anticipate words presented in context and en-hances accurate and fast recognition of printed words. In a study of primary-levelchildren, Geva et al. (1997) showed that when children read in their L1 context fa-cilitation is used and words are read more accurately and faster. However, this fa-cilitation was not detected when the same children read in their L2 (Hebrew), a lan-guage in which they had minimal proficiency. The discrepancy between the resultsof the Geva et al. study regarding the context effect for L2 readers may be due todifferences in morphosyntactic complexity (Hebrew is denser) and the fact that thelevel of English oral language proficiency of the ESL participants was more ad-vanced in this study than was the case in the Geva et al. study. Finally, future re-search needs to examine the extent to which the results can be replicated in a de-sign in which word-reading latency is measured for words presented one at a timeon a computer screen. Jackson and Donaldson found that precocious younger read-ers were disadvantaged on the Biemiller (1981) scrambled list but not whenword-reading latency was measured with words presented individually on a com-puter screen. It is possible that because the EL1 children might be more sensitive to


grammatical patterns and grammatical expectancies than the ESL children, thereading of a scrambled, serially presented list is more debilitating to them than toESL children.

Factors Contributing to Reading Efficiency in EL1and ESL Children

The second objective of this study is to examine the relative contribution of orallanguage proficiency, underlying cognitive-linguistic processes, and word recog-nition to reading efficiency. This objective embraces two related questions: Whatare the processing factors contributing to word and text reading efficiency, and towhat extent does the same pattern exist in the ESL and EL1 groups?

An intuitively appealing argument might be that to read words efficiently chil-dren need to have well-developed vocabulary and well-developed decoding skillsbut that syntactic and discourse level knowledge is necessary to read texts with ef-ficiency. However, the results did not reveal a different path for word and text read-ing efficiency in the EL1 or ESL groups. In the ESL group vocabulary and syntac-tic knowledge explained jointly 11% of the variance in the case of word efficiencyand 12% in the case of text efficiency. These results suggest that the ESL partici-pants reached some kind of a threshold in their English language proficiency thatenabled them to read with ease texts that do not challenge their current linguisticknowledge. That is, it appears that when the language used in the reading materialsis below or perhaps just at the level of oral proficiency (Chall, 1996), L2 oral profi-ciency contributes only marginally to word or text reading efficiency of ESL chil-dren, and it plays no role in the case of EL1 children. The scenario might be differ-ent when the reading materials are more demanding in terms of the range ofvocabulary and syntactic structures. This issue needs to be explored in future re-search. More research is needed to examine the contribution of oral language profi-ciency when linguistically more demanding texts are presented. Furthermore, inthis research accuracy aspects of oral language proficiency were tapped. The ex-tent to which oral language fluency might contribute more substantially to readingefficiency is another question that should be targeted.

Results of this study demonstrate that over and above the contribution of orallanguage proficiency, RAN, PA, and well-developed word recognition skills con-tribute substantially to word and text reading efficiency of ESL children. RAN andPA are the same processing constructs that have been shown elsewhere (e.g., Gevaet al., 2000; Gholamain & Geva, 1999; Lesaux & Siegel, 2003) to account for indi-vidual differences in accurate word recognition skills of EL1 and ESL children. Inthis research we examine the role of these processes as well as word recognition inreading efficiency. The results show that the roles played by PA, rapid naming, andaccurate word recognition skills in accounting for individual differences in wordand text efficiency are not identical for EL1 and ESL children. Each of these vari-


ables contributes substantially to reading efficiency in ESL children. In the case ofEL1 children, rapid naming and word recognition play a substantial role in wordand text efficiency, whereas PA does not.

One way of thinking about these results is that, in fact, ESL children are morechallenged by the reading tasks precisely because they read in a language in whichthey are not fluent. Therefore, they need to draw on all the cognitive and linguisticresources that they have. This explanation is supported by the observation that inthe ESL group (but not in the EL1 group) most of the cognitive, linguistic, andreading measures correlated significantly with each other. That is, those ESL chil-dren who are more efficient readers are more likely also to have better languageskills, faster naming speed, better developed PA skills, and more advanced wordrecognition skills. It is interesting to consider possible theoretical underpinnings ofthe differences in the amount of variance explained by rapid naming and PA ineach language group. We propose that perhaps these EL1–ESL differences reflectthat in ESL learners the effect of underlying cognitive-linguistic processes is moregeneric or more extensive. It is likely that with increased language proficiency andadditional development of more advanced reading skills these underlying pro-cesses may gradually become more specialized and domain specific, the way theyare in the EL1 group. This hypothesis is worth exploring in future research.

In general, young ESL school children who have acquired a certain level of orallanguage proficiency in English and who developed their oral and literacy skills inan immersion context can be rather similar to their EL1 counterparts in terms of theease with which they can execute basic word recognition processes and read effi-ciently simple narratives. Clearly, aspects of language proficiency such as lexicaland grammatical skills are essential for reading efficiency; the ESL children whowere efficient readers also had higher oral proficiency in English than those ESLchildren who were less efficient. At the same time, simplistic notions of L2 readingperformance that emphasize primarily oral language proficiency need to be re-fined. This refinement can be achieved by considering the cognitive-linguistic pro-cesses that underlie reading processes and that appear to be sources of individualdifferences in efficient reading of EL1 and ESL children. Less efficient reading inESL and EL1 children alike can be attributed to less efficient word recognitionskills and to reduced or less effective access to linguistic information.

Comparing the Profiles of ESL and EL1Efficiency Subgroups

L1-based research suggests that not all children who reach Grade 2 are ready to de-velop their reading efficiency and that some continue to be “dysfluent” (Wolf &Katzir-Cohen, 2001). Results of this study extend this statement to ESL children inthe primary level. The examination of profiles of EL1 and ESL subgroups that dif-fer in their reading efficiency underscores the range of language and reading skills


that exist among ESL (and EL1) learners and provides useful insights into the typeof reading skills that EL1 and ESL children develop and the cognitive and linguis-tic resources they draw on to read with efficiency.

Several observations can be made on the basis of an examination of the effi-ciency group profiles depicted in Figure 1. Most important, the subgroups definedon the basis of reading efficiency are consistently different from each other on cog-nitive, oral language, and reading measures. Next, clearly, regardless of efficiencygroup, EL1 children have better developed oral language skills in English thanESL children. However, the language group effect concerning rapid naming is inthe reverse direction, with ESL children within each efficiency group outperform-ing their EL1 counterparts. (Possible explanations for this finding have been previ-ously discussed with regard to ESL–EL1 differences on rapid automatized letternaming.) Third, it is of interest that ESL children who were classified as high-effi-cient readers had significantly higher scores on PA than the high-efficient EL1children, whereas among low-efficient and poor decoders, EL1 children outper-formed their ESL counterparts. Because the high-efficiency EL1 and ESL groupsdid not differ on nonverbal ability, an explanation for this unexpected result basedon general, nonverbal cognitive ability can be ruled out. However, possibly thisESL advantage in the high-efficient group may be related to the enhancing effectsof bilingualism. It is possible that the high-efficient ESL children benefit fromtheir bilingual status in a way that distinguishes them from ESL children who areless efficient readers. They may be better able to extract subtle phonological dis-tinctions and have more precise phonological representations that may be relatedalso to their relatively better-developed vocabulary (Metsala & Walley, 1998).Finally, it is informative to note that the high-efficiency ESL children had betterdeveloped oral language proficiency in English than the ESL children who werepoor decoders or low-efficiency readers.

There are clinical and research implications to these observations. When youngESL children have problems in developing reading efficiency even when they readsimple materials, attribution to lack of adequate oral language proficiency is notwarranted automatically—especially when ESL children develop their oral and lit-eracy skills in a systematic reading instruction program. The culprit in this casemay be inaccurate and dysfluent word recognition skills and deficits in the under-lying cognitive-linguistic processes necessary for the development of accurate andfluent word recognition skills. In addition to oral language development, such chil-dren may benefit from intervention approaches that focus on the development ofefficient word recognition skills (Gersten & Baker, 2003; Gersten & Geva, 2003;Quiroga et al., 2002).

Future research should continue to explore the development of reading efficiencywith L2 children of different ages, with different levels of oral language proficiency,and with academic reading materials that vary in linguistic and orthographic de-mands. Special attention is also needed to examine the relevance of these findings to


childrenwho, inaddition tobeingL2learners,mayhavea learningdisabilityora lan-guage impairment.This researchwasconducted inurbanandsuburbanareas that areethnically and linguistically mixed, but some immigrant communities are more ho-mogeneous in socioeconomic status and home language. To examine thegeneralizability of these results, large-scale, multilevel studies need to be conductedthat consider the effects of within-child factors and contextual factors, includinglevel of ethnic diversity at the community and school level for language and literacyoutcomes. Finally, given the large number of children who learn to read in an L2without the option of first mastering their L1 reading skills, questions pertaining toL2 reading efficiency and to the impact of different educational practices on readingefficiency and on reading comprehension of academic and narrative texts deservesustained and systematic attention in the near future.

ACKNOWLEDGMENTS

This research was supported by grant 410–96–0851 from the Social Sciences Re-search Council of Canada and a grant from the Ontario Ministry of Education toEsther Geva. Zohreh Yaghoub Zadeh is an analyst at the Canadian Council onLearning.

We thank the staff and children at the Peel Board of Education, the Toronto Dis-trict School Board, the Toronto Separate School Board, and the York Region Sepa-rate School Board of Education for their patience and cooperation.

REFERENCES

Arab-Moghaddam, N., & Sénéchal, M. (2001). Orthographic and phonological processing skills inreading and spelling in Persian/English bilinguals. International Journal of Behavioral Develop-ment, 25, 140–147.

Berninger, V. W., Abbott, R. D., Billingsley, F., & Nagy, W. (2001). Processes underlying timing andfluency of reading: Efficiency, automaticity, coordination, and morphological awareness. In M. Wolf(Ed.), Time, fluency, and dyslexia (pp. 383–414). Timonium, MD: York.

Bialystok, E. (2001). Bilingualism in development: Language, literacy, and cognition. New York:Cambridge University Press.

Bialystok, E., & Herman, J. (1999). Does bilingualism matter for early literacy? Bilingualism: Lan-guage and Cognition, 2, 35–44.

Biemiller, A. J. (1977/78). Relations between oral reading rates for letters, words, and simple texts inthe development of reading achievement. Reading Research Quarterly, 13, 223–253.

Biemiller, A. J. (1981). Biemiller Test of Reading Processes. Toronto, Ontario, Canada: University ofToronto Press.

Bowers, P., Golden, J., Kennedy, A., & Young, A., (1994). Limits upon orthographic knowledge dueto processes indexed by naming speed. In G. Berninger (Ed.), The varieties of orthographicknowledge: I. Theoretical and developmental issues (pp. 173–218). Dordrecht, The Netherlands:Kluwer Academic.


Bowers, P. G., & Wolf, M. (1993). Theoretical links among naming speed, precise timing mechanismsand orthographic skill in dyslexia. Reading and Writing: An Interdisciplinary Journal, 5, 69–85.

Breznitz, Z. (2001). The role of inter-modality temporal features of speed of information processing inasynchrony between visual-orthographic and auditory-phonological processing. In M. Wolf (Ed.),Dyslexia, fluency and the brain (pp. 245–276). Timonium, MD: York.

Breznitz, Z. (2002, June). Brain activity of dyslexic and normal readers during L1 and L2 task perfor-mance. Paper presented at the international Conference on Multilingual and Cross-Cultural Perspec-tives on Dyslexia, Washington, DC.

Carlisle, J. F., & Beeman, M. M. (2000). The effects of language of instruction on the reading and writ-ing achievement of first-grade Hispanic children. Journal of Scientific Studies of Reading, 4,331–353.

Carver, R. P. (1997). Reading for one second, one minute, or one year from the perspective of raudingtheory. Scientific Studies of Reading, 1, 3–43.

Chall, J. S. (1996). Stages of reading development (2nd ed.). Orlando, FL: Harcourt Brace.Chiappe, P., & Siegel, L. S. (1999). Phonological awareness and reading acquisition in English- and

Punjabi-speaking Canadian children. Journal of Educational Psychology, 9, 20–28.Comeau, L., Cormier, P., Grandmaison, E., & Lacroix, D. (1999). A longitudinal study of phonological

processing skills in children learning to read in a second language. Journal of Educational Psychol-ogy, 91, 29–43.

Denkla, M. B., & Rudel, R. G. (1976). Rapid ‘automatized’ naming (R.A.N.): Dyslexia differentiatedfrom other learning disabilities. Neuropychologia, 14, 471–479.

Durgunoglu, A. Y., Nagy, W. E., & Hancin-Bhatt, B. J.,(1993). Cross-language transfer of phonologicalawareness. Journal of Educational Psychology, 85, 453–465.

Ehri, L. (1998). Grapheme-phoneme knowledge is essential for learning to read words in English. In J.Metsala & L. Ehri (Eds.), Word recognition in beginning reading (pp. 3–40). Mahwah, NJ: LawrenceErlbaum Associates, Inc.

Gardner, M. (1990). Expressive One-Word Picture Vocabulary Test–Revised. Novato, CA: AcademicTherapy Publications.

Gersten, R., & Baker, S. K. (2003). English-language learners with learning disabilities. In H. L.Swanson, K. R. Harris, & S. Graham (Eds.), Handbook of learning disabilities (pp. 94–109). NewYork: Guilford.

Gersten, R., & Geva, E. (2003). Teaching reading to English learners in the primary grades: Insights intothe new research base on teaching reading to English learners. Educational Leadership, 60, 44–49.

Geva, E., & Clifton, S. (1994). The development of first and second language reading skills in earlyFrench immersion. Canadian Modern Language Review, 50, 646–667.

Geva, E., & Siegel, L. S. (2000). Orthographic and cognitive factors in the concurrent development ofbasic reading skills in two languages. Reading and Writing: An Interdisciplinary Journal, 12, 1–31.

Geva, E., Wade-Woolley, L., & Shany, M. (1997). Development of reading efficiency in first and secondlanguage. Scientific Studies of Reading, 1, 119–144.

Geva, E., Yaghoub Zadeh, Z., & Schuster, B. (2000). Understanding individual differences in word rec-ognition skills of ESL children. Annals of Dyslexia, 50, 123–154.

Gholamain, M., & Geva, E. (1999). Orthographic and cognitive factors in the concurrent developmentof basic reading skills in English and Persian. Language Learning, 49, 183–217.

Gottardo, A., Yan, B., Siegel, L. S., & Wade-Woolley, L. (2001). Factors related to English reading per-formance in children with Chinese as a first language: More evidence of cross-language transfer ofphonological processing. Journal of Educational Psychology, 93, 530–542.

Jackson, N. E., & Donaldson, G. (1989). Precocious and second-grade readers’ use of context in wordidentification. Learning and Individual Differences, 1, 255–281.

Jastek, S., & Wilkinson, G. S. (1984). Wide Range Achievement Test–Revised. Wilmington, DE: JastakAssociates, Inc.


Johnson, J. S., & Newport, E. L. (1989). Critical period effects in second language learning: The influ-ence of maturational state on the acquisition of English as a second language. Cognitive Psychology,21, 60–69.

Kame’enui, E. J., Simmons, D. C., Good, R. H., & Harn, B. A. (2001). The use of fluency-based mea-sures in early identification and evaluation of intervention efficacy in schools. In M. Wolf (Ed.),Time, fluency, and dyslexia (pp. 307–331). New York: York.

Kirby, J., Parrila, R. K., & Pfeiffer S. L. (2003). Naming speed and phonological awareness as predic-tors of reading development. Journal of Educational Psychology, 95, 453–464.

Kuhn, M. R., & Stahl, S. A. (2000). Fluency: A review of developmental and remedial practices. AnnArbor: University of Michigan, Center for the Improvement of Early Reading Achievement.

LaBerge, D., & Samuels, S. J. (1974). Toward a theory of automatic information processing in reading.Cognitive Psychology, 6, 293–323.

Lesaux, N., & Siegel, L. S. (2003). The development of reading in children who speak English as a sec-ond language (ESL). Developmental Psychology, 39, 1005–1019.

Lesaux, N., & Siegel, L. S. (2004, March). Predictors of reading failure in children from both Englishand non-English speaking (ESL) backgrounds. Sixth BDA International Conference, University ofWarwick, United Kingdom.

Levy, B. A. (2000). Whole words, segments, and meaning: Approaches to reading education. In R.Klein & P. McMullen (Eds.). Converging methods for understanding reading and dyslexia (pp.77–110). Cambridge. MA: MIT Press.

Lindsey, K. A., Manis, F. R., & Bailey, C. E. (2003). Prediction of first-grade reading in Spanish-speak-ing English-language learners. Journal of Educational Psychology, 95, 482–494.

Lipka, O. (2003). The development of reading skills of children with English as a second language. Un-published doctoral dissertation. University of British Columbia, Vancouver.

Manis, F. R., Seidenberg, M. S., Doi, M. L., Mcbride-Chang, C., & Patterson, A. (1996). On the basis oftwo subtypes of developmental dyslexia. Cognition, 58, 157–195.

Metsala, J. L., & Walley, A. C. (1998). Spoken vocabulary growth and the segmental restructuring oflexical representations: precursors to phonemic awareness and early reading ability. In J. L. Metsala& L. C. Ehri (Eds.), Word recognition in beginning literacy (pp. 89–120). Mahwah, NJ: LawrenceErlbaum Associates, Inc.

Meyer, M. S., & Felton, R. H. (1999). Repeated reading to enhance fluency: Old approaches and newdirections. Annals of Dyslexia, 49, 283–306

Naglieri, J. (1989). Matrix Analogies Test. New York: Psychological Corporation.Nassaji, H., & Geva, E. (1999). Cognitive and linguistic processes in adult L2 readers. Applied

Psycholinguistics, 20, 241–267.National Reading Panel. (2000). Teaching children to read: An evidence-based assessment of the scien-

tific research literature on reading and its implications for reading instruction (NIH Pub. No.00–4769). Bethesda, MD: National Institutes of Health, National Institute of Child Health and Hu-man Development.

Perfetti, C. A. (1985). Reading ability. New York: Oxford University Press.Quiroga, T., Lemos-Britton, Z., Mostafapour, E., Abbott, R. D., & Berninger, V. W. (2002). Phonologi-

cal awareness and beginning reading in Spanish-speaking ESL first graders: Research into practice.Journal of School Psychology, 40, 85–111.

Rosner, J., & Simon, D. (1971). The auditory analysis test: An initial report. Journal of Learning Dis-abilities, 4, 40–48.

Savage, R., (2004). Motor skills, automaticity and developmental dyslexia: A review of the research lit-erature. Reading and Writing: An Interdisciplinary Journal, 17, 301–324.

Shany, T. M., & Biemiller, A. (1995). Assisted reading practice: Effects on performance for poor read-ers in grades 3 and 4. Reading Research Quarterly, 30, 382–395.


Shimron, J., & Sivan, T. (1994). Reading proficiency and orthography: Evidence from Hebrew andEnglish. Language Learning, 44, 5–27.

Stage, S. A., Sheppard, J., Davidson, M. M., & Browning, M. M. (2001). Prediction of first-graders’growth in oral reading fluency using kindergarten letter fluency. Journal of School Psychology, 39,225–237.

Stanovich, K. E. (1992). Speculations on the causes and consequences of individual differences in earlyreading acquisition. In P. B. Gough, L. C. Ehri, & R. Treiman (Eds.), Reading acquisition (pp.307–342). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc.

Stanovich, K., & West, R. (1989). Exposure to print and orthographic processing. Reading ResearchQuarterly, 24, 402–433.

Stuart, M. (1999). Getting ready for reading: Early phoneme awareness and phonics teaching improvesreading and spelling in inner-city second language learners. British Journal of Educational Psychol-ogy, 69, 587–605.

Torgesen, J. K. (2001). The theory and practice of intervention: Comparing outcomes from preventionand remediation studies. In A. Fawcett (Ed.), Dyslexia: Theory and good practice (pp. 185–202).London: Whurr.

Wade-Woolley, L., & Geva, E. (1999). Processing inflected morphology in second language word rec-ognition: Russian-speakers and English-speakers read Hebrew. Reading and Writing: An Interdisci-plinary Perspective, 11, 321–343.

Wade-Woolley, L., & Geva, E. (2000). Processing novel phonemic contrasts in the acquisition of L2word reading. Scientific Studies of Reading, 4, 267–293.

Wade-Woolley, L., & Siegel, L. S. (1997). The spelling performance of ESL and native speakers of Eng-lish as a function of reading skills. Reading and Writing: An Interdisciplinary Journal, 9, 387–406.

Wagner, R. K., Torgesen, J. K., Rashotte, C. A., Hecht, S. A., Barker, T. A., Burgess, S. R., et al. (1997).Changing relations between phonological processing abilities and word-level reading as children de-velop from beginning to skilled readers: A 5-year longitudinal study. Developmental Psychology, 33,468–479.

Wang, M., & Geva, E. (2003). Spelling acquisition of novel English phonemes in Chinese children.Reading and Writing: An Interdisciplinary Journal, 16, 325–348.

Wimmer, H., Mayringer, H., & Landerl, K. (2000). The double deficit hypothesis and difficulties inlearning to read a regular orthography. Journal of Educational Psychology, 92, 668– 680.

Wolf, M., & Bowers, P. G. (1999). The double-deficit hypothesis for the developmental dyslexias. Jour-nal of Educational Psychology, 91, 415–438.

Wolf, M., Bowers, P., & Biddle, K. (2000). Naming-speed processes, timing, and reading: A conceptualreview. Journal of Learning Disabilities, 33, 387–407.

Wolf, M., & Katzir-Cohen, T. (2001). Reading fluency and its intervention. Scientific Studies of Read-ing, 5, 211–238.

Woodcock, R. W. (1987). Woodcock Reading Mastery Tests–Revised. Circle Pines, MN: AmericanGuidance Services.

Young, A., & Bowers, T. G. (1995). Individual difference and text difficulty determinants of readingfluency and expressiveness. Journal of Experimental Child Psychology, 20, 428–454.

Manuscript received April 23, 2004Accepted April 19, 2005


Documents

Reading Efficiency in Native English- Speaking and English-as-a … · 2014. 11. 9. · Reading Efficiency in Native English-Speaking and English-as-a-Second-Language Children: The