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URPY #315507, VOL 29, ISS 4

INFLUENCE OF DISTAL AND PROXIMAL COGNITIVEPROCESSES ON WORD READING

J. P. DAS, GEORGE GEORGIOU, and TROY JANZEN

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TABLE OF CONTENTS LISTING

The table of contents for the journal will list your paper exactly asit appears below:INFLUENCE OF DISTAL AND PROXIMAL COGNITIVEPROCESSES ON WORD READINGJ. P. DAS, GEORGE GEORGIOU, and TROY JANZEN

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Reading Psychology, 29:1–29, 2008Copyright C© Taylor & Francis Group, LLCISSN: 0270-2711 print / 1521-0685 onlineDOI: 10.1080/02702710802153412

INFLUENCE OF DISTAL AND PROXIMAL COGNITIVEPROCESSES ON WORD READING

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J. P. DAS3

University of Alberta, Edmonton, Alberta, Canada4

GEORGE GEORGIOU and TROY JANZEN5

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The objectives of the present study were twofold: (a) to explore the interrelationship

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7among distal, proximal cognitive skills, and word reading; and (b) to identify8those cognitive processes that predict phonological awareness and rapid naming.9Seventy First-Nation Canadian children attending grades 3 and 4 were10examined on phonological awareness, rapid naming, Word Identification, Word11Attack, and the cognitive processing measures of planning, attention, successive,12and simultaneous (PASS). Results indicated that phonological awareness and13rapid naming uniquely predicted reading, whereas PASS variables did not,14when the effects of phonological awareness and rapid naming were controlled.15Finally, both phonological awareness and rapid naming were predicted by16planning. Implications for diagnosis of children at risk for reading difficulties17and remediation are discussed.18

Phonological awareness and rapid automatized naming (RAN)19speed are known to be associated with reading for some years20now, and this association has gained importance in understand-21ing dyslexia or poor reading as well as in guiding programs aimed22at remediation of reading difficulties (e.g., Bowers & Newby-Clark,232002; Das & Papadopoulos, 1998; Kirby, Parrila, & Pfeiffer, 2003;24Lovett, Steinbach, & Frijters, 2000; Manis, Doi, & Bhadha, 2000;25Parrila, Kirby, & McQuarrie, 2004; Scarborough, 1998; Stanovich,261992; Wolf & Bowers, 1999). However, it is not certain that a deficit27in phonological awareness and slow RAN are the only cognitive fac-28tors that determine reading performance. Low IQ had been sug-29gested for a long time to be an explanation of reading difficulties,30but this view is much less favored now as poor readers are found at31different IQ levels (Siegel, 1989). This has led to the proposition32

Address correspondence to J. P. Das, University of Alberta, Education North 6-102,Edmonton, Alberta T6G 2G5 Canada. E-mail: j.p.das@ualberta.ca 1

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2 J. P. Das et al.

that IQ may be irrelevant to the definition of learning disabilities. 33While IQ may not be relevant for reading difficulties, cognitive 34processing skills, such as planning, attention, simultaneous, and 35successive (PASS) processing, have been shown to be relevant in 36understanding reading difficulties (Das, Naglieri, & Kirby, 1994; 37Naglieri & Reardon, 1993). Thus, one may conclude that tradi- 38tional IQ is irrelevant to reading disabilities—intelligence is not 39(Naglieri & Reardon, 1993). 40

Since cognitive processes are more useful than IQ in regard to 41an understanding of reading and, especially, reading difficulties, 42we should look beyond phonological coding and consider the fun- 43damental cognitive processing that may be of critical importance 44in acquiring reading among beginning readers and among the 45population with dyslexia. We suggest that for the reader failing to 46learn to read, the process that lies beyond phonological coding is 47a difficulty in sequencing; that is, in appreciating the succession of 48letters within a word and of words within a sentence. Therefore, 49a rational method for helping the child who has word-reading 50difficulties should begin with facilitating successive or sequential 51processing. 52

Successive processing is one of the four major cognitive pro- 53cesses in a theory of intelligence, a theory that is an alternative to 54IQ. Intelligence in this theory is conceptualized in terms of four 55interdependent cognitive processes, namely, planning, attention, 56simultaneous, and successive (PASS; Das et al., 1994). The PASSQ2 57theory is operationalized in the Das-Naglieri Cognitive Assessment 58System (CAS; Naglieri & Das, 1997). Because a considerable num- 59ber of papers have been published on the PASS theory (see, e.g., 60Das, 2005; Das et al., 1994; Das & Naglieri, 2001; Das, Parrila, & Pa-Q3

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61padopoulos, 2005; Naglieri & Das, 2005), for the purposes of this

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62article, we will only focus on how the PASS cognitive processing 63skills are related to phonological awareness, RAN, and word and 64pseudo-word reading. 65

Proximal and Distal Cognitive Processes 66

Undoubtedly, reading acquisition is a complex task that demands 67the synchronous operation of several processing skills. When a 68beginner reader comes across a novel word, he is faced with at 69least five interrelated tasks, which must be undertaken to reliably 70

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Cognitive Predictors of Reading 3

recognize the word. First, all of the letters have to be recognized.71Second, the sounds of the letters or letter combinations must be72retrieved and differentiated from their phonetically confusing73neighbors. Third, all phonemes must be stored in working74memory in their exact order of presentation. Fourth, the entire75set of phonemes in working memory has to be blended together76to form a phonological representation of the whole word. Finally,77this phonological representation of the word has to be used to78gain access to the lexicon. If the word is in the child’s lexicon, he79can read it and move on to the next word. This simple account80of word reading is to identify the interacting operations, not as a81chain of operations actually happening in discrete steps.82

To accomplish these five tasks, a beginner reader will require83the use of both proximal and distal cognitive processes. The prox-84imal cognitive processes are the linguistic skills that are directly85related to the five tasks mentioned above. The most frequently86recognized proximal processes in word reading are phonological87processes, such as phonological awareness and RAN. The distal88cognitive processes are more general and modality-unspecific un-89derlying cognitive processes and are expected to enable the de-90velopment of proximal processes. Thus, the influence that distal91cognitive processes have on reading ability is not necessarily di-92rect but can be mediated by one or several proximal processes. As93discussed later, PASS cognitive processing skills can be considered94typical examples of distal cognitive processes. In what follows we95will first review the effect of proximal cognitive processes (phono-96logical awareness and RAN) on reading acquisition. Then, we will97elaborate on how PASS cognitive processes are related to phono-98logical awareness, RAN, and reading ability, and finally we will99present the current study aimed directly at examining the rela-100tionship between the proximal and distal cognitive processes with101reading.102

Proximal Cognitive Processes: Phonological Awareness103

The most widely acceptable view is that most children experi-104encing reading difficulties have a core phonological deficit that105interferes with their ability to develop phonological awareness and106learn to decode (e.g., Goswami, 2002; Stanovich, 1992; Vellutino,107Fletcher, Snowling, & Scanlon, 2004). Phonological awareness,108

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broadly defined as the ability to perceive and manipulate the 109sounds of spoken words, has been repeatedly shown to be a 110strong predictor of reading ability in alphabetic (e.g., Badian, 1112001; Bus & van Ijzendoorn, 1999; Caravolas, Volin, & Hulme, 1122005; Goswami, 2002; Hulme, Snowling, Caravolas, & Carroll, 1132005; Papadopoulos, 2001; Parrila et al., 2004; Patel, Snowling, 114& de Jong, 2004; Share & Stanovich, 1995; Stanovich, 1992; 115Torgesen, Wagner, & Rashotte, 1994) as well as in non-alphabetic 116orthographies (e.g., Hu & Catts, 1998; McBride-Chang & Ho, 1172005; McBride-Chang & Kail, 2002). It is, therefore, of no surprise 118to us that Scarborough (1998), in her meta-analysis, reported 119correlations between phonological awareness and reading to 120be approximately .46 (see also Swanson, Trainin, Necoechea, & 121Hammill, 2003; for similar meta-analysis findings). 122

Empirical studies have demonstrated that phonological 123awareness measured prior to or at the onset of reading instruction 124successfully predicts reading performance in later years even after 125controlling for possible confounding variables such as print ex- 126posure, letter knowledge, or verbal intelligence (Blachman, 1984; 127Goswami & Bryant, 1990; Kirby et al., 2003; Manis et al., 2000; 128Muter, Hulme, Snowling, & Stevenson, 2004; Wagner et al., 1997). 129For example, Parrila et al. (2004) investigated concurrent and fu- 130ture predictive influence of phonological processing measures on 131reading development in a 4-year longitudinal study. The results 132demonstrated that phonological awareness, measured in grade 1, 133was the strongest predictor of grade 3 reading after controlling 134for the effect of prior reading skills (word identification measured 135in grade 1). Furthermore, phonological awareness measured in 136kindergarten and grade 1 accounted for unique variance in all 137reading measures, even after measures of other phonological pro- 138cessing variables (articulation rate, verbal short-term memory, and 139RAN) were taken into account. Similarly, Kirby et al. (2003) re- 140ported that phonological awareness measured in kindergarten was 141a strong predictor of reading performance in the first 2 years of 142schooling, after controlling for general intelligence and prior read- 143ing achievement (measured with letter recognition). 144

Evidence in support of a causal relationship between phono- 145logical awareness and reading has also been provided in studies in 146which the performance of dyslexics on several cognitive measures 147was compared with that of chronologically and reading-matched 148

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Cognitive Predictors of Reading 5

controls (e.g., Caravolas et al., 2005; Hatcher, Snolwing, & Griffiths, Q81492002; Snowling, Nation, Moxham, Gallaher, & Frith, 1997; Swan &150Goswami, 1997). A causal role in dyslexia has been suggested for151those component skills that are significantly worse in the dyslexic152group compared to younger normal children at the same reading153level (Bryant & Coswami, 1986). The basic rationale for this argu-154ment is that if reading development is responsible for the develop-155ment of a language skill, older dyslexic subjects should be at least156as strong in that language skill when compared to younger normal157subjects at the same reading level. In one of this kind of study, Swan158and Goswami (1997) examined the performance of 15 dyslexic159children, 15 reading age-matched controls, and 15 chronologi-160cally age-matched controls on several literacy skills. Chronologi-161cally age-matched controls were significantly better than any of the162other two groups in all the measures used in the study. Importantly,163dyslexics were significantly poorer than reading age-matched con-164trols on phoneme tapping and initial/final phoneme judgment165tasks.166

By itself the phonological-core deficit does not appear to ac-167count for all that is known about the development of reading prob-168lems. In addition, phonology-based training programs have not169been able to prevent or remediate reading difficulties completely170(Torgesen et al., 2001). Consequently, researchers began to ex-171amine other possible sources of individual differences in reading.172Recently, in their review paper, Wolf and Bowers (1999) argued173that RAN is a second core deficit in reading disabilities that ac-174counts for variance in reading over and beyond the contribution175of phonological awareness.176

Proximal Cognitive Processes: Rapid Naming Speed177

RAN has been defined as the ability to name as quickly as possi-178ble visually presented familiar symbols such as letters, digits, colors,179and objects. RAN performance has been shown to distinguish aver-180age from poor readers during childhood (e.g., Badian, Duffy, Als,181& McAnulty, 1991; Cornwall, 1992; Wolf, Bally, & Morris, 1986) and182into adulthood (Felton, Naylor, & Wood, 1990; Korhonen, 1995). Q9183In addition, even after statistically controlling for IQ (Cornwall,1841992), reading experience (Badian, 1993; Parrila et al., 2004), at-185tention deficit disorder (Compton, Olson, DeFries, & Pennington,186

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2002), socioeconomic status (Felton et al., 1990), articulation rate 187(Parrila et al., 2004), and, most importantly, phonological aware- 188ness (e.g., Bowers, 1995; Kirby et al., 2003; Manis et al., 2000; Savage 189& Frederickson, 2005), RAN has survived as a predictor of reading. 190

Despite the acknowledged importance of RAN in predicting 191reading, there is still no consensus as to what cognitive process or 192processes are driving the relationship between RAN and reading 193and what RAN tasks measure. For example, Torgesen, Wagner, and 194their colleagues (see, e.g., Torgesen, Wagner, Rashotte, Burgess, 195& Hecht, 1997; Wagner & Torgesen, 1987; Wagner et al., 1997) 196subsumed RAN under the phonological processing family, main- 197taining that RAN tasks assess the rate of access to and retrieval of 198stored phonologically based information from long-term memory. 199On the other hand, other researchers have accepted RAN as an 200independent proximal process for reading and proceeded with 201developing competing models to explain why RAN is related to 202reading (e.g., Bowers & Wolf, 1993; Martens & de Jong, 2004; Sav- 203age & Frederickson, 2005; Wolf & Bowers, 1999). Bowers, Wolf, and 204their colleagues (see Bowers, 1995; Bowers & Newby-Clarke, 2002; 205Wolf, Bowers, & Biddle, 2000) have advanced this line of research, 206reaffirming that RAN requires the integrated and coordinated use 207of attentional, perceptual, conceptual, lexical, and motoric sub- 208processes. Importantly, Wolf and Bowers (1999) also argued that 209RAN tasks may be positioned at a “lexical midpoint” (p. 428) in a 210cascading system between apparent problems in reading and wider 211perceptual-motor deficits. This view clearly suggests that links 212should be evident between RAN and distal cognitive processes, 213such as successive processing or planning, which we review next. 214

Distal Cognitive Processes: PASS Processing Skills 215

As mentioned earlier, in response to the need to better concep- 216tualize and measure intelligence, new approaches have been 217proposed. One of the most recent of these approaches is the 218planning, attention, simultaneous, and successive (PASS) theory 219of intelligence (Naglieri & Das, 1997). According to Naglieri and 220Das (1997), planning is the ability to formulate a strategy, execute 221the strategy, and verify whether the strategy is effective for solving 222a problem. Attention has been defined as selectively attending to 223relevant stimuli while inhibiting distracting or irrelevant stimuli. 224

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Cognitive Predictors of Reading 7

Simultaneous processing has been defined as the ability to survey225several elements to form an integrated whole. Finally, successive226processing has been defined as the ability to process information227in serial order.228

A substantial body of evidence has established that successive229processing is central to early reading (Das et al., 1994; Das & Q10230Papadopoulos, 1998; Papadopoulos, 2001). It is significantly231involved in word decoding, especially for pseudo-words and232words to be read aloud (requiring punctuation; Das, Mok, &233Mishra, 1994). Tasks used to operationalize successive processing234correlate strongly with these basic reading requirements, the best235correlation being with the Speech Rate task (the fast repetition236of three simple words), the Naming Time task (naming rows of237single letters, digits, color strips, or simple and familiar words),238and the serial memory tasks for words and sentences (Sentence239Repetition). Simultaneous processing also plays an important240part in basic reading skills, such as blending (in word reading)241and comprehension of meaning (Das et al., 1994). Q11242

In spite of the theoretical importance of examining the243antecedents of phonological awareness, RAN, and reading abil-244ity among the PASS cognitive processing skills, only a few stud-245ies exist that have explored these relationships. For example,246Joseph, McCahran, and Naglieri (2003), in a sample of 62 primary-247grade children referred for reading problems, showed that both248successive and simultaneous processing accounted for 33% of249the variance in phonological awareness. Planning and succes-250sive processing accounted for 27% of the variance in RAN. In251addition, Joseph et al. (2003) demonstrated that PASS variables252were accounting for a small, but still significant, amount of vari-253ance in Letter-Word Identification and Word Attack even after254the effects of phonological awareness and RAN were controlled255for.256

Likewise, working with Greek-speaking grade 1 children,257Papadopoulos (2001) demonstrated that successive processing258and planning were significantly correlated with phonological259awareness measures (Sound Isolation and Phoneme Elision). Nev-260ertheless, their effect faded out when entered into the regression261equation after phonological awareness measures. If we assume262that distal cognitive processes influence reading through their263influence on the proximal cognitive processes, then we should264

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find no additional effect of PASS processes after controlling for 265the effect of proximal cognitive processes. 266

One of the major contributions of this study is that it has ex- 267amined the relationship between proximal and distal cognitive 268processes in a sample of older children. Joseph et al.’s (2003) 269and Papadopoulos’s (2001) studies were conducted with begin- 270ner readers. It would be important to determine (a) how the rela- 271tion between the PASS skills and reading ability may change over 272time and (b) whether PASS theory can provide an alternative way 273of identifying reading difficulties as opposed to traditional intelli- 274gence measures in a sample of older readers. 275

Additionally, the results of this study will have practical 276benefits for intervention. Once we identify the most important 277processing needs of the child, we can concentrate remediation 278in those areas. Notably, several researchers pointed out that 279there are children who are unresponsive to remediation that 280focuses solely on phonological processing practices (e.g., Allor, 281Fuchs, & Mathes, 2001; Al Otaiba & Fuchs, 2002, 2006; Blachman, 2821994; Torgesen, 2002; Torgesen et al., 2001). Blachman (1994) 283called these children “treatment resisters.” We believe that while 284these students did not benefit from a remediation targeting 285the proximal cognitive processes, it is possible that they could 286have benefited if the remediation targeted the distal cognitive 287processes (Papadopoulos, Charalambous, Kanari, & Loizou, 2004; 288Papadopoulos, Das, Parrila, & Kirby, 2003). 289

The Present Study 290

The purpose of the present study was to examine the relationship 291between PASS cognitive processes, phonological awareness, RAN, 292and reading ability with a sample of grade 3 and 4 Native Canadian 293children. An additional purpose was to determine which PASS vari- 294ables best predict phonological awareness and RAN. The present 295work was motivated by our interest in understanding the widely 296prevalent reading disability among children of the American In- 297dian and Native Canadian communities, the First Nation’s (FN) 298children (e.g., Janzen, 2000; Krywaniuk & Das, 1976). Educational 299and school psychologists have to often decide how to regard the 300reading difficulties of Native or First Nation’s children in school. 301For example, to what extent is their poor reading an inherent 302

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predisposition for a specific cognitive style or learning style? In303a recent summary of cognitive styles of FN children (Hilberg &304Tharp, 2002), it was stated that a global or holistic style of organiz-305ing information and a visual style of information representation306may characterize FN individuals. FN students scored higher on307simultaneous processing, whereas Caucasian students preferred308sequential processing. This is consistent with More’s (1989) ear-309lier review of cognitive styles of FN children. Because understand-310ing the relationship between reading and cognitive predisposition311is a first step toward framing special instructional and remedial312programs, research is necessary to test two competing hypothe-313ses. If indeed the majority of FN children are characterized by a314specific cognitive style, then the variables that predict reading per-315formance in the general population (non-FN) will not be entirely316relevant for FN children. On the other hand, if it can be reason-317ably established that FN children cannot be stereotyped in terms318of a specific cognitive or learning style, then the same findings in319regard to cognitive processing correlates of reading in the general320population of learners will be expected among the FN learners.321

Based on the existing literature, we aimed at examining the322following hypotheses:323

1. Phonological awareness and RAN will make independent and324unique contributions to reading ability.325

2. Specific cognitive processes, particularly planning and succes-326sive, will predict phonological awareness and RAN and may ac-327count for variance in reading ability beyond the one accounted328for by phonological awareness and RAN if we assume that the329influence of distal processes is not mediated by proximal ones.330

Method331

Participants332

Seventy-one Canadian native children (First Nation, or FN) in333grades 3 and 4 (31 boys and 40 girls, ages 8.5 to 11.9 years, M = 9.97,334SD = 0.82) from a reservation school in Alberta, Canada, partici-335pated in this study. The school follows English curriculum estab-336lished by the province. Some instruction in Cree is also taught in337the school. All children were expected to perform in English. The338

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school district recently adopted an early literacy program, which 339was implemented several years prior to this study. All of the chil- 340dren for this study resided on reserve and were coming from low- 341SES families. None of the children had an official diagnosis for anyQ12 342reading or behavioral problems and none of them was receiving 343any special education services. 344

Measures 345

RAPID NAMING SPEED 346Object Naming. The Object Naming task from the CTOPP 347

(Wagner, Torgesen, & Rashotte, 1999) was used as a measure of 348rapid serial naming. Participants were required to state as quickly 349as possible the names of six objects (pencil, boat, star, key, chair, 350fish). On two separate sheets, objects were arranged randomly in 351four rows with nine objects in each row. Prior to beginning the 352timed naming, each participant was asked to name the objects to 353ensure familiarity. The two pages were timed separately and the 354time in seconds to name the objects on both pages was the partic- 355ipant’s score. Wagner et al. (1999) reported test–retest reliability 356of .93 for Object Naming for ages 8 to 17. 357

Color Naming. The Color Naming task was adopted from the 358CTOPP (Wagner et al., 1999). This RAN task consists of a set of 359six colors (blue, red, green, black, yellow, and brown) that are 360displayed in random sequence six times for a total of 36 stimuli. 361The individual is told to name the colors from left to right as 362quickly as possible and the total time to complete the RAN task is 363recorded. Before naming the 36 colors, each participant was asked 364to name the colors in a practice trial. Wagner et al. (1999) reported 365test–retest reliability of .89 for Color Naming for ages 8 to 17. 366

Digit Naming. This task was adopted from the CTOPP (Wagner 367et al., 1999). This RAN task consists of a set of six digits (4, 7, 8, 5, 2, 3683) that are displayed in random sequence six times for a total of 36 369stimuli. Subjects are asked to name the digits from left to right as 370quickly as possible and the total time to complete the RAN task is 371recorded. Before naming the 36 digits, each participant was asked 372

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Cognitive Predictors of Reading 11

to name the digits in a practice trial. Wagner et al. (1999) reported373test–retest reliability of .80 for Digit Naming for ages 8 to 17.374

Letter Naming. This task was also adopted from the CTOPP375(Wagner et al., 1999). Participants were asked to name as fast as376possible the names of six letters (a, n, s, t, k, c). Letters were ar-377ranged randomly in four rows of nine letters in each row. As in378the other naming speed tasks, children were asked to name the six379letters in a practice trial before proceeding to the timed trials. The380two pages were timed separately. Wagner et al. (1999) reported381test–retest reliability of .72 for Letter Naming for ages 8 to 17.382

PHONOLOGICAL AWARENESS383Phoneme Elision. The Phoneme Elision task from the CTOPP384

(Wagner et al., 1999) was used as a measure of phonological aware-385ness. This task measures the extent to which an individual can say386a word and then say what is left after dropping out designated387sounds. The task consists of 20 items. For the first two items, the ex-388aminer says compound words and asks the examinee to say the389word and then say the word that remains after dropping one of390the compound words. For the remaining items, the individual lis-391tens to a word and repeats the word and then is asked to say the392word without a specific sound. Participant’s score is the number393of correct responses. Wagner et al. (1999) reported test–retest re-394liability of .79 for Phoneme Elision for ages 8 to 17.395

Word Segmentation. The Word Segmentation task was adopted396from CTOPP as well (Wagner et al., 1999). It consists of 20397items and it measures the ability of an individual to say separate398phonemes that make up a word. The examinee is told to repeat399a word and then to say it one sound at a time. For example, the400examiner tells the examinee to say “book” and then to say it one401sound at a time. Participant’s score is the number of correct re-402sponses. Wagner et al. (1999) reported test–retest reliability of .79403for Word Segmentation for ages 8 to 17.404

COGNITIVE PROCESSING TASKS405The Das-Naglieri Cognitive Assessment System (CAS; Naglieri406

& Das, 1997) is an individually administered test of cognitive func-407tioning for children and adolescents ranging from 5 through 17408

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12 J. P. Das et al.

years of age that was designed to assess the four PASS cognitive 409processes (a) planning, (b) attention, (c) simultaneous, and (d) 410successive. The four PASS scales and the full scale standard scores 411are set at a mean of 100 and SD of 15. The basic battery, which was 412used for this research project, consists of 8 subtests; two subtests 413per PASS scale. Descriptions of the subtests and scales as well as ev- 414idence for the reliability of the individual subtest scores and PASS 415Scale scores are provided in the manual (Naglieri & Das, 1997). 416The CAS has good psychometric properties with average internal 417consistency alpha values for the basic battery as follows: planning 418= .85; simultaneous = .90; attention = .84; successive = 90; and 419full scale = .87. 420

The Planning subtests of the basic battery of CAS include 421Matching Numbers, Planned Codes. In the Matching Numbers 422subtest, children are presented with four pages containing eight 423rows of numbers. For each row, the child is instructed to under- 424line the two numbers that are the same. The time and number 425correct for each page is recorded and the subtest score is calcu- 426lated by combining both time and number correct. The Planned 427Codes subtest contains two pages, each with a distinct set of codes 428arranged in seven rows and eight columns. At the top of each page 429is a legend, which indicates how letters relate to simple codes (e.g., 430A = OX; B = XX; C = OO). The child is instructed to fill in the 431correct code beneath each corresponding letter in any manner 432he chooses. The subtest score is calculated by combining both the 433time and number correct for each page 434

The Attention subtests of the basic battery of the CAS include 435Expressive Attention and Number Detection. For Expressive Atten- 436tion, children 8 years and older are given three pages to complete. 437For the first page, the child reads color words (i.e., blue, yellow, 438green, and red). The words are presented in a quasi-random or- 439der. On the second page, the child is instructed to name the colors 440of a series of rectangles printed in aforementioned colors. On the 441third page, the color words are printed in a different ink color 442than the color the words name (e.g., the word “red” may appear in 443blue ink). The task on the third page is for the child to name the 444color of ink while not saying the color word. The subtest score is 445calculated using time and number correct. The Number Detection 446subtest asks children to find the target stimuli (e.g., the numbers 4471, 2, and 3 printed in an open font) among many distracters (e.g., 448

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Cognitive Predictors of Reading 13

the same numbers printed in a different font). The subtest score449is a ratio of accuracy (total number correct minus the number of450false detections) to total time taken to complete all items.451

The Simultaneous subtests of the basic battery of the CAS in-452clude Nonverbal Matrices and Verbal Spatial Relations. Nonverbal453Matrices items present a variety of shapes and geometric designs454that are interrelated through spatial or logical organization. For455each item the child is required to decode the relationships and456choose the best of six possible answers to complete the grid. The457subtest score is the total number correct. Verbal Spatial Relations458measures the comprehension of logical grammatical descriptions459of spatial relationships. In this subtest, the child is presented with460six drawings, arranged in a specific spatial manner, and a printed461question. Then, the child is instructed to choose one of the six462drawings that best answers the question within the 30-second time463limit. The subtest score is calculated by adding up the total number464of items answered correctly.465

The Successive subtests of the basic battery of the CAS in-466clude Word Series and Sentence Repetition. In Word Series, the467examiner reads the child a series of words and then asks her to468repeat the words in the same order. This subtest uses the following469nine single-syllable, high-frequency words: book, car, cow, dog, girl,470key, man, shoe, and wall. The presentation rate is one word per sec-471ond. The subtest score is the total number of words series correctly472repeated. For Sentence Repetition the child is read 20 sentences473aloud and is asked to repeat each sentence exactly as presented.474The sentences are composed of color words (e.g., “The blue yel-475lows the green”), which reduces the influence of simultaneous476processing and removes semantic meaning for the sentences. The477subtest score is the total number of sentences repeated correctly.478

WORD AND PSEUDOWORD READING MEASURES479The Woodcock-Johnson Tests of Achievement (WJIII; Woodcock,480

McGrew, & Mather, 2001) was used to assess word reading ability.481The Word Identification subtest involves the reading of individual482words with some early items that require correct letter identifica-483tion. Word Attack is a phonetic decoding task where the child is484required to pronounce nonsense words. All reading tests scores485were calculated using the accompanying computer scoring pro-486gram. Scores in reference to a norm group reported for this paper487

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14 J. P. Das et al.

were relative to age norms. Woodcock et al. (2001) report split-half 488reliabilities of .98 for Word Identification and .94 for Word Attack. 489

Procedure 490

This study involved individually administered tests. Assessment was 491carried out by graduate-level students who had some training in 492individual psychological test administration. All testers were thor- 493oughly trained by two of the authors, who also supervised the test- 494ing. Testing typically took place in a quiet and semi-private room 495within the school. All instructions were given in English because 496that was the primary language of the children. 497

In terms of test order, the reading, the phonological aware- 498ness, and the RAN tests were given first during a separate sitting 499from the administration of the cognitive processing measures. 500Reading, phonological awareness, and RAN tests could generally 501be completed within 30 minutes and the cognitive measures gener- 502ally took around 45 minutes to complete. All subjects were assessed 503with the above measures in May and June of the school year. Par- 504ents’ consent was obtained prior testing. 505

Results 506

Preliminary Data Analysis 507

Descriptive statistics for all the variables used in the study are pre- 508sented in Table 1. One participant who was a multiple outlier 509was removed from further analyses. In line with previous stud- 510ies (e.g., Das, Georgiou, & Janzen, 2006; Janzen, 2000), the FN 511students were particularly deficient in word identification (M = 51286.39, SD = 13.16), whereas their word-decoding skills were within 513average (M = 95.11, SD = 9.19). Repeated measures ANOVA’s 514were then conducted in order to determine whether the variation 515among the mean CAS scale scores was significant for this sample 516of children, because no significant variation among CAS scores is 517expected in a sample of normally achieving students. Findings in- 518dicated that there were significant differences in performance on 519mean CAS scale scores; F (3, 210) = 13.12, p < .000, η2 = .434. Post 520hoc analyses revealed that students performed significantly lower 521on the Planning, Successive, and Simultaneous scale than on the 522

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Cognitive Predictors of Reading 15

TABLE 1 Descriptive Statistics for all the Variables in the Study

Variables M SD Min Max

Reading Measures (W-J)a

WID 86.39 13.16 49 117WAT 95.11 9.19 71 119

Rapid Naming (CTOPP)a

Digits 7.82 2.31 2 13Letters 8.14 2.38 4 16Colors 7.45 2.55 2 13Objects 6.59 2.93 1 13

Phon. Awareness (CTOPP)a

Elision 7.32 2.35 3 13Segmentation 10.11 1.76 5 15

Cognitive Measures (CAS)b

Matching Numbers 8.36 2.22 2 13Planned Codes 8.97 2.12 5 15Planning Scale 92.28 11.05 65 115Nonverbal Matrices 8.79 2.35 4 15Verbal Simultaneous 8.88 2.61 3 14Simultaneous Scale 93.10 11.68 67 120Expressive Attention 9.62 2.43 5 18Number Detection 10.37 2.04 3 15Attention Scale 99.96 8.91 82 124Word Series 8.86 2.48 4 14Sentence Repetition 7.88 2.56 2 14Successive Scale 90.59 12.34 61 122CAS Full Scale 91.54 10.22 68 111

Notes. aStandard scores. bScaled scores.

Attention scale (p < .001). There were no significant differences523between students’ performance on the Simultaneous, Successive,524and Planning scales. With the exception of the significant differ-525ence between the scores on the Attention scale and the rest of526the CAS scale scores, these findings suggest that the FN children527behave the same way as other normally achieving children.528

Correlations Among the Different Measures529

The correlations between the different measures used in this study530are shown in Table 2. From this table we can see that planning531among the CAS measures was moderately related with both read-532ing outcomes. Simultaneous processing was significantly related533

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16 J. P. Das et al.

TABLE 2 Correlations Among the Different Measures

Measures 1 2 3 4 5 6 7 8 9 10 11

1. WID — .89∗∗ .41∗∗ .21 .08 .28∗ .38∗∗ .55∗∗ .33∗∗ .52∗∗ .28∗

2. WAT — .42∗∗ .29∗ .07 .23 .39∗∗ .47∗∗ .32∗∗ .51∗∗ .31∗∗

3. Planning — .35∗∗ .46∗∗ .19 .73∗∗ .49∗∗ .30∗∗ .33∗∗ .33∗∗

4. Simultaneous — .08 .24∗ .66∗∗ .09 .23 .17 .035. Attention — .16 .58∗∗ .32∗∗ .41∗∗ .11 .226. Successive — .60∗∗ .23 .36∗∗ .19 .28∗

7. Full Scale — .39∗∗ .43∗∗ .29∗ .33∗∗

8. RAN-DL — .62∗∗ .40∗∗ .179. RAN-CO — .29∗ .23

10. Elision — .31∗∗

11. Segmentation —

Note. RAN DL = RAN Digits and Letters; RAN CO = RAN Colors and Objects; WID =Word Identification; WAT = Word Attack.

∗ p < .05. ∗∗ p < .01.

only with Word Attack and successive processing only with Word 534Identification. Attention was not significantly related to any read- 535ing outcome. In terms of the RAN-reading relationship, the al- 536phanumeric RAN (Digits and Letters) was moderately correlated 537with Word Identification and Word Attack. In line with previous 538studies (see, e.g., Bowey, McGuigan, & Ruschena, 2005; Cardoso- 539Martins & Pennington, 2004; Parrila et al., 2004, Uhry, 2002; Wolf, 540Bowers, & Morris, 1986), the non-alphanumeric RAN (Colors andQ13 541Objects) was only weakly correlated with Word Identification and 542Word Attack. It is also important to note that the correlations be- 543tween the RAN measures and reading were generally higher for 544Word Identification than for Word Attack, a finding that has been 545reported in other studies as well (Manis et al., 2000; Manis, Sei- 546denberg, & Doi, 1999; Wolf & Bowers, 1999; Wolf et al., 2000). 547Phoneme Elision was moderately correlated with Word Identifica- 548tion (r = .52, p < .01) and Word Attack (r = .51, p < .01). On the 549other hand, Word Segmentation was only weakly correlated with 550both reading measures. 551

Correlations between the PASS variables, RAN, Phoneme Eli- 552sion, and Word Segmentation revealed that planning had rela- 553tively higher correlations with all of these variables. From the re- 554maining CAS scales, successive processing had a significant but still 555small correlation with Word Segmentation (r = .28, p < .05) and 556

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Cognitive Predictors of Reading 17

attention with alphanumeric rapid naming (r = 32, p < .01) and557non-alphanumeric rapid naming (r = 41, p < .01).558

Regression Analyses With PASS Variables Predicting Phonological559Awareness and RAN560

In order to examine which PASS cognitive processes best predict561phonological awareness and RAN, stepwise multiple regression562analyses were conducted. Age was controlled before the entrance563of the PASS variables in the regression equation. The analyses564revealed that both phonological awareness and RAN were pre-565dicted by planning (β = .288, p < .05 for phonological awareness566and β = .423, p <.001 for RAN). Simultaneous, successive, and at-567tention processing did not enter into the equation and therefore568did not significantly predict performance on either phonological569awareness or RAN.570

Regression Analyses With PASS Variables, Phonological Awareness,571and RAN Predicting Word Identification and Word Attack572

We then conducted hierarchical regression analyses in order to573answer two important questions; namely, whether phonological574awareness and/or RAN were uniquely predicting reading ability575and whether the effects of the PASS variables were contributing to576reading even after factoring out the effects of phonological aware-577ness and RAN. In order to examine the contribution of RAN and578Phonological Awareness on Word Identification and Word Attack,579we entered Phoneme Elision and alphanumeric RAN as indepen-580dent variables into the regression equation after first controlling581for age. Based on the correlations obtained in Table 2 we decided582to use the alphanumeric RAN to represent RAN and Phoneme Eli-583sion to represent phonological awareness. Both of these measures584had the strongest correlations with Word Identification and Word585Attack. The results of this analysis are of particular interest in the586context of arguments that RAN should not be subsumed under587the overarching category of phonological processing because it588accounts for unique variance in reading over and above the one589explained by phonological awareness (see, e.g., Bowers & Newby-590Clark, 2002; de Jong & van der Leij, 1999; Manis et al., 2000; Parrila591et al., 2004; Wolf & Bowers, 1999; Wolf et al., 2000). Table 3 shows592

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18 J. P. Das et al.

TABLE 3 Summary of Hierarchical Regression Analysis with Age, PhonologicalAwareness, RAN, and PASS Variables as the Predictors and Word Identificationand Word Attack as the Dependent Variables

Word Identification Word Attack

Step Variable β �R2 β �R2

1. Age −.319 .10∗∗ −.304 .09∗

2. Successive .244 .06∗ .198 .043. PA .441 .18∗∗∗ .448 .18∗∗∗

3. RAN-DL .446 .19∗∗∗ .381 .12∗∗

2. Simultaneous .139 .02 .226 .053. PA .460 .20∗∗∗ .446 .18∗∗∗

3. RAN-DL .493 .22∗∗∗ .398 .14∗∗∗

2. Planning .322 .09∗∗ .349 .11∗∗

3. PA .415 .15∗∗∗ .406 .14∗∗∗

3. RAN-DL .440 .14∗∗∗ .316 .07∗

2. PA .471 .21∗∗∗ .469 .21∗∗∗

3. RAN-DL .376 .11∗∗∗ .273 .06∗

2. RAN-DL .498 .22∗∗∗ .407 .15∗∗∗

3. PA .345 .10∗∗∗ .378 .12∗∗∗

4. Successive .123 .01 .088 .004. Simultaneous .079 .01 .167 .034. Planning .080 .01 .155 .02

Note. PA = Phonological Awareness; RAN-DL = Rapid Automatized Naming—Digits andLetters.

∗ p < .05. ∗∗ p < .01. ∗∗∗ p < .001.

that both phonological awareness and RAN were unique predic- 593tors of Word Identification and Word Attack. Alphanumeric RAN 594accounted for an additional 11% of the variance in Word Iden- 595tification and approximately 6% of the variance in Word Attack 596once age and phonological awareness were controlled. Similarly, 597phonological awareness accounted for a significant 10% of the 598variance in Word Identification and 12% in Word Attack once age 599and alphanumeric RAN were accounted for. 600

Furthermore, in order to examine whether the PASS variables 601could explain a significant amount of variance in reading before 602controlling for phonological awareness and RAN, we entered each 603one of the PASS variables (with the exception of attention, because 604it had shown no significant correlations with reading outcomes) 605at the second step of the regression equation following age (en- 606tered at step 1). The results showed that planning significantly 607

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Cognitive Predictors of Reading 19

predicted both Word Identification and Word Attack, whereas suc-608cessive processing significantly contributed only in Word Identifi-609cation. Controlling for the effects of phonological awareness or610RAN (entered at step 2) showed that neither successive nor plan-611ning made a significant contribution to Word Identification and612Word Attack. Given that planning was a predictor of phonologi-613cal awareness and RAN, we also examined whether the effect of614planning on reading ability was mediated by the effect of phono-615logical awareness and RAN. Sobel’s z statistic was used (Preacher &616Leonardelli, 2003). Indeed, phonological awareness mediated the617relationship between planning and Word Identification (Sobel’s618z = 2.12, p = .033) and Word Attack (Sobel’s z = 2.11, p = .034).619In addition, RAN mediated the relationship between planning and620Word Identification (Sobel’s z = 2.95, p = .003) and Word Attack621(Sobel’s z = 2.64, p = .008).622

To sum, the results from our regression analyses suggest that623(a) planning was a common predictor of phonological awareness624and RAN, (b) phonological awareness and RAN made unique con-625tributions to reading ability, and (c) none of the PASS variables626accounted for unique variance in reading ability after factoring627out the effects of phonological awareness and RAN.628

Discussion629

One of the primary objectives of this study was to examine the630relationship between word reading on one hand and both the dis-631tal (PASS cognitive processes) and proximal cognitive processes632(phonological awareness and RAN) on the other. In regard to the633proximal cognitive processes, clearly, the results of this study repli-634cate previous research findings in spite of the ethnic status of the635participants and their low-average performance on real word iden-636tification. Our results suggest that both phonological awareness637and RAN have an additive effect on predicting reading ability (e.g.,638Chiappe, Stringer, Siegel, & Stanovich, 2002; Manis et al., 2000; Par-639rila et al., 2004; Savage & Frederickson, 2005; Wolf et al., 2002).640

Despite the significant correlations observed between the641PASS variables and the reading measures, the PASS processing642contribution to reading did not survive the statistical control of643phonological awareness and RAN. This is a rather surprising find-644ing given previous reports on PASS cognitive processing skills and645

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20 J. P. Das et al.

their predictive power (e.g., Das et al., 1994; Das & Papadopoulos,Q14 6461998; Joseph et al., 2003; Kirby, Booth, & Das, 1996; Naglieri & 647Rojahn, 2004). Accordingly, some may consider the results as evi- 648dence against the usefulness of PASS skills in identifying children 649at risk for reading difficulties. One might further conclude that 650relying on the proximal cognitive processes will suffice to identify 651those children who struggle with reading. In fact, there is some 652evidence that phonological awareness, RAN, and letter knowledge 653alone can predict reading group membership with almost 100% ac- 654curacy (e.g., Badian et al., 1991; Savage et al., 2005). Nevertheless, 655we believe that such a conclusion would be premature because, 656as indicated in the analysis of the mediation effects, both phono- 657logical awareness and RAN mediated the effects of PASS processes 658on reading. It is not the case that PASS cognitive processes are no 659longer related to reading by themselves, but their effect on reading 660is indirect through the effect of proximal cognitive processes. It is 661possible that as the children gain reading experiences, the effect of 662proximal cognitive processes increases relative to the effect of dis- 663tal cognitive processes due to the facilitatory effect reading has on 664proximal cognitive processes, such as phonological awareness and 665RAN (e.g., Compton, 2003; Perfetti, Beck, Bell, & Hughes, 1987;Q15 666Torgesen et al., 1997). We cannot easily attribute the discrepancy 667between our results and those reported in previous studies to ei- 668ther ethnicity or the low-average word identification performance 669of the present sample. 670

The second objective of this study was to examine the predic- 671tors of phonological awareness and RAN among the PASS process- 672ing skills. Based on previous research findings (Das et al., 2000;Q16 673Papadopoulos, 2001), we hypothesized that phonological aware- 674ness would be predicted by successive processing. Certainly, our 675results failed to support this hypothesis. Phonological awareness 676was predicted only by planning. However, the results are in line 677with previous findings in that with older children like the present 678sample, who do not have reading decoding difficulties to any signif- 679icant degree, planning tests rather than successive tests are better 680predictors (Das, Mishra, & Kirby, 1994; Naglieri & Rojahn, 2004). 681

Similar to phonological awareness, RAN was predicted by 682planning. According to Clarke et al. (2005), RAN’s relationship toQ17 683reading might be attributed to the strategic control of where and 684how much to pause in between the articulations of the stimuli. This 685

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Cognitive Predictors of Reading 21

argument is in line with Das et al.’s (1994) finding that poor read- Q18686ers not only paused longer than average readers in a naming task687but also the decision of where to pause was inconsistent. Follow-688ing Wolf and Bowers (1999), it is possible that RAN includes quite689a number of processes, such as (a) attention to the stimulus, (b)690identification of initial stimulus features, (c) integration of visual691features and pattern information with stored orthographic repre-692sentations in the case of letter naming, (d) integration of visual693information with stored phonological representations, (e) access694and retrieval of phonological labels, (f) activation of semantic in-695formation, and (g) motor programming leading to articulation.696Although planning has not been explicitly stated as one of the697subprocesses involved in RAN, it is possible that it taps on the tim-698ing mechanism, which demands a fine cooperation between the699subprocesses. In essence, planning as a prefrontal lobe function700involves executing behavior over time and integrating of informa-701tion (Huey, Krueger, & Grafman, 2006).702

The present findings may also have implications for the cogni-703tive style of FN individuals: that they tend to be stronger in global,704holistic, or simultaneous strategies and, by inference, weaker in705sequential, successive strategies as discussed in the introduction706(More, 1989). In fact, our present results show only a very slight el-707evation of simultaneous score compared to successive score (93.10708and 90.59, respectively), and the difference is not significant. A709distinct cognitive style for FN children, according to the present710study, is not supported. Our results also contradict the “chronically711poor reader” labeling of FN children (Janzen, 2000), if reading712disability is essentially due to decoding deficits best measured by713pseudo-word decoding. Our sample was below average in real word714recognition. While admittedly speculative, we suggest that the715reason is poor vocabulary and inadequate exposure to literacy that716builds up sight word knowledge. The implication for remediation,717therefore, is an important one—if true dyslexia is closely related to718word-decoding deficit, and not to knowledge-base (e.g., Vellutino719et al., 2004), the FN children, in general, do not have a systemic720deficit. Rather, their deficit arises due to inadequate instruction721combined with prevalence of inadequate literacy environment at722home and in the community. Consequently, programs that enable723them to use appropriate cognitive strategies when confronted724with reading and a general spread of literacy should succeed. Our725

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22 J. P. Das et al.

belief is reinforced by a recent study on the efficacy of cognitive 726enhancement training (Hayward, Das, & Janzen, in press).Q19 727

Limitations of the Study 728

The major limitation of this study was its restriction to word reading 729level–dependent variables. Although the ultimate goal of reading 730is comprehension, we did not incorporate tasks of reading com- 731prehension in our study. We also suggest that other tests of phono- 732logical awareness, such as blending and spoonerism, should be 733added to increase the strength of phonological awareness mea- 734sure. Likewise, RAN is weakened if measured with Colors and Ob- 735jects compared to Letters and Digits. Obviously, speed of naming 736objects and colors loses its salience in predicting reading by age 9 737even among the FN who are almost close to the norm at least in 738one of the two tests of reading, in pseudo-word decoding but per- 739form poorly in word identification. Finally, it is worth mentioningQ20 740that future studies should look into direct comparisons between 741the predictors of reading in FN and Caucasian Canadian children 742rather than what has been reported in other studies. 743

Conclusion 744

Several studies have shown that phonological awareness and rapid 745naming are independent predictors of reading ability. Our study 746replicated this finding with a sample of FN children who were 747particularly deficient in word reading. In addition, we examined 748the predictors of phonological awareness and RAN among the 749PASS cognitive processing skills. Given that (a) the antecedents of 750individual differences in phonological awareness and RAN have 751been examined primarily under the rubric of home literacy en- 752vironment and print exposure (see, e.g., Georgiou, Manolitsis, 753Parrila, & Stephenson, 2006; Lepola, Poskiparta, Laakkonen, & 754Niemi, 2005; Senechal, 2006) and (b) both phonological aware- 755ness and RAN share common genetic variance (see, e.g., Petrill, 756Deater-Deckard, Thompson, DeThorne, & Schatschneider, 2006; 757Samuelsson et al., 2005), we provided new evidence of the com- 758mon ground of phonological awareness and RAN by showing that 759they were both predicted by the same distal cognitive processing; 760namely, planning. We have also showed that, in general, the FN 761

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Cognitive Predictors of Reading 23

population of young readers are not dyslexics; those who are poor762readers among them do not have a systemic deficit associated with763their ethnic affiliation and therefore can benefit from remedial764programs that we have used before (Das, Mishra, & Pool, 1995;765Hayward et al., in press). Q21766

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