Processing Speed Deficits in Young Adults with Developmental Dyslexia

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Processing Speed Deficits in Young Adults with Developmental Dyslexia
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english
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Park,Heeyoung
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Doctorate ( Ph.D.)
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University of Florida
Degree Disciplines:
Communication Sciences and Disorders, Speech, Language and Hearing Sciences
Committee Chair:
Lombardino, Linda J
Committee Co-Chair:
Altmann, Lori J
Committee Members:
Logan, Kenneth J
Franks, Bridget A

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deficits -- developmental -- dyslexia -- linguistic -- motor -- nonlinguistic -- processing -- speed -- stimulus -- verbal
Speech, Language and Hearing Sciences -- Dissertations, Academic -- UF
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Communication Sciences and Disorders thesis, Ph.D.
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Abstract:
A current growing body of evidence has shown that along with phonological deficits, impairments of processing speed are characteristic of children and adults with developmental dyslexia. The finding that dyslexic readers have processing speed deficits has led researchers to question whether these speed deficits are domain-general or domain-specific. To date, there is no clear evidence to support either position unequivocally. This study was designed to investigate whether the processing speed deficits in young adults with dyslexia are restricted to linguistic information processing only or also affect speed of nonlinguistic information processing. College students with dyslexia were compared with age-matched normal readers on the tasks in which response times for linguistic or nonlinguistic stimuli of varying complexity were tested in both speech and motor response modalities. When the linguistic or nonlinguistic stimuli were presented on a computer screen, participants were required to speak a number or press a button to answer which of the five test stimuli matched the target stimulus. Results showed that dyslexic readers were significantly slower than age-matched controls on both linguistic and nonlinguistic processing speed tasks and the differences between the two groups significantly increased with the increase of stimulus complexity. The normal readers were significantly faster with linguistic stimuli than with nonlinguistic stimuli at all three levels of complexity while the dyslexic readers failed to show this speed advantage for linguistic stimuli at the highest level of complexity. These findings suggest that while processing speed deficits appears to be domain-general in dyslexics, their processing of linguistic information may become even less efficient when stimuli become complex. This study supports the importance of testing both linguistic and nonlinguistic processing speed in reading assessment batteries and in exploring the efficacy of processing speed interventions at the early stages of reading instruction.
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by Heeyoung Park.
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Thesis (Ph.D.)--University of Florida, 2011.
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Adviser: Lombardino, Linda J.
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Co-adviser: Altmann, Lori J.
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RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2013-08-31

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1 PROCESSING SPEED DEFICITS IN YOUNG ADULTS WITH DEVELOPMENTAL DYSLEXIA By HEEYOUNG PARK A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2011

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2 2011 Heeyoung Park

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3 To my greatest blessing, my husband, Dukhyun Shin

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4 ACKNOWLEDGMENTS I would like to express my most sincere gratitude to my chair, Dr. Linda Lombardino for her generou s support, invaluable guidance, and incessant encouragement and help for all years of graduate study. I would also like to thank my co chair, Dr. Lori Altmann for her thoughtful gu idance and generous mentorin g of my research work. I am also grateful to my o ther dissertation committee members, Dr. Kenneth Logan and Dr. Bridget Franks for their academic a dvice and encouragement. I would also like to express my appreciation to research assistants, Katelyn DiPietro, Denise Magdales, Danielle Schoepski, and Kathe rine Martin for their help with data collection. I would like to thank my lab mates Sunjung Kim Sue Ann Eidson, Rebbecca Wiseheart, and Yiting Ho for sharing many wonderful moments. Lastly, I would like to express my thanks to my family members who have been a constant source of inspiration and motivation for me. I would especially like to thank my husband, Dukhyun Shin for his constant love, enormous understanding, and unfailing encourage ment

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 7 LIST OF FIGURES ................................ ................................ ................................ .......... 9 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .... 12 2 LITERATURE REVIEW ................................ ................................ .......................... 16 Definitions of Dyslexia ................................ ................................ ............................. 16 Models for Subtying Dyslexia ................................ ................................ .................. 17 Processing Speed Deficits in Dyslexia ................................ ................................ .... 20 Auditory Processing Speed Deficits ................................ ................................ 23 Visual Processing Speed Deficits ................................ ................................ ..... 24 Motor Processing Speed Deficits ................................ ................................ ..... 26 Processi ng Speed Deficit Theories ................................ ................................ ......... 27 Interhemispheric Transfer Deficit Theory ................................ .......................... 27 Cerebellar Deficit Theory ................................ ................................ .................. 28 Magnocellular Deficit Theory ................................ ................................ ............ 29 Rationale and Significance of the Study ................................ ................................ 31 Study Objective s ................................ ................................ ................................ ..... 36 3 METHODS AND MATERIALS ................................ ................................ ................ 37 Setting and Participants ................................ ................................ .......................... 37 Recr uitment Setting ................................ ................................ .......................... 37 Participants ................................ ................................ ................................ ....... 38 Participants with Developmental Dyslexia (DD) ................................ ......... 39 Participants with Normal Reading Skills (NR) ................................ ............ 40 Procedure ................................ ................................ ................................ ............... 40 Test Measures ................................ ................................ ................................ ........ 41 Reading Tests to Insure Classification of Dyslexia ................................ ........... 41 Cognition tests ................................ ................................ ........................... 41 Reading performance t ests ................................ ................................ ........ 42 Short Term and Working Memory Tests ................................ ........................... 46 Short term memory test ................................ ................................ ............. 46 Working memory test ................................ ................................ ................. 47 Standardized Processing Speed Tests ................................ ............................ 47 Written and oral symbol digit substitution tests ................................ .......... 47 Symbol copy test ................................ ................................ ........................ 48 Experimental Processing Speed Tests ................................ ............................. 48

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6 Linguistic stimulus verbal response test ................................ .................. 50 Linguistic stimulus motor response test ................................ .................. 50 Nonlinguistic stimulus verbal response test ................................ ............ 51 Nonlinguistic stimulus motor response test ................................ ............. 51 Research Questions and Hypotheses ................................ ................................ ..... 51 Research Question 1 ................................ ................................ ........................ 52 Research Question 2 ................................ ................................ ........................ 52 Data Analyses ................................ ................................ ................................ ......... 53 4 RESULTS ................................ ................................ ................................ ............... 58 Introduction ................................ ................................ ................................ ............. 58 Comparison of Reading and Reading Related Performance ................................ .. 58 Sub Question 1: Group Comparison of Phonological Awareness .................... 59 Sub Question 2: Group Comparison of Rapid Automatized Naming ................ 61 Sub Question 3: Group Comparison of Basic Reading Measures .................... 63 Sub Question 4: Group Comparison of Reading Comprehension .................... 64 Sub Question 5: Group Comparison of Short Term and Working Memory ...... 66 Research Question 1 ................................ ................................ .............................. 68 Research Question 2 ................................ ................................ .............................. 75 5 DISCUSSION ................................ ................................ ................................ ......... 94 Findings from Experimental Processing Speed Tasks ................................ ............ 96 Findings from Standardized Processing Speed Tasks ................................ ......... 102 Clinical Implications ................................ ................................ .............................. 103 Limitations and Fut ure Research ................................ ................................ .......... 106 APPEN DIX A RECRUITMENT FLYER ................................ ................................ ....................... 108 B INFORMED CONSENT LETTER FOR PARTICIPANTS ................................ ...... 109 C QUESTIONAIRE FORM ................................ ................................ ....................... 111 D WRITTEN SYMBOL DIGIT SUBSTITUTION TEST FORM ................................ .. 115 E ORAL SYMBOL DIGIT S UBSTITUTION TEST FORM ................................ ......... 116 F SYMBOL COPY TEST FORM ................................ ................................ .............. 117 G STIMULUS LIST OF EXPERIMENTAL PROCESSING SPEED TESTS .............. 118 LIST OF REFERENCES ................................ ................................ ............................. 126 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 147

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7 LIST OF TABLES Table page 3 1 Mean standard scores on the diagnostic reading tests for students with dyslexia ................................ ................................ ................................ .............. 54 3 2 Mean standard scores on the diagnostic reading tes ts for students with normal reading skills ................................ ................................ ........................... 55 3 3 Examples of four types of linguistic and nonlinguistic processing speed tasks .. 57 4 1 Descriptive statistics for DD and NR groups on cognition, phonological awareness, rapid naming, reading, and spelling measures ................................ 81 4 2 Univariate ANOVAs for DD an d NR comparison on the two phonological awareness tasks ................................ ................................ ................................ 82 4 3 Univariate ANOVAs for DD and NR comparison on the six rapid automatized naming tasks ................................ ................................ ................................ ...... 82 4 4 Univariate ANOVAs for DD and NR comparison on the six basic reading measures ................................ ................................ ................................ ............ 83 4 5 Univariate ANOVAs for DD and NR comparison on the two rea ding comprehension measures ................................ ................................ .................. 83 4 6 Descriptive statistics for DD and NR groups on short term and working memory measures ................................ ................................ .............................. 84 4 7 Summary of mixed three factor ANOVA on short term and working memory measures ................................ ................................ ................................ ............ 84 4 8 Descriptive statistics for DD and NR groups on linguistic and nonlinguistic process ing speed measures ................................ ................................ ............... 85 4 9 Summary of mixed four factor ANOVA on linguistic and nonlinguistic processing speed measures ................................ ................................ ............... 86 4 10 Post hoc pairwise comparisons for the response times between linguistic and nonlinguistic stimulus tasks at the three levels of complexity in the DD group ... 87 4 11 Post h oc pairwise comparisons for the response times between linguistic and nonlinguistic stimulus tasks at the three levels of complexity in the NR group ... 87 4 12 Descriptive statistics for DD and NR groups on standardized processing speed measures ................................ ................................ ................................ 88

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8 4 13 Univariate ANOVAs for DD and NR comparison of the response time measures on three standardized processing speed tasks ................................ .. 89 4 14 Univariate ANOVAs for DD and NR comparison of the accuracy measures on three standardized processing speed tasks ................................ ....................... 89 4 15 Correlation matrix between the response time measures of three standardized tests and four experimental tests of processing speed in DD group ................................ ................................ ................................ .................. 90 4 16 Correlation matr ix between the response time measures of three standardized tests and four experimental tests of processing speed in NR group ................................ ................................ ................................ .................. 90

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9 LIST OF FIGURES Figure page 3 1 The illustration of four types of linguistic and nonlinguistic stimulus response tasks on a computer screen ................................ ................................ ................ 56 4 1 Bar chart for the response time measures of l inguistic processing speed tasks for the DD and NR groups ................................ ................................ ......... 91 4 2 Bar chart for the response time measures of nonlinguistic processing speed tasks for the DD and NR groups ................................ ................................ ......... 91 4 3 Line graph for the response time measures between linguistic and nonlinguistic stimulus tasks at the three levels of complexity in the DD group ... 92 4 4 Line graph for the response time measures between linguistic and nonlinguistic stimulus tasks at the three levels of complexity in the NR group ... 92 4 5 Bar chart for the response time measures of three standardized processing speed tasks for the DD and NR groups ................................ .............................. 93

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10 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfi llment of the Requirements for the Degree of Doctor of Philosophy PROCESSING SPEED DEFICITS IN YOUNG ADULTS WITH DEVELOPMENTAL DYSLEXIA By Heeyoung Park August 2011 Chair: Linda J. Lombardino Cochair: Lori J. P. Altmann Major: Communication Sciences and Disorders A current growing body of evidence has shown that along with phonological deficits, impairments of processing speed are characteristic of children and adults with developmental dyslexia. The finding that dyslexic readers have processing speed d eficits has led researchers to question whether these speed deficits are domain general or domain specific. To date, there is no clear evidence to support either position unequivocally. This study was designed to investigate whether the processing speed de ficits in young adults with dyslexia are restricted to linguistic information processing only or also affect speed of nonlinguistic information processing. College students with dyslexia were compared with age matched normal readers on the tasks in which r esponse times for linguistic or nonlinguistic stimuli of varying complexity were tested in both speech and motor response modalities. When the linguistic or nonlinguistic stimuli were presented on a computer screen, participants were required to speak a nu mber or press a button to answer which of the five test stimuli matched the target stimulus. Results showed that dyslexic readers were significantly slower than age matched controls on both linguistic and nonlinguistic processing speed tasks and the differ ences

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11 between the two groups significantly increased with the increase of stimulus complexity. The normal readers were significantly faster with linguistic stimuli than with nonlinguistic stimuli at all three levels of complexity while the dyslexic readers failed to show this speed advantage for linguistic stimuli at the highe st level of complexity These findings suggest that while processing speed deficits appears to be domain general in dyslexics, their processing of linguistic information may become eve n less efficient when stimuli become complex. This study supports the importance of testing both linguistic and nonlinguistic processing speed in reading assessment batteries and in exploring the efficacy of processing speed interventions at the early stag es of reading instruction.

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12 CHAPTER 1 INTR ODUCTION Over the last two decades, the majority of the research literature on developmental dyslexia has focused on examining relationships between phonological decoding and encoding at both the lexical and sub lexical levels for component reading skills. The existence of a phonological weakness as a core deficit in children who have dyslexia has been demonstrated in numerous studies of children and adults with dyslexia (Bradley & Bryant, 1983; Catts 1989; Catts & Kamhi, 2005; Felton, Naylor, & Wood, 1990; Goswami 2000; Mann & Brady, 1988; Ramus 2003, Share, 1994; Snowling, 1981, 2000, Stanovich, 1988; Vellutino, Fletcher, Snowling, & Scanlon, 2004; Wagner & Torgesen, 1987). Broadly, individuals with dyslexia are characterized as having primary difficulties in phonological processing, such as perceiving, constructing, maintaining, and retrieving phonological representations; word decoding and word recognition; spelling and reading fluency in spite of demonstrating adequate abilities in language comprehension and production. In beginning readers, phonological awareness is one of the most powerful diagnostic indicators of later reading achievement. As a consequence of the strong relationship between phonological awar eness in young children with and without high risk factors for developing reading difficulties and their later reading achievement developing a sensitivity to the phonological structure of words along with the ability to manipulate the sounds in words ha s been targ eted as crucial skill s in young children's preparation for learning to read (Calfee, Lindamood, & Lindamood, 1973; Ehri et al., 2001; Torgesen, Wagner, & Rashotte, 1994; Wagner et al., 1997). Smith, Simmons, and Kameenui (1995) reviewed 28 studie s on phonological awareness and concluded that this skill is a reliable predic tor of later reading achievement in

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13 children from preschool through sixth grade. Researchers have also found that the robust relationship between phonological awareness and readi ng success persists in adolescents and adults who have dyslexia (Fawcett & Nicolson, 1995; Wilson & Lesaux, 2001). In addition to the focus on the explicit phonological dimension of language, several researchers have suggested that processing speed impairm ent appear s to be a key risk factor in both children and adults who have dyslexia (Berninger, Abbott, Billingsley, & Nagy, 2001; Catts, Gillispie, Leonard, Kail, & Miller, 2002; Wolf & Bowers, 1999). The evidence that dyslexic readers have slower speed of processing has been mainly shown from their poor performance on the tests of rapid automatized naming (RAN). RAN measures the rate of access to and retrieval of lexical information and has been used as one index of verbal processing speed. While there are varying theories about what RAN truly assesses ( e.g., measuring lexical retrieval, automaticity, executive function, or all of these processes) speed of proc essing is a core feature of the RAN task. Many studies have demonstrated that RAN performance is a strong predictor of reading in normally developing and in reading impaired children (Ackerman & Dykman, 1993; Badian 1995, 1996; Bowey, Storey, & Ferguson, 2004; Lovett, 1992; McBride Chang & Manis, 1996; Meyer et al., 1998a, 1998b; Snyder & Downey, 1995; Spring & Davis, 1988; Wolf, Bowers, & Biddle, 2000; Wood & Felton, 1994). Wolf, Bowers, and Biddle (2000) found that naming speed consistently accounts for variance in reading after controlling for the effects of phonological awareness. Furthermore, t hese naming speed deficits have been identified consistently in adolescents and young adults with

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14 dyslexia (Hutchens, 1989; Kinsbourne, Rufo, Gamzu, Palmer, & Berliner, 1991; Korhonen, 1991b; Wolff, Michel, & Ovrut, 1990). The importance of processing speed in reading performance is emphasized by the fact that reading is a cognitive activity that requires information processing under time constraints (Breznitz, 2006). Slow processing speed reduce s reading fluency and as a result, hinder s efficient oral reading rate and reading comprehension. The finding that naming speed deficits are common in individ uals with dyslexia le n d s support to the hypothesis that dyslexia is largely a deficit of linguistic processing (Liberman & Shankweiler, 1991; Mody, Studdert Kenned y, & Brady, 1997; Stanovich & Siegel, 1994; Vellutino & Scanlon, 1987). However, recent findings showing processing speed deficits in individuals with dyslexia on non linguistic tasks too, have led some researchers to question whether the processing speed d eficits are domain specific and rest ricted to speed of activation in the linguistic processes alone or whether they represent a domain general deficit that affects speed of both ling uistic and nonlinguistic processing M ore general processing speed deficit s for dyslexic readers, beyond rapid naming problems, have been investigated in previous studies. Their impaired processing speed was observed in slow lexical processing (Baddeley, Ellis, Miles & Lewis, 1982; Griffiths, 1988; Seymour, 1986), longer choice reaction times to an auditory tone, slow lexical decision speed (Nicolson & Fawcett, 1994), decreased cross modality integration rates (Nicolson & Fawcett, 1993; Yap & van der Leij, 1993), and reduced ability to detect visual flicker (Lovegrove, Garzia, & Nicholson, 1990). Furthermore, several studies have documented that nonlinguistic processing deficits are evident across multiple sensory modalities (Cestnick, 2001; Farmer & Klein, 1995; Laasonen, Tomma Halme Lahti

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15 Nuuttila, Service, & Virsu, 2000; Laaso nen, Service, & Virsu, 2002 b ; Stein & Talcott, 1999; Tallal, Miller, & Fitch, 1993; Talcott et al., 2000). However, despite the evidence of nonlinguistic deficits in individuals with dyslexia, numerous methodological differences across studies has preclude d an unequivocal specific or domain methodology for measuring processing speed in identically formatted linguistic and nonlinguistic tasks with the same subject groups is essential. This study aims to compare the performance of linguistic and nonlinguistic processing speed measures in young adults with and without dyslexia, in order to investigate whether the processi ng speed deficits in dyslexic readers are restricted to processing speed deficits on linguistic tasks only or whether processing speed deficits are evident on both linguistic and nonlinguistic tasks.

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16 CHAPTER 2 LITERATURE REVIEW The primary aim of this st udy is to compare the performance of young adults with and without dyslexia on the linguistic and nonlinguistic processing speed measures. This chapter reviews literature on dyslexia under the following headings: definitions of dyslexia, models for subtypi ng dyslexia, processing speed deficits associated with dyslexia, and theories underlying processing speed deficits. The rationale and objectives of this study follow. Definitions of Dyslexia Developmental dyslexia has been defined in several different ways depending on the interpretations of genetic, developmental, or environmental influences on reading in children who, despite conventional classroom experience, fail t o attain the language pecific language based disorder of constitutional origin characterized by difficulties in single word decoding, usually reflecting insufficient phonological processing. These difficulties in single word decoding are often unexpected in relation to age and other cognitive and academic abilities; they are not the result of generalized developmental disability or sensory empirical data has demonstrated that dyslexia stems from an underlying deficit in the phonological processing sy stem (Beitchman & Young, 1997; Grigorenko, 2001; Mody, 2003; Pennington, 1999; Ramus, 2003; Shaywitz, 1996; Snowling, 2000; Stanovich, 1988). Difficulties in detecting, segmenting, and

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17 manipulating individual phonemes in spoken words were consistently repo rted in children and adults with dyslexia. More recent studies have converged to support the conclusion that the lack of the development of fluent reading is another hallmark characterizing dyslexic readers (Berninger, Abbott, Billingsley, & Nagy, 2001; Ca tts, Gillispie, Leonard, Kail, & Miller, 2002; Wolf & Bowers, 1999). Slow and laborious reading has been observed in dyslexic readers of all ages. The most current definition of dyslexia was adopted by the International Dyslexia Associat ion (IDA) Board of Directors in 2002, and also used by the National Institutes of Child Health and Human Development (2002). T he IDA defines neurological in origin. It is characterized by difficulties with accurate and/or f luent word 2003, p. 2). This definition reflects that slow reading speed became widely recognized as a key factor in understanding dyslexia. Models for Subtying Dyslexia A growing body of evidence that dyslexic readers have poor reading speed has influenced the investigation of behavioral subtypes of dyslexia. T he t raditional dual r oute mo del of word recognition proposes that skil led readers convert visual stimuli into pho nological code s through two main processes, lexical reading and sublexical reading (Coltheart, 1978; Castles & Coltheart, 1993). The lexical reading procedure relies on whole word recognition and allows efficient processing of familiar regular and irregula r words, but not unfamiliar words or pronounceable non words. The sublexical reading procedure relies on grapheme phoneme correspondence rules and allows successful processing of unfamiliar words and non words. These two procedures are required for compete nt reading and impaired functioning in one procedure leads to over reliance on

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18 the other procedure. Based on the dual route model, Castles and Coltheart (1993) classified children with dyslexia into one of two subtypes, phonological dyslexics and surface d yslexics P honological dyslexia represents difficulties in non word reading from a deficit in the sublexical pro cessing route. In contrast, surface dyslexia represents difficulties in irregular word reading from an impairment or delay in the lexical proces sing route with an intact sublexical processing. More specifically, children with phonological dyslexia have more difficulty sounding out unfamiliar words and non words than recognizing familiar words as whole units, coupled with phonological awareness def icits. These problems are the most common reading deficits observed among children with dyslexia. They tend to make reading errors that deviate visually or phonetically from the written word, with partially preserved letter sound correspondences, such as r eading (Curtin, Manis, & Seidenberg, 2001; Snowling, Stackhouse, & Rack, 1986). Hulme and Snowling (1992) suggested that dyslexic readers have relatively intact semantic and syntactic skills despite their phonological difficulties, thus they use language skills outside of the phonological module to bootstrap their reading. On the other hand, children with surface dyslexia are characterized by difficulties with rea ding sight words or exception words (words that do not conform to predictable grapheme phoneme correspondence rules), with good non word decoding. They tend to read the exception words as though they were regular, studies have suggested that pure surface dyslexia is relatively rare and that these cases can be defined as a soft subtype, in which exception word reading is poorer than non

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19 word reading (Manis et al., 1996; Snow ling, Goulandris, & Defty, 1998; Stanovich, Siegel, & Gottardo, 1997). Their spelling errors are generally pho nologically accurate, but indicate an incomplete knowledge of spelling sound consistencies, such as spelling Curtin, Manis, & Seidenberg, 2001 ). Goulandris and Snowling (1991) suggested that surface dyslexic readers reach the full alphabetic phase, but do not possess extensive knowledge of higher order graphophonemic contingencies. Hendriks and Kolk (1 997) found that surface dysl exics displayed reading errors characteristic of phonological dyslexia when reading under time constraints. They suggested that word decoding skills are also fragile and slow to activate in children whose profiles are characteristic of surface dyslexia. Sl ow nam ing speed as a second core deficit in dyslexia has been used as an index to support the double d eficit h ypothesis (Bowers & Wolf, 1993 ). This hypothesis suggests that deficits in phonological awareness and naming speed are separate sources of dysfun ction in reading Based on this hypothesis, individuals with dyslexia can be classified into one of three subtypes of reading impairment: phonological deficit subtype, naming speed deficit subtype, and double deficit subtype. The phonological deficit subty pe is characterized as having significant deficits in phonological awareness with average naming speed ability, consequently showing difficulties with phonological decoding in reading. The naming speed deficit subtype is characterized as having significant disabilities in naming speed with average phonological skills, consequently showing difficulties with fluent and timed reading. The double deficit subtype is defined as having both phonological awareness and naming speed deficits, consequently showing pro blems with all components of reading. Individuals with double deficits are

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20 the most severely impaired readers Some researchers have argued that rapid naming is a component of phonological processing when defined code retriev al., 1996). However, a considerable number of studies have demonstrated that naming speed deficit is independent of phonological awareness thus it represents as a separate core defici t in dyslexics (Bowers, 1989; Bowers, Steffy, & Tate 1988; Goldberg, Wolf, Cirino, Morris, & Lovett, 1998; McBride Change & Manis, 1996 ; Wolf, 1997, Wolf, Bowers, & Biddle, 2000). Wolf (1997) found that rapid naming made a unique contribution to word readi ng beyond phonological awareness. Goldberg et al. (1998) and Wolf et al. (2000) reporte d that there were no significant relationships between phonological awareness and naming speed tasks. Processing Speed Deficits in Dyslexia Processing speed refers to an ability to automatically and fluently perform simple or routine cognitive tasks, particularly under timed conditions. Processing speed has been shown to increase from childhood to adolescence on a variety of perceptual, cognitive, and linguistic tasks (Ka il, 1979, 1991a; Kail & Hall, 1994; Wickens, 1974). Salthouse and Kail (1983) suggested that information processing speed increases rapidly through ea rly childhood but increases less rapidly during adolescence. Hale (1990) found that 15 year olds and young adults are 1.5 times faster than 12 year olds and 1.82 times fa ster than 10 year old children on four different cognitive processing tasks (choice reaction time, letter matching, mental rotation, and abstract matching). Researche r s have attempted to deter mine if processing speed develops at the same rate across a range of cognitive processes or if the speed of each process develops at a unique rate. Kail (1988a) investigated developmental changes in the speed of five

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21 separate cognitive processes (visual se arch, memory search, analogical reasoning, mental addition, and mental rotation tasks) between 8 and 21 years of age He found that the rate of developmental change was similar for the five processes. Additional studies support that the mechanism underlyin g age differences in processing speed is a general developmental mechanism (Fry & Hale, 1996; Kail, 1993 ; Miller & Vernon, 1997). However, some studies suggest that developmental change s in processing speed can be consistent within the same domain of proce sses but can vary across different domains. A simple mathematical equation was introduced by Cerella and Hale (1994) to predict the response time (RT) latencies of the child groups from those of young adults: RT child = m age RT adult Using this equation, chi specific age (RT child adult ) on the same tasks by multiplication of a slowing coefficient ( m age ). The m age corresponds to unique rate values for different domains of tasks and it should be greater than 1 because children are slower than adults. A large number of studies have confirmed that dyslexic readers are slower on most reading and reading related tasks than their typical reading peers (Adams 1990; Breznitz, 2003b; Compton & C arlisle, 1994; Felton, Naylor, & Wood 1990; Flowers 1993; Korhonen, 1995; Shankweiler & Liberman, 1989; Stanovich, 1988; Wagner & Torgesen 1987). There are some theories to explain why dyslexic readers show impaired reading speed. Tallal and colleagues sug results from a time serial processing deficit (Talla l 1980; Tallal, Curtis, & Kaplan, 1988; Tallal, Miller, & Fitch, 1993, 1995). This deficit is believed to disturb the integration of rapid sensory information that is required for effective speed reading. Yap a nd v an der

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22 their difficulties in simultaneously coordinating stimuli from different modalities and systems. Bower and Wolf (1993) proposed the mistimin g hypothesis to explain the depressed word decoding characteristic of reading disabilities They emphasized that dyslexic readers have an impaired timing mechanism and their slow reading result s from a mistiming between the orthographic and th e phonologica l information that impedes the integration needed f or successful word reading. Further studies support that dyslexic readers have an impaired capacity to organize and integrate stimuli for rapid information processing (Breznitz & Misra, 2003; L l inas, 1993; Wolff, 1993). Lovegrove (1993b) addressed the causal nature of impaired reading speed in the transient deficit hypothesis. This hypothesis suggests that reading deficiencies in dyslexic readers are the result of inefficient interactions between two separa te but interactive visual systems, transient and sustained visual systems, for the processing of temporal information. Abundant evidence of slow and laborious reading in dyslexic readers has led researchers to investigate whether slow processing speed in d yslexics is restricted to linguistic activation alone or whether it is a more generalized deficit that impacts processing sp eed in other cognitive domains Some studies have claimed that linguistic processing and t hat nonlinguistic deficits are uninformative with respect to the diagnosis and treatment of dyslexia (Adams, 1990; Liberman & Shankweiler, 1991; Mody, Studdert Kennedy, & Brady, 1997; Stanovich, 1988; Stanovich & Siegel, 1994; Vellutino & Scanlon, 1987). H owever, a growing body of evidence has shown that many dyslexic rea ders exhibit impairments in nonlinguistic domain s as well as linguistic domains suggesting that a domain general

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23 model might provide a more accurate theoretical framework for understanding the nature of processing speed deficits in dyslexics. (Cestnick, 2001; Farmer & Klein, 1995; Laasonen, Halme, Lahti Nuuttila, Service, & Virsu, 2000; Laasonen, Service, & Virsu, 2002 b ; Stein & McAnally; 1995; Stein & Talcott, 1999; Tallal, Miller, & Fitch 1993; Talcott et al., 2000). Auditory Processing Speed Deficits Nicolson and Fawcett (1990) developed the dyslexic automatization d eficit (DAD) hypothesis suggesting that dyslexic children suffer from a deficit in the process of automatizing a range of skills including phonological, memory, and motor skills (the failure to fully automatize any skill). Their empirical studies using nonlinguistic stimuli presented in the auditory modality (Nicolson & Fawcett, 1990, 1993) found that dyslexic ormance tends to deteriorate with increasing complexity of task conditions. A significant difference between normal and dyslexic children appeared in a selective choice reaction time task in which they were told to push the button for the low tone and igno re the high tone, but not in a simple reaction time task in which they were told to push the button when you hear the tone. To explain the different performance in the simple and complex conditions, they supplemented their DAD hypothesis with the conscious c ompensation (CC) hypothesis which addresses that dyslexic children are able to perform at normal levels most of time by committing a large part of their attention resources to tasks, despite their impaired automatic processing. The CC hypoth esis predicts that dyslexic children will tire more easil y due to overloaded attention, resulting in a break down in performance during more complex tasks. Processing speed difference between dyslexic and normal readers has been found in other auditory studies. Stein a nd McAnally (1995) studied sensitivity to auditory sound waves in

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24 dyslexic adults and they found that dyslexic readers completed the task in a longer time frame with more mistakes than normal readers Dyslexics also exhibited longer choice reaction time to frequency modulated tones when two or more stimuli were presented sequentially (Stein & McAnally, 1995; Witton et al., 1998). Further auditory processing deficits in dyslexics has been observed in gap detection, tonal pattern discrimination, frequency dis crimination, auditory rhythm sensitivity, and auditory fusion tasks (Amitay, Ahissar & Nelken, 2002, Farmer & Klein, 1993; Ludlow, Cudahy, Bassich, & Brown, 1983; McCroskey & Kidder, 1980; Pinheiro, 1977; Tallal, 1980; Talcott & Witton, 2002; Thomson, Frye r, Maltby, & Goswami, 2006; Watson, 1988, 1992; Wright, Bowen, & Zecker, 2000). Visual Processing Speed Deficits processing speed has been constantly reported in the visual domain. Lovegrove and collaborators investigated visible persi stence and contrast sensitivity in dyslexic children (Badcock & Lovegrove, 1981; Lovegrove, Bowling, & Badcock, 1980a ; Lovegrove, Slaghuis, Bowling, Nelson, & Geeves, 1986; Slaghuis & Lovegrove, 1985). Subjects were required to report whether or not they h ad seen a luminance matched blank stimulus between repeatedly presented grating stimuli (i.e., repetitive pattern of black and white bars). The gratings ranged between low and high spatial frequencies. Low and high spatial frequencies were determined by t h e number of cycles (one cycle = one black plus one white) per degree of visual angle (e.g., l ow spatial frequency = 2 cycles per degree ; hi gh spatial freque ncy = 12 cycles per degree ) D uration of visible persistence increases with increas ing spatial frequ ency (i.e., more time to detect the blank field in the high spatial frequencies). Dyslexic children showed a significantly longer lasting visible persistence than normal children at low spatial

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25 frequencies and less sensitivity to gratings, particularly at low sp atial frequencies. These difference s were also found in high temporal frequency stimuli rapid flicking gratings (Baro, Garzia, & Lehmkuhle, 1996; Martin & Lovegrove, 1987). Eletrophysiological s were reduced or delayed for stimuli with low spatial frequencies and high temporal frequencies ( Kubov, Kuba, Peregrin, & Novkov, 1995 ; Lehmkuhle, garzia, Turner, Hash, & Baro, 1993; Liv ingstone, Rosen, Drislane, Galaburda, 1991; Skottun, 2000). Based on the fact that transient visual channels inhibit sustained visual channels during each saccadic eye movement, L ovegrove and colleagues (198 6) proposed that increased visible persistence in dyslexics reflects a failure of the transient system on sustained inhibition. In a visual flicker fusion study, Chase (1996) indicated that dyslexic children required much longer ISIs (interstimulus intervals: the temporal interval betwe en the offset of one stimulus and the onset of another) to see two visual images tha t were pre sented in rapid succession. Additional s tudies have shown that individuals with dyslexia have longer visual persistence and slower visual integration. These deficits w ere demonstrated through a variety of information processing tasks such as temp oral order judgments, metacontrast judgments, flicker sensitivity tests, visual masking, and coherent motion detection tasks (Bjaalid, Hoien, & Lunberg, 1993; Breitmeyer, 1993; Demb, Boyton, & Heeger, 1998; Di Lollo, Hansen, & McIntyre, 1983; Eden, Stein, Wood, & Wood, 1995; Galaburda & Livingstone, 1993; Hansen, Stein, Orde, Winter, & Talcott, 2001; Hayduk, Bruck, & Cavanagh, 1993; Raymond & Sorensen, 1998; Ridder, Borsting, & Banton, 2001; Slaghuis, Lovegrove, & Davidson, 1993 ; v an Ingelghem, Boets, van W ieringen,

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26 Ghesquie`re, & Wouters, 2004; Wilmer, Richardson, Chen, & Stein, 2004; Willows, Kruck, & Corcos, 1993; Wright & Groner, 1993; Zeffiro & Eden, 2000). Motor Processing Speed Deficits Research on dyslexia has been extended to the study of motor func tions as well. Nicolson and Fawcett (1990) found that dyslexics wer e significantly impaired in dual task conditions. They compared normal and dyslexic readers on the performance of dual tasks that included balance tasks as a primary task (e.g., beam balanc e on one foot or beam walking ) and counting backwards or performing a choice reaction task as a simultaneously performing second task. Dyslexics performed comparably to typical readers on the balance tasks (single task), but their balance deteriorated sign ificantly when required to perform the additional task simultaneously. Nicolson and Fawcett suggested that this impairment stemmed from failure to completely automatiz e skills. Similarly, Wolff Michel, Ovrut and Drake (1990) showed that dyslexics perform ed significantly m ore poorly than controls on asynchronous bimanua l tapping tasks, but not on synchronous unimanual tasks. They attributed these difficulties to temporal resolution deficits or interhemispheric communication impairments. Moreover, Wolff (20 02 ) reporte d that dyslexics have motor related timing deficits on measures of syllable rhyming, unimanual fingertip tapping to a metronome, and bimanual motor coordination. Rae and collaborators (2002) and Stoodley and Stein (2006) found that dyslexics per formed significa ntly slower than controls on a peg moving task. On a task of speech articulation, Wolff, Michel and Ovrut ( 1990 ) found that dyslexic readers made more deviations than their non dyslexic peers when repeating two or three syllable nonsense s tring in time with varying metronome speeds. Fawcett and Nicolson (2002) also found

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27 that dyslexic children have deficits in the speeded production of single articulatory gestures as well as in articulation. Processing Speed Deficit Theories Interhemispheri c Transfer Deficit Theory Neuropsychological studies have suggested that dyslexia is an outcome of impaired communication or integration of auditory, visual, or tactile information between the hemispheres (Beaton, 1997; Gladstone & Best, 1985; Gladstone, B est, & Davidson, 1989; Goldberg & Costa, 1981; Gross Glenn & Rothenberg, 1984; Markee, Warren, Morre, & Theberge, 1996 ; Velay, Daffaure, Giraud, & Habib, 2002). hemisphere is involved in pattern recognition, creativity, spatial orientatio n, face and object recognition, and processing of internal information while the left hemisphere is associated with language and logic skills, sequence and number recognition, sensitivity to time, and processing of external information (Carter, 1998). Read ing requires the integration of diverse brain functions, such as spatial, phonological, orthographic, and semantic processing, from both hemispheres. Ineffective interhemispheric communication has been proposed as a cause of the reading difficulties in dys lexia. Studies using magnetic resonance imaging (MRI) have shown substantial differences in the corpus callosum structure between dyslexic and typical readers. The corpus callosum is a bundle of nerve fibers which connect the two hemispheres, allowing for interhemispheric information transfer. MRI studies have reported an increase in the size of the corpus callosum in dyslexic readers, especially in the splenium: the posterior portion of the corpus callosum (Duara et al., 1991; Rumsey et al., 1996) and the isthmus: the portion between the body and the splenium of corpus callosum (Robichon & Habib, 1998; Rumsey et al., 1996). Interestingly, Hynd and colleagues (1995) found

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28 that dyslexics have a smaller genu: the anterior end of the corpus callosum region than typical readers. On the other hand, some studies have investigated the transfer time of information between hemispheres (inter hemisphere transfer time: IHTT). Long non symmetrical delay in IHTT has been observed in finger localization tasks ( Fabbro, Pese nti, Facoetti, Bonanomi, & Lorusso, 2001 ; Markee, Brown, & Moore, 1996; Moore, Brown, Markee, Thberge, & Zvi, 1995, 1996; Summerfield & Michie, 1993). These tasks involve imitating finger sequences on the same or opposite hand when fingers are touched seq uentially. Dyslexic readers performed more slowly and made more errors than control readers in the across hands condition (imitating on opposite hand). This interhemispheric deficit theory has been consistently supported by various studies using morphologi cal, electrophysiological, computational, and behavioral techniques (Badzakova Trajkova, Hamm, & Waldie, 2005; Beaton, Edwards, & Peggie, 2005; Duara et al., 1991; Robichon & Habib, 1998; Rumsey et al., 1996; Shillcock & Monaghan, 2001 ; Sotozaki & Parlow, 2006). Cerebellar Deficit Theory Cerebellar dysfunction has been suggested as an underlying causal factor of dyslexia (Nicolson & Fawcett, 1990; Nicolson, Fawcett, & Dean, 2001). The role of cerebellum in dyslexia has been described in terms of two mechani sms. One mechanism is related to motor control in speech articulation. Cerebe llar dysfunction causes impared articulation, which leads to deficient phonological processing. The second mechanism is related to reduced processing speed a more global cognitiv e function. Cerebellar deficits negatively affect the automation of overlearned tasks or the performance of familiar tasks such as learning the grapheme phoneme relationships in reading. Dyslexics have shown i mpaire d automatization in various motor tasks, dual

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29 tasks, and non motor cerebellar tasks ( Fawcett, Nicolson, & Dean, 1996 ; Nicolson & Fawcett, 1990; Nicolson et al, 199 9 ). Based on the two roles of cerebellum, Nicolson, Fawcett, and Dean (2001) attempted to explain the double deficit hypothesis. They suggested that abnormal functioning of the cerebellum results in oral motor difficulties which lead to poor phonological awareness and reduced processing speed which leads to deficits in rapid naming In the neuroanatomical studies, Finch, Nicolson, and Fa wcett (2002) found a significantly larger mean cell area in the medial posterior cerebellar Rae and collaborators (2002) also observed significant cerebellar asymmetry (right grey matter > left g rey matter) in controls, which was absent among dyslexic subjects. These authors contend that the degree of cerebellar symmetry is correlated with the severity of the phonological decoding deficit. Eckert and colleagues (2003 ) found that dyslexics have sig nificantly smaller right anter ior cerebellar lobes, pars triangularis bilaterally an d brain volumes. Specially, measures of the right anterior lobe of the cerebellum and the left and right pars triangularis classified 72% of children with dyslexia and 94% of them had rapid automatic naming deficit. These authors suggest the cerebellar measures are highly associated with defic its in rapid automatic naming. Other brain imaging studies have provided evidence of anatomical, metabolic, and activation difference s between dyslexic and normal readers (Brown et al., 2001; Leonard et al., 2001; Nicolson et al., 1999; Rae et al., 1998). Magnocellular Deficit Theory The magnocellular theory is a unifying theory that explains many functional deficits found in dyslexics such as visual, auditory, motor, and tactile processing deficits. The magnocellular pathways that start in the retina continue to the parietal, temporal, and

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30 occipital lobes, projecting to both subcortical and cortical brain areas. The cerebellum also rece ives inputs from various magnocellular systems. Thus magnocellular dysfunction is not restricted to the visual pathways but includes all modalities (Stein & Walsh, 1997). The magnocellular system is important for processing rapidly changing information. E vidence of magnocellular abnormalities in dyslexia have been found in some post mortem studies. Galaburda and collaborators (1985) observed that magnocells in dyslexic brains were disordered and they were over 20% smaller than cells in normal brains. Livin gstone and colleague s (1991) found that cells in the magnocellular layers of the lateral geniculate nucleus (LGN) in dyslexic subjects were smaller th an cells in normal brains and suggested that development of the visual magnocellular system is impaired in dyslexic readers. Jenner, Rosen, and Galaburda (1999) also obtained similar results. They found that the magnocellular layers of the LGN in dyslexics are anatomically less organized (more varied) and contain magnocells that are about 27% smaller than in n ormal brains. Researchers have consistently supported that the disruption of magnocellular pathway can cause a range of problems that have been associated with dyslexia, such as unsteady binocular fixation, poor visual localization, reduced contrast sensit ivity at low spatial frequencies, co occurrence of visual and auditory problems, poor performance in the tactile tasks, and visual motion sensitivity as well as reading impairment (Cestnick, 2001 ; Demb, Boynton Best, & Heeger, 1998; Galaburda, Menard, & Rosen, 1994; Grant, Zangaladze, Thiagarajah, & Sathian 1999; Livingstone, Drislane, Rosen, & Galaburda, 1991; Stein & Walsh, 1997; Stein, 2001; Stoodley, Talcott, Carter, Witton, & Stein, 2000; v an Ingelghem et al., 2001; Witton et al., 1998)

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31 Rationale a nd Significance of the Study There is a lack of research investigating developmental dyslexia in adult populations. Empirical investigations supporting slow processing speed as a clinically significant risk factor in reading disabilities have been primaril y based on performance on tasks of rapid automatized naming. S everal studies of young adults with known histories of childhood dyslexia have shown that reading fluency deficits persist into adulthood (Bruck, 1990, 1992, 1993; Bruck & Waters, 199 0). Furthermore, t hese studies suggest that young adults with dyslexia often rely on spelling sound information (a strategy of reading words aloud), syllabic information, and context for word recognition. Slow reading has been recognized as the most salien t reading problem in dyslexic adults. Many adults who received a clinical diagnosis of dyslexia during childhood show improved reading accuracy with age, but persistently depressed reading fluency in spite of extensive educational and reading experience s ( Torgesen, Ras hotte, & Alexander, 2001). This finding support s that impaired reading fluency is a life long hallmark of dyslex ia (Shay witz, Morris, & Shaywitz, 2008) and underscores the importance of processing speed in the reading performance of dyslexic a dults. Previous studies have consistently suggested that poor reading fluency remains a core symptom of reading impairment. Torgesen (1999) indicated that in the children beyond the second grade, the information gained from the phonological awareness asses sment may not be useful to explain predictive relationships with their reading. Hogan, Catts, and Little (2005) found that from kindergarten to second grade, phonological awareness predicted 23% unique variance in later word reading; from first to third, 8 %; and from second to fourth, only 4%. They confirmed that the predictive power of phonological awareness

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32 disappears as second grade. On the other hand, many investigators have agreed that poor RAN performance of children with dyslexia is evident as early as kindergarten and continues to characterize adults diagnosed with dyslexia in childhood (Adams 1990; Felton, Naylor, & Wood 1990; Flowers 1993; Korhonen, 1995; Shankweiler & Liberman, 1989; Stanovich, 1988; Wagner & Torgesen 1987). A longitudinal study f ound that eighth grade single word reading was strongly predicted from third grade rapid naming within poor readers (Meyer, Wood, Hart, & Felton, 1998 a ). These studies show that the role of processing speed in the reading development of individuals with dy slexia becomes increasingly important with age. However, except for the naming speed studies, a small number of studies have focused on possible depth and breadth of processing speed deficits in adults with dyslexia and provided evidence indicating that sl ow processing speed is not limited to the reading performance. More importantly, very few studies have examined processing speed performance in dyslexics across linguistic and nonlinguistic stimuli. It is important to understand the nature of processing sp eed defici ts in dyslexic students for clinical diagnosis and intervention. Recently, Bonifacci and Snowling (2008) measured linguistic and nonlinguistic processing speed in both English speaking and Italian speaking children with dyslexia. Four types of pr ocessing speed tasks were administrated: simple reaction time, choice reaction time, number scanning (linguistic processing speed task), and symbol scanning (nonlinguistic processing speed task). Results showed that the group differences between dyslexic c hildren and controls were not statistically significant, but there was a trend for children with dyslexia to be slower than controls in all tasks except choice reaction time. They failed to find a significant difference between dyslexic and

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33 age matched chi ldren on both linguistic and nonlinguistic processing speed measures. However, their findings may have some methodological limitations. In both number and symbol scanning tests, children were instructed to look at a number (between 1 to 9) or symbol (Gurmu khi alphab et) that came first on a computer and after a blank screen whether the target was in the sequence that followed. These processing speed tasks required the recruitment of short term memory due to a time lapse between the presentation of a target stimulus and the presentation of a sequence of stimuli with or without the target. The length of the stimulus sequence was not the same for the two tests. The number scanning tes t had seven numbers, whereas the symbol scanning test had only five symbols due to the complexity of the symbols. Additionally, processing speed was measured by verbal and motor responses. The number and symbol scanning tasks required verbal responses whil e the simple and choice reaction time tasks required motor responses. However, it is impossible to compare differences between the two response modalities due to different levels of complexity. In another study, Meyler and Breznitz (2005) compared the per formance of dyslexic and normally reading adults on tasks of visual, auditory, and cross modal (visual + auditory) temporal processing for li nguistic and nonlinguistic stimuli This study was designed to address whether dyslexic readers are impaired in the temporal pattern processing. College students with and without dyslexia were required to distinguish whether two series of temporal patterns were the same or not. Six types of experiments were conducted to examine linguistic or nonlinguistic auditory, vis ual and cross modal temporal pattern processing (linguistic temporal processing: spoken, printed and

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34 spoken/printed nonsense syllables, respectively; nonlinguistic temporal processing: beep, flash, and beep/flash sequences, respectively). They found that d yslexic adults responded more slowly to temporal processing tasks across all tasks supporting the hypothesis that dyslexic readers are characterized by a generalized difficulty in rapidly processing sequential information. Additionally, in the Symbol Sear ch and Digit Symbol tasks (WAIS III; Wechsler, 1997), dyslexic readers showed significantly slower nonlinguistic processing speed when compared with control readers. However, this study may also have a limitation making it difficult to conclude that dyslex ic readers have domain general processing speed deficits. Their statistic analyses on the 12 tempora l pattern tasks (the 6 e xperimental tasks had 2 types of temporal pattern s respectively : same or different temporal patterns) indicated that the differences between two groups were significant on the 4 tasks (3 nonlinguistic tasks and 1 linguistic tasks) than normal readers, even though they were slower in all tasks. A considerable number of tasks failed to reveal statistically significant differences between the two groups. Breznitz (2002) also provided similar evidences that dyslexic children were significantly slower on most of the linguistic and nonlinguistic auditory or visual stimulus tasks, but not on all tasks (no significant differences between the tw o groups on the simple visual and motor reaction time tasks). In order to further investigate whether the processing speed deficits in dyslexia are part of a general cognitive deficit or occur only when processing linguistic information, the current study was designed to compare the performance of dyslexic readers and age matched normal readers on both linguistic and nonlinguistic processing speed tasks. Four experimental processing speed tasks, programmed in the MediaLab and

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35 DirectRT software (Jarvis, 2004 ), were composed of two types of stimuli (linguistic and nonlinguistic) and two types of responses (verbal and motor). English letters as linguistic stimuli and Korean letters as nonlinguistic stimuli were manipulated in the three levels of complexity. Mod ality of the responses to the stimuli was also varied, contrasting verbal and motor responses to the same stimuli. Participants were required to speak a number or press a button as quickly as possible without making a mistake to answer which of the five te st stimuli matches the target stimulus. Target and test stimuli were presented simultaneously without a time lapse to yield a purer measure of processing speed by minimizing the memory component. All processing speed tasks were identically formatted in the stimulus presentation and r esponse time for matching the target stimulus with a set of test stimuli was measured in units of milliseconds To measure linguistic and nonlinguistic processing speed together within the same subject groups, participants in ea ch group were required to complete all processing speed tasks. These experimental efforts to make the task formatting rules and group membership identically and to obtain a purer measure of processing speed would improve the methodological quality of exper imental studies exploring the mechanisms of processing speed deficits in developmental dyslexia. the importance of testing processing speed in diagnosing reading disabilities of young adults. Many college students with dyslexia showed relatively good performances on reading tasks when they were not under time pressure. Their decoding skills were less impaired in spite of their slow and effortful reading. However, their reading pro blems were highly salient in timed testing conditions. Meaningful findings from this study would

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36 support the importance of testing processing speed in a diagnosis of dyslexia, as the good discriminator of college students with and without reading disabilit ies. M ore importantly this study would define the nature of processing speed deficits and underscore the importance of exploring the efficacy of processing speed interventions. Study Objectives Objective 1 To identify significant differences in the perfo rmance of linguistic and nonlinguistic processing speed measures between young adults with developmental dyslexia and age matched normal readers Objective 2 To investigate whether the processing speed deficits in dyslexic readers are restricted to speed o f processing linguistic stimuli only or whether processing speed deficits are found for both linguistic and nonlinguistic stimuli Objective 3 To determine whether dyslexic readers have deficits in processing speed across speech and non speech modalities. Objective 4 To examine the effect of stimulus complexity on the speed of processing linguistic and nonlinguistic stimuli Objective 5 To identify significant differences in performance on the standardized tests of processing speed between the two groups Objective 6 To investigate within group interrelationships on three standardized tests and four experimental tests of processing speed

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37 CHAPTER 3 METHODS AND MATERIAL S Setting and Participants Recruitment Setting Two groups of college students aged 18 to 30 years of age were recruited with the approval of the University of Florida Behavioral/NonMedical Institutional Review Board (UFIRB #2010 U 0054): (1) dyslexic group: students who had been diagnosed previously with a specific reading disability or who r eported lifelong difficulties with reading, writing, or spelling but had not been formally diagnosed with reading disability; and (2) normal reading group: students who had no history of neurological or sensory deficits, or speech, language, reading, or ge neral academic problems. Participants were required to be monolingual, native English speakers who had not been exposed to Korean letters. Recruitment flyers were posted on bulletin boards in the campuses of the University of Florida, Santa Fe Community Co llege, and City College, UF Speech and Hearing Clinic, UF/SFCC offices of services for students with disabilities, and learning disabilities research centers located in Gainesville, Florida (Appendix A). Participants were also recruited through the UF LIN CSD Research Participant Pool website. The flyers included brief descriptions of the study, benefits from participation, and contact information for potential participants. All participants were compensated in the form of 2 hours of research credit for app licable courses. Additionally participants with reading disability were provided with a three page brief report of their test findings when they chose to be informed of their standardized test scores for documentation of their learning disability. They al so met individually with an academic supervisor who

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38 specializes in the diagnosis of dyslexia to discuss test results and educational recommendations. Data were collected from April, 2010 through January, 2011. Participants A total of eighty five college st udents participated in the present study: 31 students with developmental dyslexia and 54 students with normal reading skills. Written informed consent was obtained from all participants prior to the onset of the research activity (Appendix B). All particip ants completed a questionnaire that asks (a) history of speech and/or language impairments, (b) school history of reading, spelling, and/or writing problems, (c) previous diagnosis of learning disabilities, (d) duration and frequency of reading interventio n, (e) family history of dyslexia or reading difficulties, (f) self ratings of current reading abilities, and (g) general state of health (Appendix C). To confirm the diagnosis of dyslexia and clarify the classification of two groups, 2 hour reading tests were conducted for all participants. All tests were administered by the author and trained research assistants. The research assistants were senior undergraduate students in speech language pathology. The developmental and educational information collected from the questionnaire and the performances on the battery of standardized reading tests were evaluated by the specialist in dyslexia diagnoses. Participants were diagnosed with developmental dyslexia if they (1) showed deficits on the standardized tests of phonological and/or orthographic processing that include phonological awareness, rapid naming, word decoding, word reading, spelling, and/or reading fluency unexpected for their other cognitive abilities, educational levels, and socio cultural opportuni ties; (2) reported having persistent difficulties and/or remarkable lack of progress in reading, spelling, and/or writing along with a positive family history for reading disabilities; (3) obtained relatively high scores on standardized

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39 test of reading com prehension despite poor word decoding, word recognition, and/or spelling scores; and (4) had no developmental history of diagnosis and therapy of spoken language impairment. Data from 71 of the original 85 participants was used in the final analysis: 29 st udents with developmental dyslexia and 42 students with normal reading skills. The two groups did not differ significantly on chronological age ( t (69) = .15, p = .89) and years of education ( t (69) = 1.01, p = .32). Significant differences between the two g roups were found on all standardized reading and reading related tests, except on an extended time reading comprehension measure and on verbal short term memory test. S tatistical analyses about these result s are described in detail in Chapter 4. Participan ts with Developmental Dyslexia (DD) Among thirty one participants with developmental dyslexia, two students were excluded from the study: One did not meet the age requirement of 18 to 30 years, and the other was not a college student. A total of twenty nin e college students with developmental dyslexia were includ ed in the final data analysis. Five students reported that they had been diagnosed with developmental dyslexia in elementary school and their persistent reading disabilities were demonstrated again thr ough the 2 hour reading tests. Seven students noted that they had received remedial reading interventions in elemen tary and/or middle school. Twenty students, 69% of dyslexic readers, reported a positive family his tory for reading difficulties. The grou p with dyslexia was 79% female (Male = 6, Female = 23) with the following ethnic representation: Caucasian (N = 22), African American (N = 3), Asian American (N = 2), and Hispanic (N = 2). They ranged in age from 18 to 29 years (M = 21.10, SD = 2.9) and in years of education from 13 to 21

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40 years (M = 15.48, SD = 1.84). Table 3 1 shows mean standard scores on the diagnostic reading tests for students with dyslexia. Participants with Normal Reading Skills (NR) Among fifty four participants who were initially p laced into the normal reading control group, twelve students were excluded from the study for the following reasons: (1) Three students failed to complete all tasks of the study; (2) Two students scored below average on the norm referenced reading comprehe nsion t est (Nelson Denny Reading Test); (3) Three students scored below average on the norm referenced reading fluency t est (Nelson Denny Reading Test); and (4) Four students scored below average on the norm referenced sight word reading test (Test of Word Reading Efficiency). The below average scores were defined as scores below the 16th percentile or less than one standard deviation from the mean on each standardized test. A total of forty two college students with normal reading skills were includ ed in t he final data analysis. Five students, 12% of normal readers, reported a positive family history for reading difficulties The group with normal reading skills was 93% female (Male = 3, Female = 39) with the following ethnic representation: Caucasian (N = 30), Hispanic (N = 8), African American (N = 2), and Asian American (N = 2). They ranged in age from 18 to 30 years (M = 21.11, SD = 2.4) and in years of edu cation from 13 to 21 years (M = 15.83, SD = 1.08). Table 3 2 shows mean standard scores on the diag nostic reading tests for students with normal reading skills. Procedure All testing was performed individually in the reading research laboratory in Dauer Hall at the University of Florida. All participants completed the same reading test battery and exper imental protocols in a fixed order. After the author provided general

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41 information about the study and the test procedures, the participant was asked to sign two copies of informed consent form then completed the questionnaire. One copy of the consent form was given to the participant to keep and the other copy was returned to the author. Research tests started with computer delivered experimental processing speed tasks, which took approximately 20 to 25 minutes. The author recorded each responses of numbers matching with a target stimulus (1, 2, 3, 4, or 5) on a score sheet for each trial. The verbal responses were also digitally audio recorded in order to double check for errors. Standardized processing speed tasks and reading tests wer e administered by the author and trained assistant student in approximately 2 hours. Test Measures Reading Tests to Insure Classification of Dyslexia Cognition t ests Thinking Ability and Verbal Ability from the Woodcock Johnson III Test of Cognitive Abilit ies (WJ III COG: Woodcock, McGrew, & Mather, 2001) were Ability consists of four subtests; Visual Auditory Learning (VAL), Spatial Relations (SR), Sound Blending (SB), and Concept Formation (CF). On the VAL subtest, the participant is required to name words that certain symbols represent in order to read sentences formed by the symbols. It consists of 109 test items and testing is continued until cutoff criteria defined in the Test Record are reached (e.g., cutoff = 9 or more errors among total 12 items). The SR subtest asks the participant to choose which shapes construct a particular whole. It consists of 81 test items and testing is continued until cutoff criteria defined in the Test Record are reached. On the SB subtest, the participant is required to

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42 say a whole word when given the individual sounds of that word. It consists of 33 questions and testing is continued until the six highest numbered questions administered ar e incorrect. The CF subtest asks the participant to form rules and concepts based on visually presented stimuli. It consists of 40 questions and testing is continued until cutoff criteria defined in the Test Record are reached. The Verbal Ability is derive d from Verbal Comprehension subtest that is actually made up of four different tasks: Picture Vocabulary, Synonyms, Antonyms, and Verbal Analogies. The Picture Vocabulary task requires the participant to name pictured objects. The Synonyms and Antonyms tas ks ask the participant to state words having the same meaning (Synonyms) and words having the opposite meaning (Antonyms) when orally presented with a stimulus word. The Verbal Analogies task requires the participant to state a fourth word to complete a th ree word analogy. These four tasks consist of 23, 15, 18, and 15 questions, respectively, and each testing is continued until the three highest numbered questions administered are incorrect (Verbal Comprehension subtest: total 71 questions). Raw scores wer e recorded as the total number of items answered correctly in each subtest and WJ III Compuscore and Profiles Program was used for score reports of Thinking Ability and Verbal ability. The mean standard score for each subtest and composite is 100 with a st Reading performance t ests Phonological a wareness Elision subtest from the Comprehensive Test of Phonological Processing (CTOPP; Wagner, Torgesen, & Rashotte, 1999) and Sound Blending subtest from the Woodcock Johnson III Test of Cognitive Abilities (WJ III phonological awareness. The Elision subtest requires the participant to listen to and

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43 repeat a word, and then say the word without a specific soun d that is removed from either initial, medial, or final position of the word (e.g., say cup. now say cup without saying /k/). There are 20 questions in all, with testing stopped following three consecutive errors. Raw score was recorded as the total number of questions answered correctly. The mean standard score for Elision subtest is 10 with a standard deviation of phonemes from a recorded tape of a male voice and say the combined whole word (e.g., /fi / + /g r/). It consists of 33 questions and testing is stopped when the six highest numbered questions administered are incorrect. Raw score was recorded as the total number of questions answered correctly. The mean stand ard score for Sound Naming s peed Rapid Automatized Naming and Rapid Alternating Stimulus Tests ability. The RAN/RA S tests are composed of four RAN tests (Objects, Colors, Numbers, and Letters), Objects, and Colors) and two RAS tests (2 Set Letters and Numbers and 3 Set Letters, Numbers, and Colors). Each test contains total 50 stimulus items arranged in a 5 by 10 matr ix. The RAN tests consist of 5 different objects (book, chair, dog, hand, and star), colors (black, red, yellow, green, and blue), numbers (2, 6, 9, 4, and 7), and letters (o, a, s, d, and p) that randomly repeated 10 times, respectively. The 2 Set RAS tes t consists of 10 different letters and numbers (e, a, s, d, p, 2, 6, 9, 4, and 7) that randomly repeated 5 times. The 3 Set RAS test consists of 15 different letter, numbers, and colors (a, e, s, d, p, 2, 6, 9, 4, 7, black, red, yellow, green, and blue) th at randomly repeated 3 or 4 times. The participant is asked to name each stimulus item as

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44 quickly as possible without making any mistakes on all tests. Raw scores were recorded as the time in seconds that is required to name all 50 items on each test. The mean Word reading Word reading was measured with timed and untimed single word reading. The Sight Word Efficiency (SWE) and Phonemic Decoding Efficiency (PDE) subtests from the Test o f Word Reading Efficiency (TOWRE; Wagner, Torgesen, & real words fluently at the text free single word level within time limits. On the SWE subtest, the participant is given a list of 104 real words of increasing phonological length and complexity, and then asked to read them aloud as many as he/she could in 45 seconds. On the PDE subtest, the participant is given a list of 63 pronounceable non real words of increasing phonologi cal length and complexity, and then asked to read them aloud as many as he/she could in 45 seconds. Raw scores were recorded as the total number of words correctly read in 45 seconds. The Letter Word Identification (LWI) and Word Attack (WA) subtests from Woodcock Johnson III Tests of Achievement (WJ III ACH; real and non real words fluently at the text free single word level without time limits. The LWI subtest requires th e participant to read aloud real words of varying phonological length and complexity without time limits. It consists of 76 test items and testing is continued until the six highest numbered items administered are incorrect. The WA subtest requires the par ticipant to read aloud pronounceable non real words of varying phonological length and complexity without time limits. It consists of 32 test items and testing is continued until the six highest numbered items administered are incorrect.

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45 Raw scores were re corded as the total number of test items correctly read. The mean Reading fluency The Nelson Denny Reading Test Form G ( NDRT; Brown, Fishco & Hanna, 1993) was used to assess partici reading). The participant is required to read silently the first test passage of comprehension section at his/her normal reading rate (neither faster nor slower than usual) and to mark the point he/she had reached af ter one minute. Raw score was recorded as the number printed at the line of the point he/she has marked. The mean standard score for each test is 5 with a standard devia Reading comprehension The Nelson Denny Reading Test Form G ( NDRT; proficiency under timed and extra time conditions. The participant is required to read se ven short passages and to answer to 38 multiple choice questions about the contents of the passages. To measure reading comprehension under timed condition, the participant is given a time limit of 20 minutes. When they have not completed all questions wit hin the initial time limit, extra 12 minutes are provided. The total number of questions answered correctly within the initial 20 minutes was recorded as a raw score for reading comprehension in timed condition. If extended time was used, the total number of questions answered correctly within 32 minutes was recorded as a raw score for reading comprehension in extra time condition. The participants who completed all questions within the 20 minute time limit had identical raw scores in both timed and extra t ime conditions. The mean standard score for each test is 5 with a standard deviation of +/ 2.

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46 Spelling The Spelling subtest from Woodcock Johnson III Tests of Achievement (WJ III ACH; Woodcock, McGrew, & Mather, 2001) was used to measure the ability to spell single words. The participant is asked to write single words on the test form after li stening to the target word with a sample sentence which stresses the word. It consists of 59 questions and testing is continued until the six highest numbered questions administered are incorrect. Raw score was recorded as the total number of words spelled correctly. The mean standard score for Spelling subtest is 100 with a standard deviation of +/ 15. Short Term and Working Memory Tests Short term memory test Digit Span Forwards (DSF) task of the Wechsler Adult Intelligence Scale IV (WAIS IV; Wechsler, 2008) was used to measure verbal short term memory. In this task the participant has to recall a sequence of numbers in the correct order. The length of the sequence starts with two digits, and become increasingly more difficult (up to a maximum of nine digits) until the participant fails to repeat two trials of equal length. The raw score for DSF is the number of correct trials (maximum score: 16). Spatial Span Forwards (SSF) task of the Wechsler Adult Intelligence Scale Revised as a Neuropsychological Instrument (WAIS R NI; Kaplan, Fein, Morris, & Delis, 1991) was modified to measure visual spatial s hort memory. It uses a spatial span board, upon which 10 blue cubes are mounted randomly. For SSF, the examiner taps the cubes (one cube per second) in a specified sequence that the participant is asked to replicate in the correct order. The length of the sequence starts with two blocks, and become increasingly more difficult (to a maximum sequence of nine blocks) until the participant

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47 fails to repeat two trials of equal length. The raw score for SSF is the number of correct trials (maximum score: 16). Repe ated testing in each trial is not permitted. Working memory test Digit Span Backwards (DSB) task of the Wechsler Adult Intelligence Scale IV (WAIS IV; Wechsler, 2008) was used to measure verbal working memory. The DSB procedure is the same as the DSF task for verbal short term memory measure but this time the participant has to recall a sequence of numbers in reverse order. A sequence of two digits to a maximum of eight digits is used and the number of correct trials is recorded as the raw score of DSB (max imum raw score of 16 correct trials). Spatial Span Backwards (SSB) task of the Wechsler Adult Intelligence Scale Revised as a Neuropsychological Instrument (WAIS R NI; Kaplan, Fein, Morris, & Delis, 1991) was modified to measure visual spatial short memory The participant has to tap the cubes in a specified sequence that he/she is required to repeat like the SSF task, but in reverse order. A sequence of 2 blocks to a maximum sequence of 8 blocks is used and the number of correct trials is recorded as the r aw score of SSB (maximum raw score of 16 correct trials). Repeated testing in each trial is not permitted. Standardized Processing Speed Tests Written and oral symbol digit substitution tests Symbol Digit Modalities Test (SDMT; Smith, 1991) was modified to measure written and oral versions of symbol digit substitution speed. These tests provide a key that pairs nine digits (ranging between 1 and 9) with nine symbols at the top of the page. The rows of randomly ordered symbols (total 100 test items) with emp ty boxes are presented under the key. In the written version, participant is required to fill in the numbers that correspond with symbols into the empty boxes as quickly as possible

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48 without making any mistake. In the oral version, the participant is requir ed to state the numbers that correspond with symbols as quickly as possible without making any mistake. SDMT Form B was used for the written version of symbol digit substitution and SDMT Form D was used for the oral version of symbol digit substitution. Th e written version was first given as recommended in SDMT manual. Tasks started with ten practice trials before test trials were performed. Accuracy and response time (in seconds) required to complete the entire 100 test items in each task were recorded as the raw scores. The written and oral forms of symbol digit substitution tests are shown in Appendix D and E. Symbol copy test Digit Symbol Copy (Tun, Wingfield, & Lindfield, 1997) was modified to measure symbol copy speed. Participant is asked to fill in 1 00 empty boxes by copying symbols located above each box as quickly as possible without making any mistake. The task started with ten practice trials before test trials were performed. Accuracy and response time (in seconds) required to complete the entire 100 test boxes were recorded as the raw scores. The form of symbol copy test is shown in Appendix F. Experimental Processing Speed Tests Four types of experimental p rocessing speed tests were produced using MediaLab and DirectRT software (Jarvis, 2004). T hese four processing speed tasks were composed of different conditions of stimulus response pairs, using two types of stimuli (linguistic and nonlinguistic) and two types of responses (verbal and motor): Linguistic Stimulus Verbal Response Test, Linguistic Stimulus Motor Response Test, Nonlinguistic Stimulus Verbal Response Test, and Nonlinguistic Stimulus Motor Response. English letters were used as linguistic stimuli and Korean letters were

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49 chosen to represent nonlinguistic stimuli. Because all participan ts were monolingual native English speakers who were never exposed to Korean orthography, Korean letters were used as nonlinguistic symbols. When English or Korean letters were presented on a computer screen, the participant was required to speak a number or press a button as quickly as possible without making a mistake to answer which of the five test stimuli matches the target stimulus. A headset with an attached microphone and 5 button device were used for verbal and motor response tasks, respectively. T arget and test stimuli were presented simultaneously without a time lapse to yield a purer measure of processing speed by minimizing the memory component from the test requirement. Target stimulus was placed at the top and five test stimuli (one target and four distracters) were placed at the bottom. Each task contained total 48 trials which were grouped into the three levels of stimulus complexity (6 trials in each level). The three levels of matching trials were presented in a random order. The frequency of target letters and the position of answers were balanced across all trials. Figure 3 1 illustrates the stimulus presentation of four types of experimental processing speed tasks on a computer screen and Table 3 3 shows the examples for each task. Respon se time for matching the target stimulus with a set of test stimuli was measured in units of milliseconds. All tasks started with three practice trials before test trials were performed, to help the participants to become accustomed to tasks. Measures of a ccuracy and response time were recorded for each task and analyses were conducted on correct recorded to double check for errors. Appendix G provides stimulus lists used in t he four types of experimental processing speed tests.

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50 Linguistic stimulus verbal response test The participant were given a target English letter and a string of English letters simultaneously and required to speak quickly a number corresponding to the l etter that is identical to the target from the string of letters. The letter stimuli were manipulated on letter length (three stimulus complexity levels: single digit letter, double digit letters, and triple digit letters). To avoid constructing a real/pse udo word, only consonants were used at the level of double and triple letter cluster combinations. For a measure of the processing of linguistic information, letters that are visually dissimilar across case (e.g., a/A, b/B, d/D, e/E, g/G, h/H, l/L, m/M, n/ N, q/Q, r/R) were selected and the sequence of letters were always presented in opposite case to the target (e.g., target letter: G; the sequence of letters: b, d, m, g, q) in Arial Unicode MS letter fond. The target letter cases (lower, upper, and mixed) were balanced across the trials. Response time and accuracy were recorded for each trial. Linguistic stimulus motor response test The participants were given a target English letter and a string of English letters simultaneously and required to press a b utton corresponding to the letter that is identical to the target from the string of letters. The participants were directed to put their four fingers (the index, middle, ring and little fingers) from one hand (their dominant hand) on the second to fifth b uttons and asked to press one of the five buttons. The index finger was used to press the first and second buttons. Stimulus properties are manipulated in the same way as the linguistic stimulus verbal response task. Response time and accuracy were recorde d for each trial.

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51 Nonlinguistic stimulus verbal response test The participants were given a target Korean letter and a string of Korean letters simultaneously and required to speak quickly a number corresponding to the symbol that is identical to the tar get from the string of Korean letters. Korean letters which resemble geometric shapes are excluded from stimuli and the letter stimuli are manipulated on letter length (single digit letter, double digit letters, and triple digit letters) and both of Korean consonants and vowels are used for letter combinations. Response time and accuracy were recorded for each trial. Nonlinguistic stimulus motor response test The participants were given a target Korean letter and a string of Korean letters simultaneously and required to press a button corresponding to the symbol that is identical to the target from the string of Korean letters. The participants were directed to use their four fingers to press the button in the same way as the linguistic stimulus motor resp onse task. Stimulus properties are manipulated in the same way as the nonlinguistic stimulus verbal response task. Response time and accuracy were recorded for each trial. Research Questions and Hypotheses This study aimed to identify significant differenc es in the performance of linguistic and nonlinguistic processing speed measures between young adults with and without developmental dyslexia and to investigate whether processing speed deficits in dyslexic readers are restricted to speed of linguistic info rmation processing only or speed across linguistic and nonlinguistic information processing. Specifically, the purpose of the present study i s to explore the following two main research questions.

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52 Research Question 1 Are there any significant differences i n the speed of processing linguistic and nonlinguistic stimuli between young adults with developmental dyslexia and age matched normal readers? Sub question 1 Are the differences between the two groups significant on only linguistic processing speed tasks or on both linguistic and nonlinguistic processing speed tasks? Hypothesis It was hypothesized that dyslexic readers would significantly slower than normal readers on both linguistic and nonlinguist ic processing speed tasks as an outcome of domain genera l processing speed mechanism. Sub question 2 Are there any significant effects of response modality on the speed of processing linguistic and nonlinguistic stimuli between the two groups? Hypothesis It was hypothesized that dyslexic readers would respond significantly more slowly than normal readers across verbal and motor modalities. Sub question 3 Are there any significant effects of stimulus complexity on the speed of processing linguistic and nonlinguistic stimuli between the two groups? Hypothesis It was hypothesized that dyslexic readers would be increasingly slower with more complex stimuli relative to normal readers. Research Question 2 Are there any significant differences in performance on the standardized tests of processing speed (modified in the number of test items) between young adults with developmental dyslexia and age matched normal readers? Sub question 1 Are the differences between the two groups significant on three standardized tests of processing speed? Hypothesis It was hypothesi zed that dyslexic readers would perform more slowly on all standardized processing speed tests and the difference of scores between the two groups would be significantly different. Sub question 2 What interrelationships exist between the performances on t hree standardized tests and four experimental tests of processing speed in each group ?

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53 Hypothesis It was hypothesized that there would be significant associations among all variables measuring processing speed in each group Data Analyses All data for dem ographic characteristics, diagnostic reading assessments, and research questions were recorded and analyzed using SPSS version 15.0 for Windows. Raw scores were used in statistical analys es for research questions. Four statistical analyses were performed f or group comparisons: (1) A one way multivariate analysis of variance (MANOVA) and subsequent univari ate analyses of variance (ANOVAs ) using exist in performance on the s tandardized tests of reading, reading related abilities, and processing speed (response times and accuracy) between the two groups; (2 ) A mixed four factor analysis of variance (ANOVA) and post hoc Bonferroni corrected pairwise comparisons using paired sam ples t tests were conducted to examine whether any significant differences exist in the response times of linguistic and nonlinguistic processing speed tasks between young adults with developmental dyslexia an d age matched normal readers; (3 ) A mixed three fact or analysis of variance (ANOVA) was conducted to examine whether any significant differences exist in the accuracy of linguistic and nonlinguistic processing speed tasks and in the short term and working memory perf ormances between the two groups; and (4 ) A correlation analysis using the Pearson's correlation coefficients was conducted to determine whether any significant relationships exist among all processing speed variables in each group. The performances of two groups on all processing speed tasks were presented in bar charts and line graphs.

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54 Table 3 1. Mean standard scores on the diagnostic reading tests for students with dyslexia Diagnostic Reading Tests (standard score) Mean SD Min Max WJ III COG Verbal Comprehension (100) 97.69 6.99 87 112 Visual Auditory Learning (100) 99.83 18.32 61 135 Spatial Relations (100) 101.62 9.72 85 126 Sound Blending (100) 108.59 17.29 85 139 Concept Formation (100) 103.31 8.71 87 122 Verbal Ability Composite (100) 97.69 6.99 87 112 Thinking Ability C omposite (100) 105.55 11.34 85 130 WJ III ACH Letter Word Identification (100) 96.21 7.84 85 118 Word Attack (100) 90.62 9.84 69 119 Spelling (100) 96.07 7.71 74 112 Basic Reading Skills Composite (100) 93.97 7.80 79 112 CTOPP Elision (10) 9.24 2.3 6 3 12 TOWRE Sight Word Efficiency (100) 87.66 9.43 72 114 Phonemic Decoding Efficiency (100) 83.66 6.08 70 98 Total Word Reading Efficiency (100) 82.83 8.29 69 104 RAN/RAS RAN Objects (100) 103.00 11.82 77 120 RAN Colors (100) 98.17 11.82 65 121 RAN Numbers (100) 105.59 5.44 92 115 RAN Letters (100) 102.59 6.46 80 111 RAS 2 Set Letters & Numbers (100) 105.38 8.02 83 119 RAS 3 Set Letters, Numbers, & Colors (100) 102.17 9.64 84 119 NDRT Reading Rate (5) 3.21 1.52 1 7 Timed Reading Compreh ension (5) 4.86 1.51 2 8 Extra Timed Reading Comprehension (5) 5.28 1.31 3 8 Note. (1) WJ III COG: Woodcock Johnson III Test of Cognitive Abilities, (2) WJ III ACH: Woodcock Johnson III Tests of Achievement, (3) CTOPP: Comprehensive Test of Phonological Processing, (4) TOWRE: Test of Word Reading Efficiency, (5) RAN/RAS: Rapid Automatized Naming and Rapid Alternating Stimulus Tests, (6) NDRT: Nelson Denny Reading Test, Students who completed all questions within initial time limit had identical standard scores in both timed and extra time conditions SD: standard deviation, Min: minimum, Max: maximum

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55 Table 3 2. Mean standard scores on the diagnostic reading tests for students with normal reading skills Diagnostic Reading Tests (standard score) Mean SD M in Max WJ III COG Verbal Comprehension (100) 103.95 8.72 92 124 Visual Auditory Learning (100) 110.10 17.03 72 136 Spatial Relations (100) 106.14 8.39 84 126 Sound Blending (100) 116.50 7.69 101 130 Concept Formation (100) 107.02 9.45 92 126 Ve rbal Ability Composite (100) 103.95 8.72 92 124 Thinking Ability Composite (100) 114.07 8.54 92 129 WJ III ACH Letter Word Identification (100) 104.93 6.86 94 119 Word Attack (100) 103.33 8.55 88 117 Spelling (100) 107.02 7.03 92 123 Basic Reading Skills Composite (100) 104.62 6.87 94 120 CTOPP Elision (10) 10.90 .93 7 12 TOWRE Sight Word Efficiency (100) 105.64 9.31 86 114 Phonemic Decoding Efficiency (100) 105.55 9.80 89 121 Total Word Reading Efficiency (100) 106.74 9.73 87 121 RAN/RAS RA N Objects (100) 119.29 12.01 87 145 RAN Colors (100) 114.50 9.82 97 142 RAN Numbers (100) 111.98 4.78 105 126 RAN Letters (100) 110.38 4.63 102 125 RAS 2 Set Letters & Numbers (100) 113.43 6.46 104 135 RAS 3 Set Letters, Numbers, & Colors (100) 1 14.71 8.49 99 141 NDRT Reading Rate (5) 5.12 1.40 3 9 Timed Reading Comprehension (5) 6.36 1.65 3 9 Extra Timed Reading Comprehension (5) 6.36 1.64 4 9 Note. (1) WJ III COG: Woodcock Johnson III Test of Cognitive Abilities, (2) WJ III ACH: Woodcock Johnson III Tests of Achievement, (3) CTOPP: Comprehensive Test of Phonological Processing, (4) TOWRE: Test of Word Reading Efficiency, (5) RAN/RAS: Rapid Automatized Naming and Rapid Alternating Stimulus Tests, (6) NDRT: Nelson Denny Reading Test, Student s who completed all questions within initial time limit had identical standard scores in both timed and extra time conditions, SD: standard deviation, Min: minimum, Max: maximum

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56 Figure 3 1. The illustration of four types of linguistic and nonlinguistic stimulus response tasks on a computer screen A gN d r g a q Gn Gm Hn Nh Hg 1 2 3 4 5 Linguistic Stimulus Verbal Response Test Linguistic Stimulus Motor Response Test 1 2 3 4 5 Nonlinguistic Stimulus Verbal Response Test Nonlinguistic Stimulus Motor Response Test

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57 Table 3 3. Examples of four types of linguistic and nonlinguistic processing speed tasks Tasks Target Stimulus Choice Stimuli Response Linguistic Stimulus Verbal Response A d r g a q 1 2 3 4 5 Qg qB bR rB gR qG 1 2 3 4 5 mQG Gdq Mqg Mgq Gqd Dqm 1 2 3 4 5 Linguistic Stimulus Motor Response d R B D Q N Press third button gN Gn Gm Hn Nh Hg Press first button Hmb bHM hMD hDM dHM hMB Press fifth button Nonlinguistic Stimulus Verbal Response 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 Nonlinguistic Stimulus Motor Response Press fourth button Press first button Press fifth button

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58 CHAPTER 4 RESULTS Introduction This chapter is organized into three sections. The first section provides the results of group comparisons on standardized reading and reading related tests. The second section evaluates the differences between the two group s on linguistic a nd nonlinguistic processing speed tests in response to the first major research question. Th e final section investigates the differences between the two groups on standardized processing speed tests and interrelationships among all processing speed variabl es in response to the second major research question. The implications of these findings are discussed in Chapter 5. Comparison of R eading and Reading Related Performance This study examine d whether there are significant differences between college student s with developmental dyslexia (DD) and age matched normal readers (NR) on the reading and reading related test s. Table 4 1 provide s descriptive statistics for the two groups on the tests of cognition, phonological awareness, rapid naming, reading, and spel ling Statistical comparisons of two groups were organized to ans wer the following five sub questions. Sub question 1 Are there any significant differences between the two groups in phonological awareness performances? Sub question 2 Are there any signif icant differences between the two groups in rapid automatized naming (RAN) performances? Sub question 3 Are there any significant differences on the basic reading measures, including word reading, reading fluency, and spelling between the two groups? Sub question 4 Are there any significant differences on the reading comprehension measures between the two groups?

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59 Sub question 5 Are there any significant differences in performance on the short term and working memory tasks between the two groups? A one wa y multivariate analysis of variance (MANOVA) and follow up univari ate analyses of variance (ANOVAs error rates across the multiple comparisons, were conducted to examine group differences on the phonol ogical awareness, rapid naming, word reading, reading fluency, spelling, and comprehension measures. A mixed three factor analysis of variance (ANOVA) was conducted to test whether there are significant differences in memory performance. Raw scores were us ed for all statistical analyses. Sub Question 1 : Group Comparison of Phonological Awareness A one way multivariate analysis of variance (MANOVA) and subsequent univari ate analyses of variance (ANOVAs ) were conducted to determine whether significant differ ences exist in the phonological awareness performances (elision and sound blending) between college students with and without developmental dyslexia. Using number of cor rect responses in each task (elision: max 20; sound blending: max 33) was used for the data analysis. Three assumptions for the MANOVA were checked prior to the analysis: (1) multivariate normal distribution in each group, (2) homogeneity of covariance mat rices, and (3) homogeneity of error variances. The violation of these assumptions can inflate the Type I error rate and diminish the statistical power, especially when the sample sizes are not equal (Olson, 1974; Hakstian, Roed, & Lind, 1979). S kewness val ues in each group fell within the acceptable range of 2 to 0 for two dependent variables (2 tasks) while kurtosis values in each group ranged between 2 to +7 (elision: DD = +4.9, NR = +6.6; sound blending: DD = 1.4, NR = .04). These

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60 results showed that the multivariate normality assumption was violated, especially in the e lision task for both two groups p M = 103.69, p < .001) This suggested that the assumption of homogeneity of covariance matrice s was violated: Observed covariance matrices of the dependent variables were not equal across the groups. p = .05 level for both two dependent variables ( p values less than .001 ) This suggested that the assumption of homogeneity of error variance was violated: The error variance of the dependent variables was not equal across the groups. Because of these criterion is considered to be the most robust in situations of unequal sample size and/or heterogeneity of variances or covariances (Olson, 1979). The MANOVA found significant group differences between the means, F (2, 68) = 9.28, p < .001, partial 2 = .214, and observed power = .9 73. Univariate ANOVAs using Bonferroni corrections on each phonological awareness task were conducted as follow up tests to determine which specific tasks account for the significant group differences. The critical significant level for each comparison is .05/2 = .025. A significant difference between the two groups was found on both two tests (elision: F (1,69) = 13.99, p < .001; sound blending: F (1,69) = 13.58, p < .001). Effect sizes reported as partial eta squared ( p 2 ) showed that two comparisons have t he values of 0.16 or higher (elision: p 2 = .169; sound blending : p 2 = .164). Cohen (1988) characterized the values of partial eta squared of .01 as small, .06 as moderate, and .14 as a large effect size. Therefore, t hey represented large effect sizes for the difference in estimated marginal means between the two groups. These results demonstrate that college students with dyslexia have

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61 significantly poorer phonological awareness than peer ma tched normal readers. Table 4 2 shows a summary of two univariate ANOVAs on the phonological awareness tasks. Sub Question 2 : Group Comparison of Rapid Automatized Naming A one way multivariate analysis of variance (MANOVA) followed by univari ate analyses of variance (ANOVAs ) was conducted to examine whether there are s ignificant differences between college students with and without developmental dyslexia o n the six types of rapid automatized naming (RAN) performances: RAN objects, RAN colors, RAN numbers, RAN letters, RAN 2 set letters & numbers, and RAN 3 set letters, ANOVA was tested at a significance level of .008 (.05/6). Raw response times required to name all 50 stimulus items in each task, measured in seconds, were used for the data analysis. Three assumptions for the MANOVA were examined: (1) In the multivariate normality test, skewness values in each group fell within the acceptable range of 1 to +2 for all six dependent variables while not all kurtosis values in each group fell with in the accepta ble range of 1 to +2 (NR group: RAN objects = +2.42; DD group: RAN colors = +2.65, RAN letters = +4.23). These results showed that the multivariate no rmality assumption was violated; (2) p = 62.26, p < .001) indicating that the assumption of homogeneity of c ovariance matrices was violated; and p = .05 level for five dependent variables ( p values within the range of .020 to .029). A non significant Levene's test was found only in the RAN colors task ( p = .095). This suggested that the assumption of homogeneity of error variance was violated. Because

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62 The MANOVA found significa nt group differences between the means, F (6, 64) = 7.81, p < .001, partial 2 = .423, and observed power = 1.000. Univariate ANOVAs at the Bonferroni correction level of .008 on each RAN task were conducted as follow up tests to determine which specific ta sks account for the significant group differences. A significant difference between the two groups was found on all RAN tasks. Estimated marginal mean differences (DD minus NR) and F values on each measure were as follows: (1) RAN objects: 5.21, F (1,69) = 30.33 p < .001; (2) RAN colors: 7.02 F (1,69) = 40.02, p < .001; (3) RAN numbers: 4.68 F (1,69) = 33.33, p < .001; (4) RAN letters: 5.06 F (1,69) = 34.57, p < .001; (5) RAN 2 set letters & numbers: 4.92 F (1,69) = 26.92, p < .001; and (6) RAN 3 set letter s, numbers, & colors: 5.67, F (1,69) = 34.57, p < .001. The greatest difference between the two groups occurred in the RAN colors task and the least difference was found in the RAN numbers task. Effect sizes reported as partial eta squared ( p 2 ) indicated t hat two comparisons have the values of 0.28 or higher ( RAN objects : p 2 = .305 ; RAN colors: p 2 = .367; RAN numbers: p 2 = .326 ; RAN letters: p 2 = .334 ; RAN 2 set letters & numbers: p 2 = .281 ; RAN 3 set letters, numbers, & colors: p 2 = .334 ). They repre sented that all of the six comparisons had very large effect sizes for the difference in estimated marginal means between the two groups. These findings suggest that rapid automatic naming abilities were significantly more depressed in college students wit h dyslexia regardless of the type of stimulus named, when compared with age matched normal readers. A summary of six univariate ANOVAs on the rapid automatized naming tasks is provided in Table 4 3

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63 Sub Question 3 : Group Comparison of Basic Reading Measure s A one way multivariate analysis of variance (MANOVA) and follow up univari ate analyses of variance (ANOVAs ) were conducted to examine whether there are significant differences between college students with and without developmental dyslexia in the six ba sic reading measures: timed sight word reading (T SWR), timed nonsense word reading (T NWR), untimed sight word reading (UT SWR), untimed nonsense word reading (UT NWR), reading fluency (RF), and spelling. Using VA was tested at a significance level of .008 (.05/6). The total number of correct responses in each task was used for the data analysis (T SWR: max 104; T NWR: max 63; UT SWR: max 76; UT NWR: max 32; RF: max 601; spelling: max 59). Three assumptions for t he MANOVA were examined: (1) In the multivariate normality test, skewness values in each group fell within the acceptable range of 2 to +2 for all six dependent variables. Kurtosis values in each group were within the acceptable range of 1 to +2 for all six dependent variables, except one task in normal reading group, reading fluency task. These results showed that the multivariate no rmality assumption was violated; (2) p = 74.21, p < .001) indicat ing that the assumption of homogeneity of covarian ce matrices was violated; and p = .05 level for five dependent variables ( p values all less than .044). A non significant Levene's test was found only for the read ing fluency task ( p = .985). This suggested that the assumption of homogeneity of error variance was violated. Because of these The MANOVA found significant group differences betwe en the means, F (6, 64) = 26.45 p < .001, partial 2 = .713, and observed power = 1.000. Univariate ANOVAs at

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64 the Bonferroni correction level of .008 on each basic reading task were conducted as follow up tests to determine which specific tasks account for the significant group differences. A significant difference between the two groups was found on all six basic reading measures (T SWR: F (1,69) = 59.27 p < .001; T NWR: F (1,69) = 150.35 p < .001; UT SWR: F (1,69) = 39.42 p < .001; UT NWR: F (1,69) = 35.79 p < .001; RF: F (1,69) = 28.61 p < .001; spelling: F (1,69) = 48.36 p < .001). Effect sizes reported as partial eta squared ( p 2 ) revealed that a ll of the six comparisons had very large effect sizes for the difference in estimated marginal means between the two groups ( T SWR: p 2 = .462 ; T NWR: p 2 = .685 ; UT SWR: p 2 = .364 ; UT NWR: p 2 = .342 ; RF: p 2 = .293 ; spelling p 2 = .412). These findings demonstrate that college students with dyslexia have significantly poorer basic reading skills than peer ma tched normal readers. Table 4 4 shows a summary of six univariate ANOVAs on the basic reading measures. Sub Question 4 : Group Comparison of Reading Comprehension A one way multivariate analysis of variance (MANOVA) and subsequent univari ate analyses of va riance (ANOVAs examine whether there are significant differences between college students with and without developmental dyslexia in the timed and extra timed reading comprehension tests (T RC and ET RC). Ea ch univariate ANOVA was tested at a significance level of .025 (.05/2). The total number of correct answers within the initial 20 minutes was used in the data analysis for the timed reading comprehension. The total number of correct answers within whole 32 minutes was used in the data analysis for the extra timed reading comprehension (both tasks: max 38). The subjects who completed all questions

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65 within the initial 20 minute time limit provided identical data in both timed and extra timed reading comprehens ion analyses. Three assumptions for the MANOVA were examined: (1) In the multivariate normality test, all skewness and kurtosis values in each group fell within the acceptable range of 2 to +1 for both dependent variables. These results indicated that the multivariate normality assumption was not violated in each group; (2 ) p = 44.46, p < .001) indicating that the assumption of homogeneity of c ovariance matrices was violated; and were significant at the p = .05 level for the timed reading comprehension task ( p < .001), not for the extra timed reading comprehension task ( p = .471). This suggested that the assumption of homogeneity of error variance was violated. Because of these vio inference. The MANOVA found significant group differences between the means, F (2, 68) = 1 2.41 p < .001, partial 2 = .267, and observed power = .995. Univariate ANOVAs using Bonferroni correcti on level of .025 on each reading comprehension task were conducted as follow up tests to determine which specific tasks account for the significant group differences. A significant difference between the two groups was found only in the timed reading compr ehension performance (T RC: F (1,69) = 24.00 p < .001). The difference between the two groups on the extra timed reading comprehension task was not significant at the p = .025 level (ET RC: F (1,69) = 4.95 p = .029). Effect size reported as partial eta squ ared ( p 2 ) indicated that the comparison of timed reading comprehension had a very large effect size for the difference in estimated marginal means between the two groups ( p 2 = .250). These results suggest that

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66 college students with dyslexia had significa ntly lower scores than peer matched normal readers on the timed reading comprehension test. However, when extended time was given, the reading comprehension between the two groups did not differ significantly. Th ese result s demonstrate that college student s with dyslexia have significantly lower scores than norm al readers on the timed test, despite their normal reading comprehension abilities This finding emphasizes the importance of processing speed in reading performance. Table 4 5 provides a summary of two univariate ANOVAs on the reading comprehension measures. Sub Question 5 : Group Comparison of Short Term and Working Memory Table 4 6 provides descriptive statistics for the two groups on the short term and working memory measures. Performance on two ty pes of memory tasks was analyzed by a mixed three factor analysis of variance (ANOVA), with group (college students with and without developmental dyslexia) as a between subject factor and memory type (short term and working memory; STM and WM) and modalit y (verbal and visual spatial modalities) as within subject factors. Raw scores (the total number of correct answers) in each task were used for the data analysis. The three f actor ANOVA yielded one significant main effect and two significant two way intera ctions: group main effect, group x memory type interaction, and memory type x modality interaction. These significant ANOVA results on the short term and working memory measures are shown in Table 4 7 F values were calculated under the assumption of spher icity, which evaluates the equality of the variances of the differences between levels of the within were not significant at the p = .05 level for main effects and interaction effect (memory, modaility, and memory type x modality) indicating that the assumption of sphericity was

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67 not violated. The significant group main effect indicated that dyslexic readers had significantly lower memory spans than normal readers (DD: M = 8.95, SE = .23; NR: M = 10.08, SE = .19; ( F (1,69) = 14.39, p < .001, p 2 = .173). The main effect was modified by significant interactions. A significant interaction was found between group and memory type ( F (1,69) = 4.26, p < .05, p 2 = .058). This interaction was explored by comparing the memor y spans of two groups across the short term and working memory measures. Dyslexic readers had significantly lower spans on both short term and working memory tasks than normal readers. Two groups showed significantly greater differences on the working memo ry tasks than on the short term memory tasks This result suggests that college students with dysl exia have weaker working memory skills than short term memory skills Mean differences (NR minus DD) and t scores on each measure were as follows: (1) STM: .8 0, t (69) = 2.66, p = .010; and (2) WM: 1.47, t (69) = 3.91, p < .001. A significant memory type x modality interaction was also obtained ( F (1,69) = 87.67, p < .001, p 2 = .560). This interaction was explored by comparing the memory spans between short term and working memory tasks across verbal and visual spatial modalities. The s hort term memory score was significantly higher than the working memory score i n t he verbal modality. I n contrast, the short term memory score was significantly lower than the worki ng memory score i n the visual spatial modality. Mean differences (STM minus WM) and t scores on each measure were as follows: (1) verbal modality: 1.75, t (70) = 6.49, p < .001; and (2) visual spatial modality: 1.43 (higher scores in working memory task), t (70) = 7.32, p < .001.

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68 As shown in Table 4 6, d yslexic readers had significantly lower spans on all memory tests except verbal short term memory. The greatest difference b etween the two groups occurred o n the verbal working memory task and the difference diminished slightly o n the visual spatial working memory task. The smallest group difference was found on the visual spatial short term memory task. d revealed medium to large effect sizes for the difference in means betwe en the two groups (visual spatial STM: d = .64; verbal WM: d = .78; visual spatial WM: d = .75). Cohen (1988) characterized an effect size of 0.2 to 0.3 as a small effect, around 0.5 as a medium effect, and above 0.8 as a large effect. These results emphas ize that college students with dyslexia have more difficultie s with working memory than with short term memory. Research Question 1 The primary goal of this study was to examine whether the processing speed deficits in young adults with developmental dysle xia are domain general or domain specific. Response time on four types of linguistic and nonlinguistic stimulus response tasks (three complexity levels in each task: total 12 tasks) was analyzed using a mixed four factor analysis of variance (ANOVA), with group (college students with and without developmental dyslexia; DD and NR) as a between subject factor and stimulus type (linguistic and nonlinguistic stimuli; LS and NLS; English and Korean letters), response type (verbal and motor responses; VR and MR; saying the number and pressing the button corresponding to the correct responses), and stimulus complexity (number of letters; single digit letter to triple digit letter cluster combinations) as within subject factors. Mean raw response times for correct r esponses in each task, measured in milliseconds, were used for the data analysis. Accuracy on four types of linguistic and

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69 nonlinguistic stimulus response tasks (not separated by complexity levels: total 4 tasks) was also analyzed using a mixed three facto r ANOVA, with group (DD and NR) as a between subject factor and stimulus types (LS and NLS), and response types (VR and MR) as within subject factors. The total number of correct responses in each task consisted of 48 trials was used for the data analysis. Post hoc pairwise comparison s using paired samples t tests were conducted to interpret interaction effects. T able 4 8 describes the performance of the two groups on the response time and accuracy measures for all linguistic and nonlinguistic processing speed tasks. Figure 4 1 and 4 2 display graphical representations of response time measures. The four factor ANOVA examining response times yielded significant findings for (1) four main effects, (2) four two way interactions, and (3) two three way interactions. These significant ANOVA results on the linguistic and nonlinguistic processing speed measures are shown in Tabl e 4 9 F values were calculated under the assumption of sphericity ricity tests indicated that main effect of complexity, stimulus x complexity interaction, response x complexity interaction, and stimulus x response x complexity interaction violated this assumption ( p values less than .05). The violation of the sphericity assumption results in an increase in the Type I error rate (Box, 1954). For this reason, F values for any effect involving complexity, stimulus x complexity interaction, response x complexity interaction, or stimulus x response x complexity interaction te rm were corrected based on the estimates of epsilon values (Keselman & Keselman, 1993). Greenhouse Geisser corrected F values were reported for any effect involving complexity (the epsilon values

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70 were less than 0.75) and Huynh Feldt corrected F values were reported for any effect involving stimulus x complexity interaction, response x complexity interaction, or stimulus x response x complexity interaction term (the epsilon values were more than 0.75). Significant main effects were found for all factors: gro up, stimulus type, response type, and stimulus complexity. Dyslexic readers were significantly slower in response time than normal readers (DD: M = 2608.80, SE = 45.00; NR: M = 2007.82, SE = 37.39; F (1,69) = 105.52, p < .001, p 2 = .605). Both groups respo nded significantly slower to nonlinguistic stimuli than linguistic stimuli (NLS: M = 2493.51, SE = 32.58; LS: M = 2123.12, SE = 39.66; F (1,69) = 74.36, p < .001, p 2 = .519) and performed significantly more slowly on motor response tasks than verbal respon se tasks (MR: M = 2358.61, SE = 31.64; VR: M = 2258.02, SE = 31.26; F (1,69) = 18.99, p < .001, p 2 = .216). Both groups showed significant increases in response time as the level of complexity increased (1 digit letter condition: M = 1395.55, SE = 15.38; 2 digit letter condition: M = 2390.84, SE = 33.45; 3 digit letter condition: M = 3138.55, SE = 45.50; F (1.36,93.60) = 1781.02, p < .001, p 2 = .963). The se main effects were modified by significant interactions. The ANOVA found four significant two way inte ractions: group x complexity, stimulus type x complexity, stimulus type x response type, and response typ e x complexity interactions. A significant interaction was found between group and complexity ( F (1.36,93.60) = 57.72, p < .001, p 2 = .456). This inter action was explored by comparing the response times of two groups across the three levels of complexity. Dyslexic readers responded significantly more slowly at all levels of complexity than

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71 normal readers. The differences between the two groups significan tl y increased with the increase of complexity. Th is result suggest s that processing s peed deficits in dyslexic readers become more marked as the complexity increases. Mean differences (DD minus NR) and t scores on each measure were as follows: (1) 1 digit letter condition: 267.88, t (69) = 8.71, p < .001; (2) 2 digit letter condition: 641.41, t (69) = 9.59, p < .001; and (3) 3 digit letter condition: 893.65, t (69) = 9.82, p < .001. A significant stimulus type x complexity interaction was also obtained ( F (1.58 ,109.20) = 14.84, p < .001, p 2 = .177). This interaction was explored by comparing the response times for two stimulus types, linguistic and nonlinguistic, across the three levels of complexity. Response time for nonlinguistic stimuli was significantly sl ower than for linguistic stimuli at all three levels of complexity. Interestingly, the greatest difference in response time between linguistic and nonlinguistic stimulus tasks was observed at the 2 digit letter condition. The 1 digit letter condition had t he least difference between linguistic and nonlinguistic stimulus tasks. Mean differences (NLS minus LS) and t scores on each measure were as follows: (1) 1 digit letter condition: 272.60, t (70) = 14.62, p < .001; (2) 2 digit letter condition: 534.65, t (70 ) = 10.74, p < .001; and (3) 3 digit letter condition: 341.78, t (70) = 4.78, p < .001. There was a significant stimulus type x response type interaction ( F (1,69) = 16.24, p < .001, p 2 = .191). This interaction was explored by comparing the response times between linguistic and nonlinguistic stimulus tasks across verbal and motor response modalities. Response time for nonlinguistic stimuli was significantly slower than for linguistic stimuli on both verbal and motor response tasks. The response tim es for th e two stimuli showed significantly greater diffe rence in motor responses than in oral

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72 responses. Mean differences (NLS minus LS) and t scores on each measure were as follows: (1) verbal response tasks: 308.18, t (70) = 8.06, p < .001; and (2) motor response tasks: 457.84, t (70) = 8.59, p < .001. A significant response type x complexity interaction was also found ( F (1.64,113.26) = 16.90, p < .001, p 2 = .197). This interaction was explored by comparing the response times for two response modalities, verbal an d motor, across the three levels of complexity. Motor responses were significantly slower than verbal responses for the 2 digit letter and 3 digit letter conditions. However, speed of performance for the 1 digit letter condition did not differ between verb al and motor responses. Mean differences (MR minus VR) and t scores on each measure were as follows: (1) 1 digit letter condition: .68, t (70) = .041, p = .97; (2) 2 digit letter condition: 93.89, t (70) = 3.23, p = .002; and (3) 3 digit letter condition: 189.69, t (70) = 4.78, p < .001. The ANOVA also yielded two significant three way interactions: group x stimulus type x complexity ( F (1.58,109.20) = 4.36, p = .022, p 2 = .059) and stimulus type x response type x complexity ( F (1.86,128.04) = 9.04, p < .001, p 2 = .116). The group x stimulus type x complexity interaction was explored by comparing the response times between linguistic and nonlinguistic stimulus tasks across the three levels of complexity in each group. Post hoc pairwise comparisons using Bonfe familywise error rate of .05 were conducted for each group separately. The critical significant level is .05/3 = .0167. Normal readers were significantly faster with linguistic stimuli than with nonlinguistic stimuli at all levels of complexity. However, dyslexic readers showed a different pattern of performance. Their linguistic processing speed

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73 was not always faster than nonlinguistic processing speed. Their differences between linguistic and nonlinguistic processing speed were s ignificant at 1 digit letter and 2 digit letter conditions, not at the 3 digit letter condition. This finding suggests that dyslexic response time for the linguistic stimuli inc rease as much as their response time for the nonlinguistic stimuli whe n the complexity increased. For the normal reading group, mean differences between two stimulus tasks (NLS minus LS) and t scores at each complexity level were as follows: (1) 1 digit letter condition: 273.62, t (41) = 16.64, p < .001; (2) 2 digit letter co ndition: 583.27, t (41) = 12.48, p < .001; and (3) 3 digit letter condition: 461.11, t (41) = 7.19, p < .001. For the dyslexia group, mean differences between two stimulus tasks (NLS minus LS) and t scores at each complexity level were as follows: (1) 1 digi t letter condition: 271.11, t (28) = 6.87, p < .001; (2) 2 digit letter condition: 464.24, t (28) = 4.59, p < .001; and (3) 3 digit letter condition: 168.96, t (28) = 1.17, p = .25. Table 4 10 and 4 11 provide a summ ary of post hoc pairwise comparisons for th e response times between linguistic and nonlinguistic stimulus tasks at the three levels of comp lexity in each group. Figure 4 3 and 4 4 display graphical representations of this information. The stimulus type x response type x complexity was explored by c omparing the verbal and motor response times across the three levels of complexity in each of linguistic and nonlinguistic processing domains. Follow up pairwise comparisons after In the nonlinguistic processing, the motor responses were significantly slower than verbal responses for the 2 digit letter and 3 digit letter conditions and almost significantly at the 1 digit letter condition ( p = .0171). These findings were consistent with the results of

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74 response type x complexity interaction. However, in the linguistic processing, the difference between two response modalities was significant only at the 1 digit letter condition (interestingly, the verbal responses were slower than mo tor responses). Their difference did not reach significance at the 2 digit letter and 3 digit letter conditions. This finding suggests that the differences between verbal and motor responses are more apparent at the nonlinguistic processing speed measures. In the nonlinguistic processing speed measures, mean differences between two response tasks (MR minus VR) and t scores at each complexity level were as follows: (1) 1 digit letter condition: 55.04, t (70) = 2.44, p = .017; (2) 2 digit letter condition: 118 .12, t (70) = 3.09, p = .003; and (3) 3 digit letter condition: 334.25, t (70) = 5.91, p < .001. In the linguistic processing speed measures, mean differenc es between two response tasks (MR minus V R) and t scores at each complexity level were as follows: (1) 1 digit letter condition: 56.40, t (70) = 3.26, p = .002; (2) 2 digit letter condition: 69.67, t (70) = 1.80, p = .076; and (3) 3 digit letter condition: 45.13, t (70) = .98, p = .329. As shown in Table 4 8, dyslexic readers performed significantly more sl owly on all processing speed tasks (total 12 tasks = 2 stimuli x 2 responses x 3 complexities) than normal readers. The two groups showed slightly greater differences on linguistic processin g speed tasks rather than nonlinguistic processing tasks. The dysl exic students were 18% to 30% slower in response time than their nondyslexic peers on the linguistic processing speed tasks while they were 16% to 21% slower in response time on the nonlinguistic processing speed tasks. d r evealed that a ll of the twelve comparisons had very large effect sizes ranging from 1.26 to 1.76. These findings suggest that young adults with dyslexia are significantly slower

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75 than age matched normal readers on both linguistic and non linguistic processi ng speed tasks, supporting the hypothesis that processing speed deficits in dyslexia are domain general. Accuracy on four types of linguistic and nonlinguistic stimulus response tasks was analyzed using a mixed three factor ANOVA. Under the assumption of s phericity, all F values for main effects and interactions were valid. The ANOVA found only a significant main effect for stimulus type. Participants were significantly less accurate on nonlinguistic stimulus tasks than linguistic stimulus tasks (LS: M = 46 .76, SE = .15; NLS: M = 45.52, SE = .17; F (1,69) = 50.09, p < .001, p 2 = .421). There were no other significant main effects or interactions. This result suggests that dyslexic readers were not less accurate than age matched normal readers on the linguist ic and nonlinguistic stimulus matching tasks, requiring verbal or motor response. Research Question 2 A second goal of this study was to determine whether any significant differences exist in performance on three standardized processing speed tests (modifi ed in the number of test items: 100 items total in all tests) between young adults with developmental dyslexia and age matched normal readers. A one way multivariate analysis of variance (MANOVA) and subsequent univariate analyses of variance (ANOVA s ), usi multiple comparisons, were conducted to compare response time on three standardized processing speed tests, written symbol digit substitution test (WSDS), oral symbol digit substituti on test (OSDS), and symbol copy test (SC), between the two groups. Raw response times required to complete the entire 100 test items in each task, measured in

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76 seconds, were used for the data analysis. Accuracy on three standardized processing speed tests w as also analyzed using the same statistical procedures (MANOVA and follow up ANOVA s ). The total number of correct responses in each task consisted of 100 test items was used for th e data analysis. T he associations between measures on three standardized tes ts and four experimental tests of processing speed in each group were analyzed using the Pearson correlation coefficient. Table 4 12 describes the performance of the two groups on the response time and accuracy measures for all standardized processing spee d tasks. Response time on the three standardized tests of processing speed between the two groups was compared using a one way multivariate analysis of variance (MANOVA) Three assumptions for the MANOVA were examined: (1) In the multivariate normality tes t, skewness and kurtosis values in each group fell within the range of 1 to +1 for all three dependent variables indicating that the multivariate normality assumption p = .001 le = 21.57, p = .002) indicating that the assumption of homogeneity of covariance matrices was not violated ; p = .05 level for the written and oral sym bol digit substitution tests, but not for the symbol copy test (WSDS: F (1, 69) = 3.14, p = .081; OSDS: F (1, 69) = 3.67, p = .059; SC: F (1, 69) = 6.69, p = .012). These results showed that the assumption of homogeneity of error variance was violated. Becaus e of ivariate statistical inference.

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77 The MANOVA found significant group differences between the means, F (3, 67) = 22.43, p < .001, partial 2 = .501, and observed power = 1.000. U nivariate ANOVAs using Bonferroni corrections on each standardized processing speed task were conducted as follow up tests to determine which specific tasks account for the significant group differences. The critical significant level for each comparison i s .05/3 = .0167. A significant difference between the two groups was found on all tasks. Estimated marginal mean differences (DD minus NR) and F values on each measure were as follows: (1) WSDS: 33.51, F (1,69) = 35.74, p < .001; (2) OSDS: 27.48, F (1,69) = 58.67, p < .001; and (3) SC: 15.67, F (1,69) = 28.08, p < .001. The dyslexic reader s were 19%, 17%, and 19% slower in their responses than their nondyslexic peers respectively on written symbol digit substitution test, oral symbol digit substitution test, a nd symbol copy test. Effect sizes reported as partial eta squared ( p 2 ) revealed very large effect sizes for the difference in estimated marginal means between the two groups ( WSDS: p 2 = .341 ; OSDS : p 2 = .460; SC: p 2 = .209) These findings suggest that young adults with dyslexia have a significantly slower processing speed than peer matched normal readers regard less of test modality. Table 4 13 shows a summary of three univariate ANOVAs on the response time measures of standardized processing speed task s. Figure 4 5 displays graphical representations of this information. Accuracy on the three standardized tests of processing speed between the two groups was compared using a one way multivariate analysis of variance (MANOVA). Three assumptions for the MAN OVA were examined: (1) In the multivariate normality test, skewness values in each group fell within the acceptable range of 2 to 1 for all three dependent variables while kurtosis values in each group ranged between 1 to +6

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78 (NR group: between 1 to +2; DD group: between +2 to +6). These results showed that the multivariate normality assumption was violated, es pecially in dyslexic group; (2) p = 103.69, p < .001) indicating that the assumption of homogeneity of c ovariance matrices was violated; and (3) p = .05 level for all three dependent variables (all p values were less than .001), indicating that the assumption of homogeneity of error variance was violated multivariate statistical inference. The MANOVA found significant group differences between the means, F (3, 67) = 6.44, p < .001, partial 2 = .224, and observed power = .961. Univariate ANOVAs at t he Bonferroni correction level of .0167 on each standardized processing speed task were conducted as follow up tests to determine which specific tasks account for the significant group differences. A significant difference between the two groups was found on the written symbol digit substitution test and symbol copy test, not on the oral symbol digit substitution test (WSDS: F (1,69) = 8.34, p = .005; OSDS: F (1,69) = 3.73, p = .058; SC: F (1,69) = 13.40, p < .001). Effect sizes reported as partial eta squared ( p 2 ) indicated that two comparisons have the values of 0.11 or higher ( WSDS: p 2 = .11; SC: p 2 = .16). They represented moderate to large effect sizes for the difference in estimated marginal means between the two groups. These resul ts suggest that dysl exic reader s had significantly greater difficulty in accuracy than age matched normal readers on the two standardized processing speed tasks, written symbol digit substitution test and symbol copy test. A summary of three univariate ANOVAs on the accuracy measures of standardized processing spee d tasks is provided in Table 4 14

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79 To explore the associations between the performances on three standardized tests and four experimental tests of processing speed in each group, Pearson correlation coefficients were calculated. Significance level was defined as p < .05 (two tailed). The three standardized tests included written symbol digit substitution test (WSDS), oral symbol digit substitution test (OSDS), and symbol copy test (SC). Raw response times required to complete the entire 100 test items in each task were used for the data analysis. The four experimental tests included linguistic stimulus verbal response test (LS VR), linguistic stimulus motor response test (LS MR), nonlinguistic stimulus verbal response test (NLS VR), and nonlinguistic stimulus motor response test (NLS MR). Mean raw response times for correct responses in each experimental processing speed task were used f or the data analysis. Table 4 15 and Table 4 16 show the correlation matrices betwee n all processing speed tasks for each group. In the dyslexic group, two standardized processing speed tasks, WSDS and OSDS were significantly correlated (r = .747, p < .001), but SC was not correlated with both WSDS and OSDS. Two linguistic stimulus variab les, LS VR and LS MR were significantly correlated (r = .824, p < .001). A significant correlation was also found between two nonlinguistic stimulus variables, NLS VR and NLS MR (r = .548, p < .001). Two verbal response variables, LS VR and NLS VR were sig nificantly correlated (r = .462, p < .05) while two motor response variables, LS MR and NLS MR were not correlated (r = .058, p = .764). Two standardized tests, WSDS and OSDS were significantly correlated with all experimental processing speed tests, excep t LS VR. Unexpectedly, the SC was not correlated with any experimental tests, indicating that the SC was not related at all to other processing speed variables.

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80 In the normal reading group, all standardized processing speed tasks, WSDS, OSDS, and SC were s ignificantly correlated with each other (WSDS & OSDS: r = .760, p < .001; WSDS & SC: r = .314, p < .05; OSDS & SC: r = .335, p < .05). Two linguistic stimulus variables, LS VR and LS MR were significantly correlated (r = .678, p < .001) and two nonlinguist ic stimulus variables, NLS VR and NLS MR were also significantly correlated (r = .703, p < .001). These patterns of performance were observed in both dyslexic and normal reading groups. However, unlike the dyslexic group, two verbal response variables, LS VR and NLS VR were significantly correlated (r = .486, p < .01) and two motor response variables, LS MR and NLS MR were also significantly correlated (r = 382, p < .05). Only one standardized test, WSDS were significantly correlated with experimental proce ssing speed tests, LS MR (r = 326, p < .05) and NLS VR (r = 323, p < .05). There were no other significant correlations between the standardized and experimental processing speed tests. Interestingly, the SC was not correlated with any experimental tests, except the standardized tests. This finding suggests that the SC does not always show the significant interrelationships with other processing speed tests.

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81 Table 4 1. Descriptive statistics for DD and NR groups on cognition, phonological awareness, ra pid naming, reading, and spelling measures Measures (maximum scores) DD Group (N=29) NR Group (N=42) M SD Min Max M SD Min Max Cognition Verbal Comprehension (71) 54.97 4.17 49 63 58.88 4.03 51 67 Long Term Retrieval (109) 97.31 10.59 64 109 102.60 6.81 76 109 Visual Spatial Thinking (81) 71.31 4.87 61 80 73.90 4.23 60 80 Fluid Reasoning (40) 35.52 3.10 27 40 36.88 2.41 31 40 Phonological Awareness Elision (20) 16.86 3.37 6 20 18.90 .93 15 20 Sound Blending (33) 25.86 5.6 0 16 33 29.36 2.13 24 32 Naming Speed RAN Objects (secs) 31.76 4.61 26 44 26.55 3.37 20 38 RAN Colors (secs) 31.59 5.80 22 50 24.57 3.54 17 32 RAN Numbers (secs) 21.52 4.28 15 31 16.83 2.55 11 22 RAN Letters (secs) 21.79 4.68 16 38 16.74 2.53 10 22 RAN 2 Set Letters & Numbers (secs) 23.59 5.10 16 37 18.67 2.86 12 25 RAN 3 Set Letters, Numbers, & Colors (secs) 25.69 4.86 18 36 20.02 3.27 11 27 Word Reading Timed Word Reading Timed Sight Word Reading (104) 84.66 10.37 64 104 99.29 5.55 85 104 Timed Nonsense Word Reading (63) 40.31 7.05 22 55 57.02 4.44 46 63 Untimed Word Reading Untimed Sight Word Reading (76) 68.86 3.26 63 75 72.81 2.04 68 76 Untimed Nonsense Word Reading (32) 25.72 4.04 15 32 29.86 1.62 26 32 Reading Fluency (601) 180.31 48.96 106 299 246.69 53.00 195 443 Reading Comprehension Timed Reading Comprehension (38) 28.28 6.02 16 35 33.50 3.08 25 38 Extra Timed Reading Comprehension (38) 32.66 2.11 29 36 33.95 2 .60 27 38 Spelling (59) 46.93 4.65 34 54 53.05 2.75 45 57 M: mean, SD: standard deviation, Min: minimum, Max: maximum

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82 Table 4 2 Univariate ANOVAs for DD and NR comparison on the two phonological awareness tasks Dependent Variables MS MSE F (1,69) p v alue p artial 2 O bserved power Elision 71.58 5.12 13.99 .000* .169 .958 Sound Blending 209.56 15.44 13.58 .000* .164 .953 Comparisons are based on estimated marginal means. The Bonferroni critical p value for multiple comparisons is .025. MS: mean squar e, MSE: mean square for error, partial 2 = effect size, *: p < .001 Table 4 3 Univariate ANOVAs for DD and NR comparison on the six rapid automatized naming tasks Dependent Variables MS MSE F (1,69) p value partial 2 O bserved power RAN Objects 465.83 15.36 30.33 .000* .305 1.000 RAN Colors 844.15 21.09 40.02 .000* .367 1.000 RAN Numbers 376.36 11.29 33.33 .000* .326 1.000 RAN Letters 438.36 12.68 34.57 .000* .334 1.000 RAN 2 Set Letters & Numbers 415.18 15.43 26.92 .000* .281 .999 RAN 3 Set Lette rs, Numbers, & Colors 550.70 15.93 34.57 .000* .334 1.000 Comparisons are based on estimated marginal means. The Bonferroni critical p value for multiple comparisons is .008. MS: mean square, MSE: mean square for error, partial 2 = effect size, *: p < .0 01

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83 Table 4 4 Univariate ANOVAs for DD and NR comparison on the six basic reading measures Dependent Variables MS MSE F (1,69) p value partial 2 O bserved power Timed Sight Word Reading 3672.06 61.9 6 59.27 .000* .462 1.000 Timed Nonsense Word Reading 4792.06 31.87 150.35 .000* .685 1.000 Untimed Sight Word Reading 267.32 6.78 39.42 .000* .364 1.000 Untimed Nonsense Word Reading 293.04 8.19 35.79 .000* .342 1.000 Reading Fluency 75590.14 2642.16 28.61 .000* .293 1.000 Spelling 641.81 13.27 48.36 .00 0* .412 1.000 Comparisons are based on estimated marginal means. The Bonferroni critical p value for multiple comparisons is .008. MS: mean square, MSE: mean square for error, partial 2 = effect size, *: p < .001 Table 4 5 Univariate ANOVAs for DD an d NR comparison on the two reading comprehension measures Dependent Variables MS MSE F (1,69) p value partial 2 Observed power Timed Reading Comprehension 468.19 20.35 23.00 .000* .250 .997 Extra Timed Reading Comprehension 28.87 5.83 4.95 .029 .0 67 .592 Comparisons are based on estimated marginal means. The Bonferroni critical p value for multiple comparisons is .025. MS: mean square, MSE: mean square for error, partial 2 = effect size, *: p < .001

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84 Table 4 6. Descriptive statistics for DD an d NR groups on short term and working memory measures Measures (maximum scores) DD Group (N=29) NR Group (N=42) t (69) p ES M SD Min Max M SD Min Max Short Term Memory Verbal STM (16) 9.97 1.80 6 14 10.71 2.13 7 15 1.55 .127 .37 Vi sual Spatial STM (16) 8.48 1.46 6 11 9.33 1.20 7 12 2.69 .009* .64 Working Memory Verbal WM (16) 7.66 1.86 4 11 9.36 2.44 5 15 3.18 .002* .78 Visual Spatial WM (16) 9.69 1.71 6 13 10.93 1.61 7 14 3.10 .003* .75 M: mean, SD: standard devi ation, Min: minimum, Max: maximum d ), p < .01 Table 4 7 Summary of mixed three factor ANOVA on short term and working memory measures Effects F value p value partial 2 Observed power Main Effects Group F (1,69) = 14.39 000** .173 .962 Memory type F (1,69) = 1.77 .188 .025 .259 Modality F (1,69) = .69 .408 .010 .130 Two way Interaction Group x Memory type F (1,69) = 4.26 .043* .058 .530 Memory type x Modality F (1,69) = 87.67 .000** .560 1.000 Group x Mod ality F (1,69) = .16 .686 .002 .069 Three way Interaction Group x Memory type x Modality F (1,69) = .67 .416 .010 .127 Sphericity assumed F values for all main and interaction effects. p < .05, ** p < .001

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85 Table 4 8 Descriptive statistics for DD and NR groups on linguistic and nonlinguistic processing speed measures Measures DD Group (N=29) NR Group (N=42) t (69) p ES M SD Min Max M SD Min Max LS VR 1 Digit Letters RT (ms) 1416.94 200.89 1101.44 1972.19 1156.59 104. 02 927.33 1446.40 7.14 .000* 1.63 2 Digit Letters RT (ms) 2413.04 524.69 1449.63 3522.94 1765.44 249.69 1170.64 2450.88 6.95 .000* 1.58 3 Digit Letters RT (ms) 3454.33 695.36 2243.06 5089.54 2455.18 401.53 1715.33 3394.00 7.66 .000* 1.76 Accu racy (48) 46.90 1.24 43 48 46.88 1.15 43 48 .05 .957 .02 LS MR 1 Digit Letters RT (ms) 1370.93 227.46 1054.13 1888.94 1093.01 119.33 869.44 1342.56 6.71 .000* 1.53 2 Digit Letters RT (ms) 2545.80 633.68 1710.50 4258.94 1791.55 27 5.18 1283.31 2625.00 6.85 .000* 1.54 3 Digit Letters RT (ms) 3547.47 777.63 2433.33 5884.13 2467.16 381.57 1834.00 3217.00 7.77 .000* 1.76 Accuracy (48) 46.34 2.08 39 48 46.93 1.09 44 48 1.54 .127 .36 NLS VR 1 Digit Letters R T (ms) 1634.41 171.32 1253.25 1945.63 1373.05 131.72 1121.63 1666.88 7.26 .000* 1.71 2 Digit Letters RT (ms) 2860.09 347.99 1924.87 3489.79 2319.63 262.54 1792.36 2844.80 7.46 .000* 1.75 3 Digit Letters RT (ms) 3469.15 534.63 2652.67 4889.50 277 8.34 392.68 1933.45 3808.50 6.28 .000* 1.47 Accuracy (48) 45.69 1.23 43 48 45.52 1.60 42 48 .47 .639 .12 NLS MR 1 Digit Letters RT (ms) 1695.68 235.65 1282.44 2055.13 1423.79 192.36 1078.88 2018.47 5.34 .000* 1.26 2 Digit Lette rs RT (ms) 3027.24 411.68 2217.20 3740.53 2403.89 345.20 1757.19 3180.93 6.91 .000* 1.64 3 Digit Letters RT (ms) 3870.56 621.94 3068.43 5940.50 3066.22 440.94 2266.25 4145.00 6.38 .000* 1.49 Accuracy (48) 45.45 1.80 41 48 45.40 1.74 42 48 .10 919 .03 Note. (1) LS VR: linguistic stimulus verbal response test, (2) LS MR: linguistic stimulus motor response test, (3) NLS VR: nonlinguistic stimulus verbal response test, (4) NLS MR: nonlinguistic stimulus motor response, RT: response time, M: mean, SD: standard deviation, Min: minimum, Max: maximum d ), p < .001

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86 Table 4 9 Summary of mixed four factor ANOVA on linguistic and nonlinguistic processing speed measures Effects F value p value Partial 2 Observed power Main Effects Group F (1,69) = 105.52 (A) .000** .605 1.000 Stimulus type F (1,69) = 74.36 (A) .000** .519 1.000 Response type F (1,69) = 18.99 (A) .000** .216 .990 Complexity F (1.36,93.60) = 1781.02 (B) .000** .963 1.000 2 W ay Interaction Group x Complexity F (1.36,93.60) = 57.72 (B) .000** .456 1.000 Stimulus type x Complexity F (1.58,109.20) = 14.84 (C) .000** .177 .995 Response type x Complexity F (1.64,113.26) = 16.90 (C) .000** .197 .999 Stimulus type x Response type F (1,69) = 16.24 (A) .000** .191 978 Group x Stimulus type F (1,69) = 2.58 (A) .113 .036 .353 Group x Response type F (1,69) = 2.22 (A) .141 .031 .312 3 W ay Interaction Group x Stimulus type x Complexity F (1.58,109.20) = 4.36 (C) .022* .059 .673 Stimulus Type x Response ty pe x Complexity F (1.86,128.04) = 9.04 (C) .000** .116 .964 Group x Stimulus type x Response type F (1,69) = .000 (A) .994 .000 .050 Group x Response type x Complexity F (1.64,113.26) = .967 (C) .369 .014 .197 4 W ay Interaction Group x Stimulus x R esponse x Complexity F (1.86,128.04) = .116 (C) .735 .002 .063 A: Sphericity assumed F values, B: Greenhouse Geisser corrected F values, C: Huynh Feldt corrected F values p < .05, ** p < .001

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87 Table 4 10 Post hoc pairwise comparisons for the res ponse times between linguistic and nonlinguistic stimulus tasks at the three levels of complexity in the DD group LS vs NLS Mean Difference (NLS LS) SE t (28) p ES 95% Confidence Interval for Difference Lower Bound Upper Bound 1 Digit Letter Condit ion 271.11 39.44 6.87 .000* 1.28 190.33 351.90 2 Digit Letter Condition 464.24 101.22 4.59 .000* .90 256.90 671.59 3 Digit Letter Condition 168.96 144.09 1.17 .251 .22 126.21 464.12 The Bonferroni critical p value for multiple comparisons is .0167. L d ), p < .001 Table 4 11 Post hoc pairwise comparisons for the response times between linguistic and nonlinguistic stimulus tasks at the three levels of com plexity in the NR group LS vs NLS Mean Difference (NLS LS) SE t (41) p ES 95% Confidence Interval for Difference Lower Bound Upper Bound 1 Digit Letter Condition 273.62 16.45 16.64 .000* 2.85 240.41 306.84 2 Digit Letter Condition 583.27 46.73 12 .48 .000* 1.94 488.90 677.63 3 Digit Letter Condition 461.11 64.14 7.19 .000* 1.11 331.57 590.65 The Bonferroni critical p value for multiple comparisons is .0167. LS: linguistic stimuli, NLS: nonlinguistic stimuli SE: standard error, ES: effect size (C d ), p < .001

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88 Table 4 12. Descriptive statistics for DD and NR groups on standardized processing speed measures Measures DD Group (N=29) NR Group (N=42) M SD Min Max M SD Min Max Written Symbol Digit Substitution RT (sec) 179.1 7 28.74 129 258 145.67 18.52 109 197 Accuracy (100) 97.66 3.00 88 100 99.17 1.32 95 100 Oral Symbol Digit Substitution RT (sec) 159.24 17.57 127 194 131.76 12.68 107 159 Accuracy (100) 98.41 2.34 90 100 99.19 .97 97 100 Symbol Copy RT (sec) 81.24 15.55 53 119 65.57 9.35 52 89 Accuracy (100) 98.79 1.59 93 100 99.74 .45 99 100 RT: response time, M: mean, SD: standard deviation, Min: minimum, Max: maximum

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89 Table 4 13. Univariate ANOVAs for DD and NR comparison of the response time measures on three standardized processing speed tasks Dependent Variables MS MSE F (1,69) p value partial 2 Observed power Written Symbol Digit Substitution 19258.73 538.80 35.74 .000* .341 1.000 Oral Symbol Digit Substitution 12954.06 22 0.80 58.67 .000* .460 1.000 Symbol Copy 4212.35 149.99 28.08 .000* .289 .999 Comparisons are based on estimated marginal means. The Bonferroni critical p value for multiple comparisons is .0167. MS: mean square, MSE: mean square for error, partial 2 = e ffect size, *: p < .001 Table 4 14. Univariate ANOVAs for DD and NR comparison of the accuracy measures on three standardized processing speed tasks Dependent Variables MS MSE F (1,69) p value partial 2 Observed power Written Symbol Digit Substitution 39.19 4.70 8.34 .005* .108 .812 Oral Symbol Digit Substitution 10.35 2.78 3.73 .058 .051 .478 Symbol Copy 15.32 1.14 13.40 .000** .163 .950 Comparisons are based on estimated marginal means. The Bonferroni critical p value for multiple compari sons is .0167. MS: mean square, MSE: mean square for error, partial 2 = effect size, *: p < .01, **: p < .001

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90 Table 4 15 Correlation matrix between the response time measures of three standardized tests and four experimental tests of processing speed in DD group 1 2 3 4 5 6 7 1. Written Symbol Digit Substitution 2. Oral Symbol Digit Substitution .747** 3. Symbol Copy .081 .267 4. Linguistic Stimulus Verbal Response .144 .275 .330 5. Linguistic Stimulus Motor Respons e .425* .562** .268 .824** 6. Nonlinguistic Stimulus Verbal Response .452* .546** .312 .462* .565** 7. Nonlinguistic Stimulus Motor Response .603** .470* .055 .089 .058 .548** *: p < .05; **: p < .001 Table 4 16. Correlation matrix bet ween the response time measures of three standardized tests and four experimental tests of processing speed in NR group 1 2 3 4 5 6 7 1. Written Symbol Digit Substitution 2. Oral Symbol Digit Substitution .760*** 3. Symbol Copy .314* .33 5* 4. Linguistic Stimulus Verbal Response .207 .276 .022 5. Linguistic Stimulus Motor Response .326* .204 .077 .678*** 6. Nonlinguistic Stimulus Verbal Response .323* .181 .153 .486** .429** 7. Nonlinguistic Stimulus Motor Re sponse .273 .076 .061 .153 .382* .703*** *: p < .05; **: p < .01; ***: p < .001

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91 Figure 4 1 Bar chart for the response time measures of linguistic processing speed tasks for the DD and NR groups Figure 4 2 Bar chart for the response time m easures of non linguistic processing speed tasks for the DD and NR groups

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92 Figure 4 3 Line graph for the response time measures between linguistic and nonlinguistic stimulus tasks at the three levels of complexity in the DD group Figure 4 4 Line graph for the response time measures between linguistic and nonlinguistic stimulus tasks at the three levels of complexity in the NR group

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93 Figure 4 5. Bar chart for the response time measures of three standardized processing speed tasks for the DD and NR groups

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94 CHAPTER 5 DISCUSSION The primary focus of this study was to compare the performance of linguistic and nonlinguistic processing speed measures in young adults with and without dyslexia to investigate whether the processing speed deficits in dy slexic readers are restricted to linguistic information processing only or also affect speed of nonlinguistic information processing. To measure linguistic and nonlinguistic processing speed, four types of experimental tasks were produced using MediaLab an d DirectRT software in identical formats regarding stimulus presentation (target stimulus and five test stimuli), response requirement (verbal and motor responses), and complexity manipulation (single digit letter, double digit letters and triple digit le tters). A second purpose of this study was to compare the two groups on three standardized tests of processing speed ( modified in the number of test items; written symbol digit substitution test, oral symbol digit substitution test, and symbol copy test) a nd to investigate within group interrelationships on th ree standardized tests and four experimental tests of processing speed. Before addressing two main research questions, data from comparing the two groups on standardized reading and reading related te sts were presented. Two groups were compared on the tests of phonological awareness (elision and sound blending), rapid naming (RAN objects, RAN colors, RAN numbers, RAN letters, RAN 2 set letters & numbers, and RAN 3 set letters, numbers, & colors), word reading (timed and untimed sight word and nonsense word reading), reading fluency, spelling, reading comprehension (timed and extra timed reading comprehension), and memory (verbal and visual spatial short term and working memory). Significant differences between the

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95 two groups were found on all standardized reading and reading related tests, except on an extended time reading comprehension measure and on verbal short term memory test. These results demonstrated that college students with dyslexia have sign ificantly poorer phonological awareness, rapid naming, word reading, reading fluency, spelling, timed comprehension and working memory than peer matched normal readers. Dyslexic adults are often characterized with relatively high levels of reading compre hension abilities, despite of their inaccurate and slow word recognition skills. Previous s tudies have indicated that their intact cognitive abilities, such as verbal ability, semantic knowledge, and reasoning, can be causes of their relatively good compre hension (Frith & Snowling, 1983; Nation & Snowling, 1997; Shaywitz, 2003; Snowling, 2000; Torgesen et al., 2001). This study suggests that college students with dyslexia scored significantly lower than normal readers on the reading comprehension test under timed conditions despite their normal reading comprehension. This finding underscores the importance of testing processing speed in diagnosing reading disabilities of young adults. Th e present study found that college students with dyslexia have weaker working memory (WM) skills than short term memory (STM) skills. Dyslexic readers performed significantly more poorly than normal readers on the verbal and visual spatial WM and visual spatial STM tests, but not on the verbal STM test. The greatest differen ce between the two groups was found in verbal WM and the difference decreased in visual spatial WM. The lowest difference was observed in the visual spatial STM. These results are partially consistent with previous findings that individuals with dyslexia e xhibit weaker verbal WM than visual spatial WM skills (Papadopoulos, Charalambous,

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96 Kanari, & Loizou, 2004; Siegel & Ryan, 1989; Vellutino, Scanlon, & Spearing, 1995). However, this study f ailed to find a significant group difference on the verbal STM test. This finding contradicts previous studies which have indicated that dyslexics have limited verbal STM capacity. Snowling (2000) noted that reduced verbal STM span is perhaps the most consistently reported area of difficulty for dyslexic children and adult s. Paulesu, Frith, Snowling, and Gallagher (1996) found that the verbal STM difficulties are still present in dyslexic adults who have compensated fully for their reading problems. Some studies emphasized that that dyslexic readers have poor verbal STM, bu t their visual STM is intact (Hulme, 1981; Jeffries & Everatt, 2004; Kibby & Cohen, 2008; Kibby, Marks, Morgan, & Long; 2004; Shankweiler, Liberman, Mark, Fowler, & Fischer, 1979). The data from this study support that impaired memory function is one of th e main characteristics of dyslexia and suggest that t his weakness is more emphasized in the WM performance than in the STM performance. Findings from Experimental Processing Speed Tasks The present study revealed that slow processing speed in dyslexics re present s a domain general deficit that affects speed of both linguistic and nonlinguistic processing. Dyslexic readers performed significantly more slowly than normal readers on all linguistic and nonlinguistic processing speed tasks and all of these compa risons had very large effect sizes. Similar results have been found from several previous studies that examined processing speed in dyslexics across linguistic and nonlinguistic stimuli, even though their findings did not show clear and significant differe nces between dyslexic and normal readers on every linguistic and nonlinguistic processing speed task (Bonifacci & Snowling, 2008; Breznitz, 2002; Meyler & Breznitz, 2005).

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97 Many previous studies have indirectly indicated that dyslexic readers have global pr ocessing speed deficits which are not restricted to reading performance. Impaired visual, auditory, motor, and tactile processing speed in dyslexic readers has been consistently reported from various studies using perceptual, cognitive, and behavioral task s (Amitay, Ahissar & Nelken, 2002; Demb, Boyton, Best, & Heeger, 1998; Eden, Stein, Wood, & Wood, 1995; Fawcett & Nicolson, 2002; Galaburda & Livingstone, 1993; Hansen, Stein, Orde, Winter, & Talcott, 2001; Slaghuis, Lovegrove, & Davidson, 1993; Talcott & Witton, 2002; Thomson, F ryer, Maltby, & Goswami, 2006; v an Ingelghem, Boets, van Wieringen, Ghesquie`re, & Wouters, 2004; Wilmer, Richardson, Chen, & Stein, 2004; Wright, Bowen, & Zecker, 2000). This study was designed to eliminate, in as far as possible, many of the methodological factors in previous studies that rendered their findings inconclusive. By controlling for factors associated with both subject selection and design implementation, data from this study provides clear evidence of domain general pr ocessing speed deficits in dyslexic readers when domains are limited to two types of stimuli (linguistic and nonlinguistic) and two modes for responding (verbal and motor). However, not all previous studies have supported that dyslexic readers have slower and less efficient processing speed as compared to normal readers. A considerable number of studies have reported that impaired auditory processing speed was found only in a subgroup of dyslexics, ranging from a few individuals to half of study subjects (A dlard & Hazan, 1998; Lorenzi, Dumont, & Fullgrabe, 2000; Manis et al., 1997; Marshall, Snowling, & Bailey, 2001; Mody, Studdert Kennedy, & Brady, 1997; Reed, 1989; Rosen & Manganari, 2001; Tallal, 1980). Further, Heath, Hogben, and

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98 Clark (1999) and McArth ur and Hogben (2001) indicated that auditory deficits were found only in dyslexic readers who have additional language impairments. In the visual processing studies, some have failed to find any evidence for a visual deficit in dyslexic readers (Victor, Co nte, Burton, & Nass, 1993; Johannes, Kussmaul, Munte, & Mangun, 1996) and some have argued that visual dysfunction was applied to a restricted group of dyslexics (Amitay, Ben Yehudah, Banai, & Ahissar, 2002; Cornelissen, Richardson, Mason, Fowler, & Stein, 1995 ). Among motor processing studies, Yap and v an der Leij (1994) replicated the balance/dual tasks examined by Nicolson and Fawcett (1990, 1994) and found that dyslexic readers performed poorly in only one dual task. Wimmer, Mayringer, and Landerl (1998 ) and Stringer and Stanovich (1998) failed to find any motor dysfunction evidence on the dual tasks. More attempts to find motor and automaticity deficits in dyslexics were unsuccessful (Kronbichler, Hutzler, & Wimmer, 2002 ; van Daal & van der Leij, 1999 ). Some studies reported that the motor impairments were observed only in dyslexic children who have attention deficit hyperactivity disorder ( Denckla, Rudel, Chapman, & Krieger, 1985; Wimmer, Mayringer, & Raberger 1999). These findings show that there is s till controversy surrounding the global processing speed deficits in dyslexia. It is possible that processing speed deficits in dyslexics are limited to the response system and do not impact sensory systems. No study to date has employed a design that care fully and comparably examines processing speed across response (i.e., verbal, motor) and sensory (i.e., auditory, visual) modalities. The present study found that the differences between the two groups were slightly greater on linguistic processing speed t asks than nonlinguistic processing tasks. The

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99 dyslexic readers were 18% to 30% slower in response time than normal readers on the linguistic stimulus tasks while they were 16% to 21% slower in response time on the nonlinguistic stimulus tasks. This pattern has been also shown in previous studies (Boden & Brodeur, 1999; Tallal, Merzenich, Miller, & Jenkins, 1998; Meyler & Breznitz, 2005) which have concluded that dyslexic individuals exhibit deficits in processing both linguistic and nonlinguistic stimuli bu t their difficulties are more noticeable in linguistic processing. Boden & Broder (1999) found that visual temporal integration deficits in dyslexic readers were more exacerbated at the linguistic level. Meyler and Breznitz (2005) also indicated that dysle xic readers were more impaired when processing linguistic sequences (e.g., visual syllables) rather than processing nonlinguistic sequences (e.g., flashes or beeps). In contrast, some studies have argued that processing speed deficits in dyslexic readers a re only apparent in the linguistic tasks and their nonlinguistic performances are not impaired. Breier and colleague s (2002) reported that dyslexic children exhibited deficits in perception of speech at the syllable levels, but not pure tone complexes. Ele ctrophysiological (event related potentials, ERP) experiments conduced by Schulte Korne and colleague s (1998, 2001) also speech processing tasks (e.g., phonemes or syllable s), not on auditory processing tasks (e.g., simple tones). These findings support a domain specific deficit in dyslexia comparable to the phonological core deficit hypothesis. This study a lso showed that both groups were significantly slower and less accur ate on nonlinguistic stimulus tasks than linguistic stimulus tasks. This finding is not surprising from an evolutionary perspective in that the accumulation of linguistic

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100 experiences through reading and writing in literate societies that requires repeated experience with the visual processing of print; hence, this high rate of exposure to written language is likely to result in faster and more accurate responses to linguistic stimuli than nonlinguistic stimuli. Such findings may help explain results from th e current study in which there were greater differences between the two groups on the linguistic tasks as compared to the nonlinguistic tasks. If normal readers benefit from their accumulated linguistic experience when processing linguistic stimuli, the di fferences between the two groups would be more obvious on the activities associated with linguistic processing speed. More importantly, group differences were significantly associated with stimulus complexity. The differences between th e two groups increas ed rapidly with the increase of complexity This finding suggests that processing speed deficits in dyslexics deteriorate as the complexity of the stimulus increases. Many studies have demonstrated that stimulus complexity influences the speed of informati on processing: the more complex a stimulus, the longer the duration of information processing. Nicolson and Fawcett (1994) found that dyslexic children were significantly slower than normal children on selective choice reaction time tasks (i.e., requiring decisions), but not on the simple reaction time tasks. Dyslexic readers also performed more poorly on the tasks that required the processing of two or more stimuli presented sequentially, such as individuation tasks or temporal order tasks, than on the tas ks using a single stimulus (Helenius, Uutela, & Hari, 1999; Overy, Nicolson, Fawcett, & Clarke, 2003; Stein & McAnally, 1995; Tallal, 1980; Tallal, Miller, & Fitch, 1993; Tallal, Merzenich, Miller, & Jenkins, 1998; Witton et al., 1998). In summarizing stud ies of visual or auditory

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101 processing, using reaction time measures and ERP experiments, Breznitz (2006) concluded that the differences in speed of performance between dyslexic and nondyslexic readers increases with the complexity of the tasks. T he results of this study are consistent with this conclusion. As mentioned above, both groups were significantly faster with the linguistic stimuli compared to the nonlinguistic stimuli However, at each level of complexity, the two groups did not exhibit identical p attern of performance. Normal readers were still significantly faster with linguistic stimuli than with nonlinguistic stimuli at all levels of complexity whereas dyslexic readers were significantly faster with linguistic stimuli than with nonlinguistic sti muli at 1 digit letter and 2 digit letter conditions, but not at the 3 digit letter condition. These findings show was just as slow as their nonlinguistic processing speed when using the most complex stim u li (3 digit letter condition), suggesting that while processing speed deficits appears to be domain general in dyslexics, advanced processing speed of linguistic information may be less efficient when stimuli becomes complex. Previous studies have provided evidence that linguistic stimuli are processed faster than nonlinguistic stimuli, and the discrepancy between linguistic and nonlinguistic processing speed is greater in adulthood (Jenkins, Myerson, Joerding, & Hale, 2000; Lawrence, Myerson, & Hale, 1998) Consistent with these findings, normal readers demonstrated significant differences between linguistic and nonlinguistic processing speed at all levels of complexity, likely as a result of accumulated linguistic experience and exposure. Based on the resu lts of the current study, it might be argued that dyslexic readers have d evelopmental problems in improv ing their linguistic processing speed despite

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102 continuous linguistic activities and their impaired linguistic processing speed (not developed sufficientl y) is more apparent when the complexity of the linguistic stimulus processing linguistic information. In this study, response modality (verbal and motor responses) did not a ffect the difference in the performance of the two groups. Both groups performed significantly faster on the verbal response tasks than motor response tasks. This pattern was more obvious on the nonlinguistic processing speed measures than the linguistic p rocessing speed measures. Notably, stimulus complexity influences response modality. The verbal responses were significantly faster than motor responses for the 2 digit letter and 3 digit letter conditions, but not for the 1 digit letter condition. These f indings suggest that the dyslexic readers as well as normal readers were significantly slower on motor response tasks than verbal response tasks and the difference between verbal and motor responses increases with the increase of complexity. Findings from Standardized Processing Speed Tasks Impaired processing speed in dyslexic readers was demonstrated repeatedly through the three standardized processing speed tests (modified in the number of test items): written symbol digit substitution test (WSDS), oral symbol digit substitution test (OSDS), and symbol copy test (SC). Dyslexic readers were significantly slower than normal readers on all tests, with similar rates of decrease in response times ( 19%, 17%, and 19% slower, respectively). In the accuracy measur es, significant group differences were found on the two motor response tests (WSDS and SC), not on the verbal response test (OSDS). This finding suggests that dyslexic readers have deficits in both verbal and motor processing speed, particularly with motor execution problems (lower

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103 accuracy in motor performance). Three standardized tests and four experimental tests of processing speed were more strongly correlated in dyslexic group than in normal group. Dyslexic group showed that two standardized tests, WSD S and OSDS were significantly correlated with all experimental processing speed tests, except linguistic stimulus verbal response task. On the other hand, normal group showed that only one standardized test, WSDS were significantly correlated with the two experimental processing speed tests, linguistic stimulus motor response task and nonlinguistic stimulus verbal response task. This finding suggests that dyslexic readers have more pervasive processing speed deficits, not localized in specific speed tasks, supporting the domain general deficits. Interestingly, this study found that in dyslexic group, the SC was not correlated with any other processing speed variable. The SC was correlated only with the standardized tests, WSDS and OSDS in normal group. This finding suggests that the SC may not be a specialized test to assess the processing speed. Indeed, the SC has more served as a measure of simple motor speed (Tun, Wingfield, & Lindfield, 1997; Wood et al. 2005). However, some researchers have argued that the SC requires cognitive processes by adding perceptual processing speed to the graphomotor element and allows a measure of cognitive processing time (Joy, Fein, & Kaplan, 2003). This study initially considered the SC as a processing speed test. But, the poor correlations between the SC and other processing speed tests do not support that the SC is an effective test for measuring cognitive processing speed. Clinical Implications The results of this study have implications concerning the use of processing s peed tasks for the diagnostic assessment of dyslexia. College students with dyslexia scored significantly lower than age matched normal readers on all diagnostic reading tests

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104 (phonological awareness, word reading, reading fluency, spelling, and timed read ing comprehension) except extra timed reading comprehension test, even though most of their standardized scores were within average ranges (see Table 3 1, timed word reading scores were in low and below average ranges). These findings indicate that dyslexi c adults are still suffering from their poor reading skills relative to normal readers, especially under timed conditions. Many studies have already argued that dyslexic readers can improve their accuracy of word recognition as they mature, but their readi ng still remains effortful and slow (Lefly & Pennington, 1991; Shaywitz, 2003; Shaywitz, Morris, & Shaywitz, 2008; Torgesen, Rashotte, & Alexander, 2001). This on the timed tasks as compared with untimed tasks. These findings suggest that processing speed should be assessed as a core component of the diagnostic evaluation for dyslexia in adult population. This study emphasizes that evidence of nonlinguistic processing s peed deficits are very informative for the diagnosis of dyslexia. Dyslexic students at college experience that their academic competence is often underestimated due to their inefficient reading. Their accurate but slow and laborious reading can be a crucia l failure factor in timed tasks such as formal examinations. The processing speed tests will provide a more direct evidence for the academic accommodations to help dyslexic students such as extra time to complete reading tasks including examinations. The main finding of this study, which processing speed deficits in dyslexic adults are domain general, will also provide a theoretical foundation to widen the range of accommodation and intervention selection, not localized in reading tasks.

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105 This study support s the development of intervention programs that focus on increasing processing speed and reading rate. Most reading interventions have been directed to treatment for phonologically based decoding problems. Methods for increasing reading speed have been oft en neglected in the instructional programs and reading rate of dyslexic readers is significantly harder than improving their phonological awareness and decoding skills. Som e interventions for facilitating reading speed have been implemented. The oldest and most commonly used method is the repeated reading Researchers have reported that various versions of single word or connected text repeated reading practices increase rea ding rate for the given material and other similar materials and contribute to comprehension improvement (Dahl, 1974; Levy, Bourassa, & Horn, 1999; Samuels, 1985; Stahl, Heubach, & Cramond, 1997; Tan & Nicholson, 1997). Fisher (1995 speed drills was des igned to develop automatic word recognition skills. Students are instructed to read lists of words quickly and correctly for 1 minute to meet grade level criteria: 30 correct words per minute (wpm) for 1 st and 2 nd grades; 40 correct wpm for 3 rd grade; 60 c orrect wpm for mid 3 rd grade; and 80 wpm for 4 th and higher grades. Campbell (1995 Great Leaps Reading Program applied 1 minute timings to three timed readings, phonics, sight phrases, and short stories. Students are required to read each page with no m ore than 2 errors. The RAVE O ( Retrieval, Automaticity, Vocabulary, Engagement with Language, Orthography ; Wolf, Miller, & Donnelly, 2000), as a more comprehensive and systematic intervention, was designed to increase both automaticity in underlying compon ential processes (i.e., visual and auditory recognition, orthographic pattern recognition, and

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106 lexical and semantic retrievals) and fluency in word attack, word identification, and comprehension. To increase reading speed, more strategies, such as choral r eading, peer/paired reading, echo reading, and tape assisted reading, have been proposed. The results of this study suggest that the increase of processing speed should be emphasized as much as the development of decoding skills in reading interventions fo r dyslexic readers. The strategies to increase processing speed may be more effective for young children because information processing speed increases rapidly through early childhood whereas it increases less rapidly during adolescence (Salthouse & Kail, 1983). Limitations and Future Research This study carried out using linguistic and nonlinguistic stimuli in the visual modality. To support the hypothesis of global processing speed deficits, linguistic and nonlinguist ic processing speed need s to be examin ed in different modalities such as auditory, temporal, or cross modalities. In this study, the sample selections were limited to college students. Additional research may need to be conduced in other adult and child samples. This study may need to be repli cated with expanding stimulus complexity. Increases in stimulus complexity may result in more depressed linguistic processing speed (rather than nonlinguistic processing speed) in dyslexic readers, suggesting the domain general processing speed deficits wi th overlap of linguistic processing weakness. Further research may need to increase the number of subjects to verify the findings of this study and consider the control of variables such as age of the sample, severity of reading problems, the nature of def icits, and prior reading ability. This study suggest s that processing speed in dyslexic children needs to be assessed to investigate the causal basis of their reading disabilities before they

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107 deteriorate reading problems. This study supports that t he scien tific exploration of the potential effects of early processing speed instruction on later reading abilities in dyslexic children. The predictive validity of processing speed in preschool children may be investigated through tasks that require rapid perform ance such as matching letters, copying letters, and producing letters under timed conditions Ongoing research, hopefully, will help understand the relationships between processing speed and reading in developmental dyslexia through the continual testing o f both dyslexics and non impaired children and adults or through the prospective follow up studies of dyslexic readers. The research design measuring both linguistic and nonlinguistic processing speed within the same dyslexic group will be useful for under standing the nature of processing speed defi cits in developmental dyslexia. Studies elucidating the contributions of processing speed to reading skills will be useful for earlier and more specific diagnosis and intervention of dyslexia.

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108 APPENDIX A RECR UITMENT FLYER Researchers: Linda J. Lombardino, PhD., Heeyoung Park, MA Location of experiment: Dauer Hall, UF Estimated duration of experiment: 2 3 hours In this study, you will be asked to name, match or identify symbols presented on a computer screen. You will also be asked to perform some vocabulary, memory, visual matching, spelling, and reading tasks. To participate in this study, you must be a native speaker of English age 18 30, with normal or corrected vision. It is also very important that you have never been exposed to the Korean alphabets. Two groups of subjects needed: Group 1 Students who have no history of difficulty with reading or spelling Group 2 Stu dents who have had reading or severe spelling difficulties since elementary school. These students may have no diagnosis or may have a diagnosis of a learning disability, reading disability, processing disability or dyslexia. screening to find out! All participants with reading disability will be given a three page brief report of their test findings if they choose to be informed o f their standardized test scores for documentation of their learning disability. or applicable courses, participants will be compensated in the form of 2 hours of research credit. ppointment with: Heeyoun g Park ( heeyoung@ufl.edu ) Reading Study heeyoung@ufl.edu (352) 273 3707 Reading Study heeyoung@ufl.edu (352) 273 3707 Reading Study heeyoung@ufl.edu (352) 273 3707u Reading Study heeyoung@ufl.edu (352) 273 3707 Reading Study heeyoung@ufl.edu (352) 273 37 07 Reading Study heeyoung@ufl.edu (352) 273 3707 Reading Study heeyoung@ufl.edu (352) 273 3707 Reading Study heeyoung@ufl.edu (352) 273 3707 Reading Study heeyoung@ufl.edu (352) 273 3707 Volunteers Needed To participate in a reading study

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109 APPENDIX B I NFORMED CONSENT LETT ER FOR PARTICIPANTS Informed Consent Letter for Participants Please read this consent document carefully before you decide to participate in this study. Protocol title Processing Speed: A Comparison of Young Adults with and without Developmental Dyslexia Purpose of the research study The purpose of this study is to examine how quickly you can name or match visual symbols and pictures. We plan to comp are results of these tasks between impaired and non impaired readers to determine whether different types of readers process familiar vs. unfamiliar symbols differently and name frequent vs. infrequent pictures differently. What you will be asked to do in the study You will be asked to complete several tasks to determine your speed of processing. In one set of tasks, you will be asked to match English or Korean letters presented on a computer screen, by verbal indication or by button press. In another set of tasks, you will simply be asked to name a series of randomly repeating pictures presented on a computer screen. With your permission, your responses to these tasks will be recorded and timed by the examiner. The audio recording will be accessible only to the research team for verification purposes and will be destroyed at the completion of the study. All other data collection will be archived for research purposes. Additionally, you will be asked to complete some standardized tests that measure processi ng speed, memory, vocabulary, sound awareness, spelling and reading skill. Tests and experimental processing speed tasks will be administered by either a principal investigator or a trained undergraduate research assistant. Time required 2 3 hours Risks and Benefits There are no known risks to the participants. All participants with reading disability will be given a three page brief report of their test findings if they choose to be informed of their standardized test scores for documentation of their learning disability. Compensation No monetary compensation is offered for participation. However, for applicable courses, participants will be compensated in the form of 2 hours of research credit.

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110 Confidentiality Your identity will be kept confidential to the extent provided by law. Your information will be assigned a code number. The list connecting your name to this number will be kept in a locked file in my faculty supervisor's office. When the study is completed and the data have been analyzed, the list will be destroyed. Your name will not be used in any report. Voluntary participation Your participation in this study is completely voluntary. There is no penalty for not participating. Right to withdraw from the study You have the right to with draw from the study at anytime without consequence. Whom to contact if you have questions about the study Principal Investigator: Linda J. Lombardino, PhD, CCC SLP, Professor Department of Special Education, School Psychology and Early Childhood Studies 336 Dauer Hall, PO Box 117420, University of Florida, Gainesville, FL, 32611 2250 Phone: 352 392 2113 (Ext 285) Whom to contact about your rights as a research participant in the study IRB02 Office, Box 112250, University of Florida, Gainesville, FL, 32 611 2250 Phone: 352 392 0433 Agreement I have read the procedure described above. I voluntarily agree to participate in the procedure and I have received a copy of this description. Participant: ___________________________________________ Date: _______ __________ Principal Investigator: __________________________________ Date: _________________

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111 APPENDIX C QUESTIONAIRE FOR M QUESTIONAIRE FORM Date Subject# Group IDENTIFYING INFORMATION 1. Name: 2. Date of Birth: 3. Age: 4. Gender: 5. Address: Street City/State Zip Code 6. Education: 7. Occupation: 8. Telephone Number: 9. E mail Ad dress:

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112 EDUCATION If yes, please indicate the following: Name of school: Year in school: Major area of study: 2. Highest degree earned: 3. Do/Did you receive any special assistance or help at school (e.g., tutoring, reading instruction, If yes, please describe in more detail. . 4. When did you begin receivi ng the assistance? . 5. Is/Was the special assistance helpful? . If yes, please explain why. . If yes, how did you do? . 8. Do you have difficulty remembering If yes, please describe in more detail. .

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113 SPEECH / LANGUAGE / READING If yes, please describe in more detail. . 2. Do you have any reading, spelling, or wr If yes, please describe in more detail. . If yes, please describe in more detail. . 4. Have you previously had your speech, langu If yes, please describe in more detail. . 5. Have you ever received any speech language therapy or remedial reading program at clinic or school? If yes, please indicate the following: When: Where : L ength and frequency of session: Primary focus of therapy: 6. H ave you ever been diagnosed with any type of learning difficulty such as (a) learning disability, (b) reading disability, (c) auditory processing disability, (d) attention deficit disorder or any other kind of problem? If yes, please indicate the following : What: When: Where: By whom: If yes, please describe in more detail. .

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114 8. How do you rate yourself in the following areas on a scale of 1 through 5? 1 = Exc ellent 2 = Good 3 = Fair 4 = Have difficulty Occasionally 5 = Have difficulty often Ability to read at a normal speed Ability to understand what you read in most instances Ability to spell accurately Ability to remember short pieces of information such as a series of numbers Ability to do simple math calculations in your head Ability to learn the pronunciation of new or long words Ability to translate thoughts in your head onto paper in an accurate and clear manner Ability to take good notes in class while the instructor is lecturing GENERAL HEALTH If yes, please describe in more detail. . If no, please describe in more detail. . 3. Do you wear glasses or co 4. How do you describe your current health? OTHER Do you have any other comments you feel might be helpful to us in planning your evaluation? .

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115 APPENDIX D WRITTEN SYMBOL DIGIT SUBSTITUTION TEST FO RM Written Symbol Digit Substitution Test Date Subject# Group SDMT Form B Time Error PRACTICE ITEMS

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116 APPENDIX E ORAL SYMBOL DIGIT SU BSTITUTION TEST FORM Oral Symbol Digit Substitution Test Date Subject# Group SDMT Form D Time Error PRACTICE ITEMS

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117 APPENDIX F SYMBOL COPY TEST FOR M Symbol Copy Test Date Subject# Group Time Error PRACTICE ITEMS

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118 APPENDIX G STIMULUS LIST OF EXP ERIMENTAL PROCESSING SPEED TESTS Stimulus List of Experimental Processing Speed Tests Linguistic Stimulus Verbal Response Test Target Stimulus Choice Stimuli Answer A d r g a q 1 2 3 4 5 4 M n b m e h 1 2 3 4 5 3 H g l b h a 1 2 3 4 5 4 D g q d a b 1 2 3 4 5 3 L l d n b h 1 2 3 4 5 1 E m r g a e 1 2 3 4 5 5 B h b d g l 1 2 3 4 5 2 N g e m n h 1 2 3 4 5 4 r R A N G B 1 2 3 4 5 1 e M D E Q L 1 2 3 4 5 3 d N G B R D 1 2 3 4 5 5 g E G H A Q 1 2 3 4 5 2 m B R N M E 1 2 3 4 5 4 n N M A B R 1 2 3 4 5 1 a A D Q B M 1 2 3 4 5 1 b R B D Q N 1 2 3 4 5 2 BQ qd bq qg qb dl 1 2 3 4 5 2 NL gl gr nb nl mb

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119 1 2 3 4 5 4 MH rh hm rd nd mh 1 2 3 4 5 5 DG dg dq br bn nb 1 2 3 4 5 1 rl RH LR HR HL RL 1 2 3 4 5 5 qm BQ QN QM MD MB 1 2 3 4 5 3 nr HN NH NQ NR QB 1 2 3 4 5 4 hd HB HD DN DH ND 1 2 3 4 5 2 Qg qB bR rB gR qG 1 2 3 4 5 5 Gh gH hG gB qH hQ 1 2 3 4 5 1 Bh hB dB bH dH mL 1 2 3 4 5 3 Nb bN nB qM mQ mB 1 2 3 4 5 2 dQ Bh Hd Db Hb Dq 1 2 3 4 5 5 hN Gn Gm Hn Nh Hg 1 2 3 4 5 3 mD Nq Dn Mb Md Dm 1 2 3 4 5 4 gB Gb Qh Hq Gd Bq 1 2 3 4 5 1 MLH hlm qml mql mlq mlh 1 2 3 4 5 5 QRL rlg qlr qrl rqn rlq 1 2 3 4 5 3 BGr bgR brG grD gdR rdG 1 2 3 4 5 1 DMn ndM dmN dnM bmN mbL 1 2 3 4 5 2 RbH rHd dRh rBd hBd rBh 1 2 3 4 5 5 GdN bNg bGn gDn gBn nBg 1 2 3 4 5 3 Hdm bHM hMD hDM dHM hMB 1 2 3 4 5 3

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120 Qrg gQR qGR gRQ qRG rQG 1 2 3 4 5 4 gml GLM GMH MLG MHL GML 1 2 3 4 5 5 dlr DLR DRG NRL LNR NLR 1 2 3 4 5 1 qmN NMg NMh QMn QNm QNb 1 2 3 4 5 3 bdG BHr BDg RHb HRb BRh 1 2 3 4 5 2 dBq RdQ RqB RqD DqB DbQ 1 2 3 4 5 5 rDn RnD NgR NrG RdN DnR 1 2 3 4 5 4 mQG Gdq Mqg Mgq Gqd Dqm 1 2 3 4 5 2 nGH Mgh Ghn Nhg Ngh Mhg 1 2 3 4 5 4 Linguistic Stimulus Motor Res ponse Test Target Stimulus Choice Stimuli Answer R d r g a q 2 N n b m e h 1 A g l b h a 5 Q g q d a b 2 B l d n b h 4 M m r g a e 1 L h b d g l 5 E g e m n h 2 n R A N G B 3 q M D E Q L 4 g N G B R D 2 e E G H A Q 1 r B R N M E 2 a N M A B R 3 m A D Q B M 5 d R B D Q N 3 QB qd bq qg qb dl 4 GL gl gr nb nl mb 1 RD rh hm rd nd mh 3 BN dg dq br bn nb 4 hl RH LR HR HL RL 4

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121 mb BQ QN QM MD MB 5 nh HN NH NQ NR QB 2 dn HB HD DN DH ND 3 Rb qB bR rB gR qG 3 Hq gH hG gB qH hQ 5 Dh hB dB bH dH mL 4 Mq bN nB qM mQ mB 4 hB Bh Hd Db Hb Dq 4 gN Gn Gm Hn Nh Hg 1 nQ Nq Dn Mb Md Dm 1 qH Gb Qh Hq Gd Bq 2 MQL hlm qml mql mlq mlh 3 RLQ rlg qlr qrl rqn rlq 5 GRd bgR brG grD gdR rdG 3 DNm ndM dmN dnM bmN mbL 3 RhD rHd dRh rBd hBd rBh 1 BgN bN g bGn gDn gBn nBg 2 Hmb bHM hMD hDM dHM hMB 5 Gqr gQR qGR gRQ qRG rQG 1 mhl GLM GMH MLG MHL GML 4 nlr DLR DRG NRL LNR NLR 5 nmH NMg NMh QMn QNm QNb 2 bhR BHr BDg RHb HRb BRh 1 rQb RdQ RqB RqD DqB DbQ 2 nRg RnD NgR NrG RdN DnR 3 gDQ Gdq Mqg Mgq Gqd Dqm 1 mHG Mgh Ghn Nhg Ngh Mhg 5 Nonlinguistic Stimulus Verbal Response Test Target Stimulus Choice Stimuli Answer 1 2 3 4 5 4 1 2 3 4 5 3 1 2 3 4 5 4 1 2 3 4 5 3 1 2 3 4 5 1 1 2 3 4 5 5

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122 1 2 3 4 5 2 1 2 3 4 5 4 1 2 3 4 5 1 1 2 3 4 5 3 1 2 3 4 5 5 1 2 3 4 5 2 1 2 3 4 5 4 1 2 3 4 5 1 1 2 3 4 5 1 1 2 3 4 5 2 1 2 3 4 5 2 1 2 3 4 5 4 1 2 3 4 5 5 1 2 3 4 5 1 1 2 3 4 5 5 1 2 3 4 5 3 1 2 3 4 5 4 1 2 3 4 5 2 1 2 3 4 5 5 1 2 3 4 5 1 1 2 3 4 5 3

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123 1 2 3 4 5 2 1 2 3 4 5 5 1 2 3 4 5 3 1 2 3 4 5 4 1 2 3 4 5 1 1 2 3 4 5 5 1 2 3 4 5 3 1 2 3 4 5 1 1 2 3 4 5 2 1 2 3 4 5 5 1 2 3 4 5 3 1 2 3 4 5 3 1 2 3 4 5 4 1 2 3 4 5 5 1 2 3 4 5 1 1 2 3 4 5 3 1 2 3 4 5 2 1 2 3 4 5 5 1 2 3 4 5 4 1 2 3 4 5 2 1 2 3 4 5 4

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124 Nonlinguistic Stimulus Motor Response Test Target Stimulus Choice Stimuli Answer 2 1 5 2 4 1 5 2 3 4 2 1 2 3 5 3 4 1 3 4 4 5 2 3 3 5 4 4 4 1 1 2 3 5 3 3 1 2 5 1

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125 4 5 2 1 2 3 1 5

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126 LIST OF REFERENCES Ackerman, P. T., & Dykman, R. A. (1993). Phonological processes immediate memory, and confrontational naming in dyslexia Journal of Learning Disabilities 26 597 609. Adams, M. (1990). Beginning to read: Thinking and learning about print Cambridge, MA: MIT. Press. Adlard, A., & Hazan, V. (1998). Speech perception in children with specific reading difficulties (dyslexia). The Quarterly Journal of Experimental Psychology 51 A, 153 177. Allington, R. L. (1983). Fluency: The neglected reading goal in reading instruction. The Reading Teacher 36 556 561. Amitay, S., Ah issar, M., & Nelken, I. (2002). Auditory processing deficits in reading disabled adults. Journal of the Association for Research in Otolaryngology 3 (3), 302 320. Amitay, S., Ben Yehudah, G., Banai, K., & Ahissar, M. (2002). Disabled readers suffer from vi sual and auditory impairments but not from a specific magnocellular deficit. Brain 125 2272 2285. Badcock, D. R & Lovegrove, W. (1981) The effect of contrast, stimulus duration and spatial frequency on visible persistence in normal and specifically di sabled readers. Journal of experimental psychology Human perception and performance 7 495 505. Badian, N. A. (1995). Predicting reading ability over the long term: The changing roles of letter naming, phonological awareness and orthographic processing. A nnals of Dyslexia 45 79 96. Badian, N. A. (1996). Dyslexia: A validation of the concept at two age levels. Journal of Learning Disabilities 29 (1), 102 112. Badzakova Trajkova, G., Hamm, J. P., & Waldie, K. E. (2005). The effects of redundant stimuli on visuospatial processing in developmental dyslexia. Neuropsychologia 43 473 478. Baro, J. A., Garzia, R. P., & Lehmkuhle, S. (1996). Visual evoked potentials in reading disability. In R. P. Garzia (Ed.), Vision and reading (pp. 193 207). St. Louis: Mosby. Beaton, A. A. (1997). The relation of planum temporale asymmetry and morphology of the corpus callosum to handedness, gender and dyslexia: A review of the evidence. Brain and Language 60 255 322.

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127 Beaton, A. A. Edwards, R., & Peggie, A. (2005). Dyslexia and across hands finger localisation deficits. Neuropsychologia 44 326 334. Beitchman, J. H., & Young, A. R. (1997). Learning disorders with a special emphasis on reading disorders: A review of the past 10 years. Journal of the American Academy of Child and Adolescent Psychiatry 36 1020 1032. Berninger, V., Abbott, R., Billingsley, F., & Nagy, W. (2001). Process underlying timing and fluency of reading:efficiency, automaticity, coordination, and morphological awareness. In M. Wolf (Ed.) Dyslexia, flue ncy and the brain. Timonium, MD: York Press. Bjaalid, I. K., Hoien, T., & Lundberg, I. (1993). Letter identification and lateral masking in dyslexic and normal readers. Scandinavian Journal of Educational Research 37 151 161. Boden, C., & Brodeur, D. A. (1999). Visual processing of verbal and non verbal stimuli in adolescents with learning disabilities. Journal of Learning Disabilities 32 58 71. Bonifacci, P., & Snowling, M. J. (2008). Speed of processing and reading disability: A cross linguistic inves tigation of dyslexia and borderline intellectual functioning. Cognition 107 997 1017. Bowers, P. G. (1989). Naming speed and phonological awareness: Independent contributors to reading d isabilities. In S. McCormick & J. Zutell (Eds.) Cognitive and s ocia l perspectives for l iteracy research and instruction: 38th yearbook of the N ational R eading C onference Chicago: National Reading Conference, Inc. Bowers, P. G., & Wolf, M. (1993). Theoretical links among naming speed, precise timing mechanisms and orthogr aphic skill in dyslexia. Reading and Writing: An Interdisciplinary Journal 5 (1), 69 85. Bowers, P. G., Steffi, R. A., & Tate, E. (1988). Comparison of the effects of IQ control methods on memory and naming speed predictors of reading disability. Reading R esearch Quarterly 23 304 319. Bowey, J. A., Storey, T., & Ferguson, A. (2004). The association between continuous naming speed and word reading skill in fourth to sixth grade children. Australian Journal of Psychology 56 155 163. Box, G. E. P. (1954). Some theorems on quadratic forms applied in the analysis of variance: II. Effects of inequality of variance and correlation between errors in the two way classification. Annals of Mathematical Statistics 25 484 498. Bradley, L., & Bryant, P. E. (1983). C ategorizing sounds and learning to read: A causal connection. Nature 301 419 21.

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128 Breier, J. I., Gray, L. C., Fletcher, J. M., Foorman, B., & Klaas, P. (2002). Perception of speech and nonspeech stimuli by children with and without reading disability and attention deficit disorder. Journal of Experimental Child Psychology 82 226 250. Breitmeyer, B. G. (1993) Sustained (P) and transient (M) channels in vision: a review and implications for reading. In D.M. Willows, R.S. Kruk, & E. Corcos (Eds.), Visual p rocesses in reading and reading disabilities (pp. 95 110). Hillsdale, NJ: Erlbaum. Breznitz, Z. (2002). Asynchrony of visual orthographic and auditory phonological word recognition processes: An underlying factor in dyslexia. Reading and Writing 15 (1 2), 15 42. Breznitz, Z. (2003b). Speed of phonological and orthographic processing as factors in dyslexia: Electrophysiological evidence. Genetic, Social and General Psychology Monographs 129 (2), 183 206. Breznitz, Z. (2006). Fluency in reading: Synchronizat ion of processes Mahwah, NJ: Lawrence Erlbaum. Breznitz, Z., & Misra, M. (2003). Speed of processing of the visual orthographic and to word recognition deficits. Brain and L anguage 85 (3), 486 502. Brown, J. I., Fishco, V. V., & Hanna, G. (1993). The Nelson Denny reading test, NDRT Itasca, IL: The Riverside Publishing Company. Brown, W. E., Eliez, S., Menon, V., Rumsey, J. M., White, C. D., & Reiss, A. L. (2001). Preliminary evidence of widespread morphological variations of the brain in dyslexia. Neurology 56 781 783. Bruck, M. (1990). Word recognition skills of adults with childhood diagnoses of dyslexia. Developmental Psychology 26 439 454. Bruck, M. (1992). Persistenc e of dyslexics' phonological awareness deficits. Developmental Psychology 28 (5), 874 886. Bruck, M. (1993). Word recognition and component phonological processing skills of adults with childhood diagnosis of dyslexia. Developmental Review 13 (3) 258 268. Bruck, M., & Waters, G. S. (1990). An analysis of the component spelling and reading skills of good readers good spellers, good readers poor spellers, and poor readers poor spellers. In T. H. Carr & B. A. Levy (Eds.), Reading and its development: Compone nt skills approaches (pp. 161 206). San Diego: Academic Press.

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147 BIOGRAPHICAL SKETCH Heeyoung Park was born and raised in Busan, South Korea. She graduated Magna Cum Laude from the Daegu University in 2000 with a Bachelor of Science degree in speech language p athology and a minor in rehabilitation p sychology. She worked as a speech l anguage pathologist for three and a half years in South Korea S he e isorders at the University of Florida in 2004 and completed her Maste r of Arts degree in 2006 She began her doctoral studies in communication sciences and d isorders at the University of Florida in 2007 with an interdisciplinary focus on developmental reading disorders. She received her Ph.D. from the University of Florida in the summer of 2011.