Jpn. J. (6),

The Japanese Association of Special Education

NII-Electronic Library Service

The JapaneseAssociation of Special Education

Jpn. J. Spec. Educ., 45 (6), 383-404, 2008.

invited PaPerCurrent Topic

The Multiple Systems Model of Reading:Understanding Reading Disabilities andTheir Effect on Academic Achievement

Across Individuals and Orthographies

Rauno PARRILA

The present paper contends that for a fu11 understanding of reading develop-ment and disabilities, both within and across languages, a better meta-theoretical

framework is needed in order to guide research and interpret research findings

so that they can be applied to educational practice. The framework presented,called the

`Cmultipic systems model of reading'], views development as contingent

cycles of construction and reconstruction that developmental resources at various

levels of functioning (genetic, neural, psychological, behavioral, and environmen-

tal) contribute to. The model makes two key assumptions: (a) reading abilities are

continuously distributed, and (b) the developmental process has distributedcontrol; every observed outcome is jointEy determined by multiple factors, includ-ing the developing organism itself. Ramifications of these assumptions for both

research and educational practice are discussed. Educational practicc is well

served by respecting the complex, and sometimes idiosyncratic, nature of' the

developing organism, and by not a]locating causal responsibility, or all the

remedial eflbrts, of possible reading problems to any single cause.

Key Werds: reading disabilities, dyslexia, multiple system modcl, core deficit

Introduction

Reading disabilities in general and developmental dyslexia in particular are

conceptualized and assessed variably both within and across linguistic contexts,

leading to both definitional and 'theoretical

cenfusion. The present article proposesthat a theoretical framework is needed that encompasses multiple Ievels of function-

ing, in order to enhanee the knowledge of why individuals (both within and across

linguistic contexts) fail to develop suMcient word-reading or text-level reading skMs,

and how such skills are related to each other and to academic outcomes. Specifically,

to understand probabilistic relationships between possible cognitive deficits, word-

and text-level reading problems, and difflirent academic and remedial outcomes,

University of Nberta

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R. Parrila

rnodels adhering to the principles of developmental systems theory (DST; e.g.,

Oyama, GriMths, & Gray, 2001) provide better meta-theoretieal frameworks than any

single (or dual) core deficit model that is currently relied on. One such model, the

Multiple Systems Model of Reading (MSMR), will be presented.

In what foIIows, shortcomings ot' theories of reading disabilities, mainly of

dyslexia, wil1 be discussed, after which devclopmental systems theory and the

Multiple Systerns Model of Reading will be presented. Seme recent studies guided bythe Multiple Systems Model of Reading wM be described, and its educational

implications wM be discussed.

Theories of Reading Disabilities

A great deal of research on children and adults with. reading disabilities has

focused on identifying the source or corc deficit of the reading disability on the

cognitive Ievel of analysis. The majority of these studies have fbcused on English-

speaking individuals with word-level reading problems, or dyslexia, and have aimedat verifying or refuting the existence of some qualitative difi'erences between the

individuals who are dyslexic and control groups.

For the large part, studies with individuals who are developmental dyslexics (asopposed to neuropsychological studies with peop}e who are acquired dyslexics) have

been guided by single-factor theeries, most of which posit a specific impairment in the

ability to manipuiate, retrieve, and/or store phonological information as the cognitive

level core deficit responsible for poor reading (e.g., Frith, 1999; Ramus & Szenkovits,

2008; Snowling, 2001). When other explanatory constructs have been examined, their

purpose has been either to provide a neuroLogical and/or perceptual level explanation

for the cognitive level phonological deficits (e.g., Ahissar, 2007; Goswami, Thomson,

Richardson, Stainthorp, Hughes, Rosen, & Scott, 2002; Nicolson & Fawcett, l990;

Tallal, Miller, Jenkins, & Merzenich, 1997) or to provide an alternative explanation

for the performance of a subgroup of individuals who are dyslexic whose deficits may

not involve, or are not limited to, phonologica] tasks (e.g., Badian, 1997; Bosse,

Tainturier, ･& Valdois, 2007; Ho, Chan, Tsang, & Lee, 2002; Wolf & Bowers, 1999).

For example, researchers have reported that many, but not all, individuals who

are dyslexic perform poorly on rapid naming (e.g., Ho, Chan, Lee, Tsang, & Luan,

2004} Miller-Shaul, 2005) and orthographic processing tasks (e.g,, Badian, 1997; Ho

et aL, 2004; Meyler & Breznitz, 2003), and have problems proccssing visual infbrma-

tion using the magnocellular pathway (e,g,, Buchholz & McKone, 2e04). Other

researchers have reported that at least some individuals with dyslexia show depressed

levels of perlbrmance in diflbrent auditory processing (e.g., King, Lombardino,

Crandell, & Leonard, 2003) and visual attcntion span tasks (Bosse et al., 2007),experience mQtor-coordination (e.g., Rack, 1997) and implicit learning (e.g., Howard,Howard, Japikse, & Eden, 2006) difficulties, and report high levels of visual stress

(e.g., Singleton & Trotter, 2005).

Without going into detail on how plausible any of' these cleficits is as the core

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Understanding Reading Disabilities

deficit (see, e.g., Ramus, Rosen, Dakin, Day, Castellote, White, & Frith, 2003; Ramus,2006), or how reliably each has been linked to reading outcomes Csee, e.g., Ahissar,

2007), existing studies sufler from notable methodological and theoretical problems,in the opinion of the present author. Methodologically, most studies on develop-

mental dyslexia have sulfered from (a) relatively srnall and heterogeneous samples

(e.g., Joanisse, Manis, Keating & Seidenberg, 2000; Reid, Szczerbinski, Iskierka-

Kasperek, & Hansen, 2007), (b) inconsistent sample selection proccdures (e.g.,compare Leikin & Zur-Hagit, 20e6, and Szenkovits & Ramus, 2005), (c) selection

procedures that have included aspects of the examined cause ln thern (e.g., use of

spelling and word attack scores as selection criteria and then examining phonologicalawareness), (d) variabLe measures of purportedly the same constructs (e.g., timed and

untimed mcasures of phonological awareness), (e) poor or nonexistent control of

potential confounding lactors (e.g., Giraudo, 2001), and (fi inconsistent selection

criterion fbr comparison groups (compare, e.g., Egan & Pring, 2004, and Bosse et al.,

2007; see also Goswami, 20e3, for a further discussion of methodological issues),

In addition, the theoretical assumption of qualitative rather than quantitativedifferences has led to simplistic study designs (group comparisons with small sample

sizes assuming, rather than examining, within-group homogeneity) and data analysis

methods, Even when more than one construct has been examined and individual

level data presented (e,g., Parrila, Georgiou, & Corkett, 2007; Rack, 1997; Ramus et

al,, 20e3), each of them has been explored separately without relating as much as the

number of deficient areas to observed reading levels (see Birch & Chase, 2004;Kinsbourne, Rufo, Gamzu, Palmer, & Berliner, I991, fbr notable exceptions). No

published study that we could find has exarnined, fbr example, the possibility that

several subclinical cognitive deficits may jointly produce a clinically significant

reading deficit. Contrary to what has been suggested (see, e,g., Vellutino, Scanlon, &

Tanzman, 1991), such alternatives are not ruled out simply by adopting IQ as an

exclusionary criterion for reading disabilities.

Theoretically, the assumption that developmental disorders, such as develop-mental dyslexia or specific reading comprehcnsion deficit, can have a single cau,se at

any !eve! of analysis has been challenged recently by multifactorial etiological models

(e.g., Gottlieb & Halpern, 2002; Pennington, 2006; see, however, Morton, 2004, and

Ramus, 2006, fbr multifactQrial etiological models that assume a single cognitive level

eause), Pennington (2006) argues that probabilistic multiple deficit models are needed

to providc realistic accounts of developmental disorders and the nondeterministic

relationship between disorders and their causes. He suggests further that such modcls

have to include (a) both protec:tive and risk factors, (b) multiple levels of analysis (hisown general model includes etiologic (with both genetic and environmental i'actors),

neural, cogni,tive, and behaviora] levels), (c) bidirectional connections between con-

structs within each level, and Cd) bidirectional connections between the levcls to

account for interactions between protective and risk factors functioning at diflerent

levcls ot' analysis (see also Ferd & Lernct', 1992; Gottlieb, 1983, 1997; Gottlieb,

Wahlsten, & Lickliter, 2006).

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R. Parrila

I propose here that to understand the probabilistic relationships between

possible cognitive deficits, word- and text-level reading problems, and diflerent

academic and remedial outcomes, models adhering to the prineiples of developmental

systems theory (DST; e.g., Oyama et al., 2001) provide better meta-theoretical

frameworks than any single (or dual) core deficit model. In general, developmental

systems theory views development as contingent-but more or less reliable-cycles of

construction and reconstruction that dif{erent developmental resources contribute to.

One of the key underlying assumptions is that the developmentai process has

distributed control; every observed outcome is jointly determined by multiple factors,

or interactants, including the developing organism itself, Implicit in this assumption

is the important idea that the significance of any particular factor is dependent upon

the state of the rest of the system, thus making it necessary to consider other risk and

protective factors as well as changes in importance of diff'erent factors both over time

and across contexts.

The Multiple Systems Model of Reading

Based on developmental systems theory and earlier work by Gottlieb (198S),Frith (1999, 2002) and Pennington (2006), my associates and I have been developing

a probabilistic multiple systems model of reading (MSMR) to guide our research

efforts. This rnodel aims to understand reading development and disabilities across

the life span in diflerent orthographies (see, e.g., Georgiou, Parrila, & Liao, in press;Georgiou, Parrila, & Papadopoulos, in press; Kirby, Silvestri, Alligham, Parrila, & La

Fave, 2008; Liao, Georgiou, & Parrila, in press; Parrila et aL, 2007; Stephenson,Parrila, Georgiou, & Kirby, 2008). The full model, depicted in Fig. 1, assumes

bidirectional influences between five levels of analysis or systems-genetic, neural,

psychological, behavioural, and environmental-and several functionally identifiable

subsystems in each Ievel (see, e.g., Gottlieb et aL, 20e6, and Oyarna et al., 2001, for

related models). The present article will explicate some specific connections betweep

risk and protective factors both betwcen and within the behavioral, psychological,and environmental systems, including the language that the individual is learning toread. Note that the assignment of factors (or "interactants")

to any levels, systems,

and categories is always arbitrary and exemplifies only one possible assignment

among many, The one used here was chosen only to promote discussion, not to irnply

any fundamental ontological dichetomies. An alternative depiction of the simplified

three-level multiple systems model is shown in Fig. 2,

The three-level Multiple Systems Model of Reading makes several assumptions

derived from the principles ef developmental systems theory (Oyama et al., 2001),Frith (1999), Penning'ton (2006), and from continuous abilities theories of reading

(e.g., Olson & Gayan, 2001; Shaywitz, Escobar, Shaywitz, Fletcher, & Makuch, 1992;

Stanovich, 1988; Vellutino et al., 1991) that also have rejected the validity oS"

qualitative difi'erences between readers of difi'erent abilities. These assumptions

include:

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The JapaneseAssociation ofSpecial Education

Understanding ReadingDisabilities

(I) Any system or subsystem (e.g., cognitive risk and protective factors) can be the

focus of study by itself, but full expianations of reading and acadcmic out-

comes require simultaneous consideration of multiple risk and protective

fhctors operating at more than one level of analysis (for example, the eflect of

cognitive factors on reading is mediated by environmental factors, such as

language, e.g., Georgiou, Parrila, & Papadopoulos, in press, and instructional

methods, see, e.g., IJanderl, 2000; Papadopoulos, 2001);

(2) Distributions of risk factors, protective factors, and reading outcomes are

continuous (see, e.g,, Olson & Gayan, 2001; Shaywitz et aL, 1992; Stanovich,

Main Leve]s efActivit},

Environmcnt

Behaviour

Psychelogical

Neural

GcnctLc

BidiTectionalInfiuences

.

FIG.

Individual Development

1 Schematic Representation of the Diflerent Levels of Analysis

Multiple Systems Model of' Reading (Modified From Gottlieb,in

the1992)

Behaviour(actiens,interaction$it)

wa..

,

Environment(physicai,secial,cultural)

di k .i u,.

! }'t

/ x 1,,

g F

.,K.

)'/pa Vif./.g/><hlll."k

,/

l'.{･'fg.v.!a.f･.//･ `esM-um-ma----cpt [Eii.i.E:Etl･:'illFIG. 2 Three-Levcl Multiple Systems

-

Reading &academic

outcomes

Model of Reading

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R, Parrila

1988), and any decision of' when the pertbrmance is regarded as clinically

depressed, subclinically depressed, or not depressed is necessarily arbitrary;

(S) Connections between risk factors, protective factors, and reading outcomes are

bidireetional (for example, protective factor motivation to read results in a high

level ofprint exposure which then leads to better reading skills and, further, to

higher motivationl see, e.g., Fink, 1998);

(4) Connections between risk t'actors, protective factors, and reading outcomes are

probabilistic rather than deterministic. No single risk factor is 1ikely a sufiicient

or necessary cause for a reading disability, and the presence of multiple risk

l'actors (in the same or difi'erent systems) may be necessary for reading

disability to occur (see also Pennington, 2006);

(5) In the absence of protective factors within a system (for example, strong

orthographic or semantic skills moderating the eff'ect of poorer phonological

skills on word reading) or in other systems (for exampie, strong motivation to

succeed moderating the effect of slow text reading rate), the effbct of any risk

factor or a combination of risk factors is accentuated;

(6) Conneetions between risk faetors, protective factors, and reading and academic

outcomcs are not equally weighted across individuals or languages (fbr exam-

ple, the role of phonological deficit is not equal across languages; compare Ho

et al., 2e02; Lyytinen, Aro, Eklund, Erskine, Guttorm, Laakso, Leppanen,

Lyytinen, Poikkou, & Richardson, 2004; and Morris, Stuebing, FIetcher,

Shaywitz, Lyon, Shankweiler, Katz, Francis, & Shaywitz, l998), or across

developmental periods (e.g,, Parrila, Kirby, & McQuarrie, 2004).

According to this conceptualization, reading disabilities may result (but do not

necessarily result) from a spccific deficiency in a particular reading-related cognitive

ability Csuch as representation, e.g., Snowling, 2000, or processing, e.g., Ramus &

Szenkovits, 2008, of phonological information), as qualitative diflerence theories

would predict. Note, however, that thc impact of a phonological deficit is probabilisticand depends upon the state of the rest of the system, such as the presence or absence

of other risk and protective factors, the language being learned, and the instructional

methods employed, In addition, a reading disability can result from a lcss than

adcquatc mix of diflerent cegnitivc abilities (as quantitative differencc, continuous

abilities theories of reading disability would predict), or from a suboptimal interaction

between the cognitive subsystem, other psychological subsystems, and the environ-

mental system (see also, Frith, 2002).

The distribution of weights, however, is not assumed to be equal within and

between systems, or across developrnental periods, languages, or individuals. For

example, the existing evidence suggests that for cxplaining a word reading deficit in

a population of elementary school students receiving generally effective instruction

(such as synthetic phonics if they are learning an alphabetic language), the psycholog-ical system carries more weight than any other system, and within the psychologicalsystem, the cognitive subsystem and phonological processing are more importantfactors than, say, general intelligence, motivation, or attention (see reviews in Adams,

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Undcrstamding Reading Disabilities

1990; Vellutino, Fletcher, Snowling, 8t Scanlon, 2004). However, the samc weighting

may not be optimal or even appropriate tbr elementary school students learning toread Chinese (e,g., McBride-Chang, Shu, Zhou, Wat, & Wagner, 2003; Shu,

McBride-Chang, Wu, & Liu, 2006) or Greek Ce,g., Georgiou, Parrila, &

Papadopoulos, in press), or tbr older students whose phonological skills have reached

a plateau but whose reading skills may continue to develop (e.g., Andreassen,

Knivbcrg, & Niemi, 2006).

Research Implications

The multiple systems model of reading is best viewed as a meta-theory that can

guide creation of more specific theories, research designs, and firameworks fbr

planning and implementing educational programming. One immediate research

ramification that the Multiple Systems Model of Reading has is that the assumption

of universality ol' any theoretical explanation is a working hypothesis at best and

requires verification across contexts (for example, across diffttrent languages, or in

empirical studies that involve factors frorn several systems). A second ramification is,

as stated above in assumption (1), that studies should attcmpt to include predictorsfrom diflerent systems and subsystems in order to understand better how these jointlycontribute to the development of any particular target skM. When trying to under-

stand the performance of individuals with learning disabilities, it may be particularlyimportant to examine both protcctive and risk factors to account better for the

probabilistic relationship bctween what is frequently regarded as the core deficits and

the academic outcomes they are expected to aflect.

Recent studies in my laboratory on predictors of reading development have been

guided by the Multiple Systems Model of Reading. For example, my associates and

I (Stephenson ct al., 2008) recently reported a iongitudinal study that examincd how

home litcracy (shared book reading, parent teaching activities, and books in the

home), parents' belief's in and expectations of their children's reading and academic

abi].ity, and children's task-focused behavior during everyday learning situations were

associated with the dcveloprnent ef two emergent literacy skills phonological sensi-

tivity and letter knowledge in kindergarten and of word reading in both kindergar-

ten and first grade. There is substantial evidence that at least somc aspects of each

of these i'actors contribute to reading development (see, e.g., Aunola, Nurmi, Niemi,Lerkkanen, & Rasku-Puttonen, 2002; Bus, van IJzendoorn, & Pellegrini, 1995; de

Jong & van der Leij, 1999; Entwisle & Hayduk, 1988; Kirby, Parrila, & Pfeiflbr, 2003;Parrila et al., 2004), thus making them good candidates for interactants in the reading

acquisition process. However, most existing studies have focused on onc or the other

of them and, as a result, there is little understanding of the joint contributions that

the different environmental and psychological subsystems makc to successfu1 reading

acquisition. The results from my }aboratory show that parents' teaching activities at

home prior to kindergarten (but not shared book reading), parents' beliefs about their

children's reading ability, and children;s task-focused behavior were signilicant

389 --




R. Parrila

predictors of at least seme early literacy skMs, but also that much of the eflect that

these variables have on early word reading skills is mediated by two highly correlated

emergent literacy skills, phonological awareness and letter knowledge. These results

suggest that the cumulative developmental cycle between task-focused behavior,

parents' expectations and literacy practices, and difEerent literacy and cognitive skMs

likely starts years before children enter into any kind of formal educational environ-

ment. We argue that a better understanding of relationships between diffbrentenvironmental factors, children's task-focused behavior, and emergent literacy skills

is necessary for a more comprehensive theory of reading acquisition.

In a related study, my associates and I (Manolitsis, Georgiou, Stephenson, &

Parrila, 2008) exarnined whether the relationship between parents' home literacy

instruction and childrenis performance is moderated by the language children are

learning to read. We chose two alphabetic languages, English and Greek, that differ

greatly in the consistency of their grapheme-phoneme correspondences and, subse-

quently, on the demands they impose on the first grade learner. Learning to read

Greek poses only a moderate challenge (see, e.g., Ellis, Natsurne, Stavropoulou,Hoxhallari, van Daal, Polyzoe, Tsipe, & Petalas, 2004; Seymour, Aro, & Erskine,2003), and we speculated that this alone might aflbct the frequency and nature of

home literacy activities that parents engage in with their children, In general, our

findings indicated that the Greek parents reported doing home literacy activities less

oftcn with their children than did the Canadian (English-speaking) parents, and the

Greek children did poorer in tasks measuring emergent literacy skills in kindergartenthan the English-speaking Canadian chitdren.

However, the most interesting finding was that for the Greek children, the

firequency of home literacy activities was negatively correlated with phonologicalawareness, whereas the opposite was true for the Canadian children learning to read

English. We suspect that the explanation for this counterintuitive (at least tbr thoseof us who work in North America) finding is that Greek parents, in general, do not

believe that what they do at home wM have much impact on how easily their children

learn to read (and most Greek children did indeed learn to read in first grade with

no problems) and they only get actively involved when they have a specific reason to

expect diMculties (see Silinskas, Leppanen, Aunola, Parrila, & Nurmi, 2008, fbr

similar results with children who were Iearning to read another highly consistent

orthography, Finnish).

In a separate series of studies, we have been examining the moderating role of

orthography to how speeific cognitive subsysterns are related to reading, The theoreti-

cal impetus for these studies has been the idea that carefu11y selected cross-linguistic

comparisons often provide excellent contrasts for testing different theoretical accountsof reading acquisition, because languages vary in critical aspects, such as size of the

optimal decoding unit (see also Ziegler & Goswami, 2005), orthographic consistency

and transparency, and morphological complexity.

Liao et al. (in press) examined the relationship between rapid naming speed

(RAN) and Chinese character recognition accuracy and fiuency. This study was

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Understanding Reading Disabllities

motivated by reports that rapid naming speed tasks may predict Chinese character

recognition better than they predict English word recognition, and that as a functionof increased reading sk-, the relationship between rapid naming speed and reading

becomes stronger in Chinese (see, e.g., Tan, Spinks, Eden, Perfetti, & Siok, 2005), a

result that challenges most theoretical accounts of the rapid naming speed-reading

relationship developed to explain the performancc patterns observed when children

are learning to read English. The Tesults of Liao et al. (in press) indicated that while

some of the relations observed between rapid naming speed tasks and reading in

English were replicated in Chinese (for example, graphological rapid naming speed

tasks were better predictors of reading than non-graphological rapid naming speed

tasks), others were not, More specifically, similar to Tan et al. (2005), Liao et al. (inpress) found that the importance of rapid naming speed increased from second to

fourth gradc, evcn aftcr controlling for age, nonverbal intelligence, phonologicalsensitivity, short-term memory, and orthographic processing.

In an extension of the Liao et aL (in press) study, Georgiou, Parrila, and Liao

(in press) showed that when the dependent variable (either an accuracy or a fluencymeasure) was comparable across languages, there were no statistically significant

diffbrences in the correlations between rapid naming speed and reading in fourth

grade students, across three orthographies: English, Greek, and Chincse.

However, the results also indicated that diflbrent components of the rapid

naming speed tasks may be responsible for the rapid naming speed-reading relation-

ship across languages. More specifically, while pause time (the average time between

two articulations in the series) was a less important predictor of word reading than

articulation time (the average time to say the names ot' the stimuli) in English and

Grcek, the oppesite was true fbr orthographically less transparent Chinese, This result

raises the possibility that what underlies the rapid naming speed-reading relationship

may vary across languages.

Thus, when rapid naming speed is fiagged as an important indicator of reading

difliculties in different languages (see, e.g., Ho et al., 2004, in Chinese, and Torppa,

Tolvanen, Poikkeus, Eklund, Lerkkanen, Leskinen, & Lyytinen, 2007, in Finnish, and

Badian, DuffY, Als, & McAnulty, 1991, in English), it is possible that the underlying

cognitive deficits and how they impact reading are very diflbrent across those

languages. An interesting possibility that fo11ows from this reasoning is that rapid

naming speed may be related differently to the different writing systems used in

Japanese. One prediction from the above studies is that the rapid naming speed-kana

reading relationship would likely resemble that observed in alphabetic orthographies

(and be based more on articulation speed with older readers, but not necessarily with

younger readers, see, e.g,, Georgiou, Parrila, & Kirby, 2006), whereas the rapid

naming speed-kanji relationship would likely resemble that observed in Chinese (andwould likely be based more on lexical access speed),

Currently, we are expanding the Multiple Systems Model of Reading research to

examine which interactants play a role in determining the academic outcomes of

adults with learning disabilities. This line of research was initialIy motivated by the

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R. Parrila

observations (e.g., Jackson, 2005) that in post-secondary students, reading skills and

academic outcomes are not highly correlated, and that studcnts who are successfu1 in

their post-secondary studies can have very deficient basic reading skills (Parrila et al.,

2007). Existing studies of post-secondary students with learning disabilities, most of

which were done with very small and non-representative samp!es, suggest that

protective factors include use of good study and learning strategies, good motivation

and attitude towards the teaching/learning process, good interpersona] skills, being

perslstent and goal-oriented, and having environmental aceommodations, such as

lighter course' loads (e.g., Corkett et al., 2008; Corkett et al., 2006; Keim et al,, 1996;

Kirby et al., 2008; Reis, McGuire, & Neu, 2000; Ruban, McCoach, McGuire, & Reis,

2003; Vogei & Adelman, 1992), Vogel and Adelman (1990), in turn, suggest that poormotivation, poor attitude, substance abuse, dcnial erlearning disability, and unrealis-

tic expectations are risk lactors for university students with LD.

While very few of these studies have specifically fbcused on post-seeondarystudcnts with reading disabilities, it seems reasonable to assume that (a) there is

significant heterogeneity in the reading disabled population in behavioral, psychologi-cal, and environmental systems, (b) dilfercnt combinations of risk and protectivelactors can be associated with similar academic outcomes, both successful and

unsuccessfu1, and (c) both the deployment and the utility of environmental accomme-

dations vary as a function of behavioral and psychological risk and protectivefactors.

In an ongoing study, we are testing these assumptions alld examining how

specific cognitive (phonological sensitivity, naming speed, orthographic processing,and working memory) and noncognitive (attention, motivation, selfieMcacy) psycho-logieal risk and protective factors interaet with reading ability (decoding, word

reading, and reading comprehension), study and learning strategies, and environ-

mental accommodations (e.g., lighter course loads, use oi' family and friends as

readers and/or note takers, use ol' support services) in determining aeademic

achievement.

While the above studies are simple in their design and data analysis methods,

they are presented here as examples ot' research resulting from questions that the

assumptions of the Multiple Systems Modcl of Reading can lead us to consider. On

the simptest teveL, we could be examining the rnediating and moderating effects of

interactants frorn other systems or subsysterns, whereas more complex longitudinal

designs could bc aimed at modeling the cyclcs oi' contingencies that lcad to normative

outcomes, and the variations in the constellation and weighting of diflbrent inter-

actants that lead to individual differences, including learning disabilities.

In all approaches, the multiple systems model encourages inclusion of a wider

variety of participanrs and tasks, so that the joint contributions of various potentialrisk and protective ±

'actors can be assessed.

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Undcrstanding Rcading Disabilities

Educational Implications

The multiple systems model of reading has important ramifications in terms of

how we identit'y individuals who require educational accommodations and intcrven-

tions, the factors that should be considered when designing accommodations and

interventions and, further, how we assess the efllrctiveness of those accommodations

and interventions.

Traditionally, the process of identifying students as having learning disabi]ities

has, at least in North America, relied on an assessunent ot' whether a specific student

qualifies for some specific Iabel defined on the basis of some arbitrary criteria, such

as a two standard deviation diiference between an achievement test result and an

intelligence test result (see Fletcher, Lyon, Fuchs, & Barnes, 2007, {br a review ol' the

aptitude-achievement discrcpancy models), More recently, and at least partly as a

rcsult of criticisms of the aptitude-aehievement discrepancy models (e.g., Siegel, 1992),

several jurisdic]tions have moved towards models that rely on low achievement

together with some cxclusionary criteria (e.g., normal vision, hearing, inte"igence,

educational experiences) in order to maintain the idea that learning disabilities are

unexpectcd and result from an uneven patterns of intra-individual development.

Finally, the most recent models, driven in part by the 2004 reauthorization of the

Individuals with Disabilities Education Act (IDEA) in the U.S., combine low achieve-

ment and examination of how the individual responds to additional targeted interven-

tions, possibly leading to repeated cycles of assessments and interventions (see, e.g.,

Fletcher et al., 2007; Vellutino, Scanlon, Small, & Fanuele, 2006).

The Multiple Systems Model of Reading challenges each of these approaches,

First, no matter what approach is taken, it is necessary to acknowledge that distribu-

tions of all the assessed abilities are continuous, and the decision as to what the cut-off

score is for low achievement is nccessarily a financial dccision whose purpose is to

control aecess to additional educatienal resources, rather than to identify children

whose pcrformancc is somehow qualitatively diflbrcnt firorn the rest, It is not an

educational decision so long as we do not have data to show that, ibr example,

children whose performance fa]Js outside of the cut-off would not benefit from the

same reseurces. Being clear on this /issue is important for the discussion of how

existing resourccs are dividcd.

Second, whatever the criteria fbr low achievement, initial identification should

take place on the basis of the individual;s low achievement on the target academic (orpre-academic in the case of younger learners) skilL without any additional exclusionar-

y or inclusionary eriteria. This fo11ows from the idea of distributed control of the

developrnental process: academlc outcomcs arejointly determined by multiple factorsincluding the developing organism itself.

No interactant should be assumed to have a causal priority. All discrepancy

definitions and definitions that includc exclusionary criteria make this assurnption,

either directly or inadvertentty. Letting such assumptions guide identification leads to

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R. Parrila

absurd conclusions, such as that children with low IQ cannot have dyslexia: because

since beth IQ and reading ability (however dyslexia is defined) are normally distribut-ed, it fo11ows that some children wru fa11 at the low end of both distributions bychance alone. The same logic applies to the presumed impossibility of children having

both hearing impairments and dyslexia, or vision impairments and dyslexia. Once the

initial identification is completed on the basis of low achievement, the task then is to

try to identify and understand al1 the interactants that possibly affect the low

achievement of the particular individuai. Here it is partieularly important to include

both protective and risk factors to better account fbr the probabilistic relationship

between what we frequently regard as primary deficits and the academic outcomes,

and to enhance planning of interventions that address the problem simultaneously on

multiple levels.

Third, because performance is jointly determined by multiple interactants, and

because many of these interactants are distributed continuously in the population, it

follows that categorical classifications, such as "dyslexia'',

are dithcult to defend on

any grounds other than low performance of the target academic skill (where they are

ultimately defended on financiai grounds). This is because locating cases in specific

regiens of a multivariate space requires both making a somewhat arbitrary decision

as to what variables should be included and using arbitrary cut-offs tbr each ofthose

variables. Inciuding more than two variables quickly leads into a multiplication of

categories, whereby it quickly defeats the purpose of categorical classification.

This is not to say that such classifications cannot be usefu1 for research purposes.For example, assurning a phonologicaL processing deficit (rather than poor word

reading) as the core deficit in dyslexia has served research well in terms of under-

standing the interactants that impact word reading in poor readers who have a

phonological deficit (see, e.g., Frith, 2002; Ramus, 2006; Snowling, 2000). However,

poor word reading (whether defined on the basis of accuracy, a reasonable criterion

fbr children in English, or automaticity, perhaps the only reasonable criterion in more

consistent orthographies; sec, e.g., Yamada & Banks, 1994) is not necessarily associat-

ed with any single interactant, and determining the possible active interactants

(including phonological processing) for each individual is the precise task of educa-

tional assessment; a task that has to be guided by the best available data on what

variables aflbct word reading performance.

Finally, as a result of the observed low achievement being aflbcted by multiple

continuously distributed interactants (possibly with variable weightings), we should

expect large differences between individuals and few prototypical cases, That is,

heterogeneity rather than homogeneity is to be expected (see also Erskine & Seymour,

2005). The solution to the diversity is likely not better subtyping (e.g., increasing thenumber of categories; see above), but rather assessment and intervention planningthat acknowledges the role that multiple interactants can play in affecting behavior.

To guide assessment and intervention planning, we could develop checklists of

possible interactants (both risk and protective) that should be considered in order to

obtain a better understanding of the entire system when an individual is identified

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with a low aehievement on a specific aeademic task. Such checklists would initiallyconsist of all possi,ble interactants, as determined by the best available research

evidence, and the goal of the assessment would be to come up with a shorter list of

active interactants, some or all of which could then be targeted fbr intervention, The

selection of interventions should naturally also be guided by the best available

research evidence, however limited that is for any givcn approach.

Exaniple of the multiple n'sk and Proteetive foctors involved in word readiag deevelopment.

The discussion of risk and protective factors in what fbllows is not meant to exhaus-

tive but rather to iliustrate how many interactants may be involved in determining

performance level even in a relatively simple academic task. Readers familiar with

current assessment practices can also consider how many of the suggested inter-

actants are covered in such practices. Much of what is rcported below has been wellestablished with English-speaking participants. Some evidence wiIl also be reported

from studies conducted with participants learning to recognize words in orthograph-

ically more consistent alphabetic languages and in languages that do not use an

alphabetic writing system. However, caution should be exercised before making

generalizations to any specific language or writing system.

There is a general consensus among researchers that word reading problems

(often equated with dyslexia) in English are associated with problems in phonologicalawareness, that is, one's ability to reflect on and manipulate the phonemes in spoken

language (see, e.g., Share, 1995, for a review). Frith (1999), for example, estimated

that roughly 80% of British children with dyslexia have such problems. Although this

number may be an over-estimate (it was based on a sample of children already

diagnosed with a specific learning disability), the importance of phonological aware-

ness to learning and of being able to use grapheme-phoneme correspondences

fiuently, is well established in the English language.

In addition to phonological awareness, we know that several other cognitive level

variables can contribute to word reading difi,culties. These include rapid naming

speed and verbal short-term memory problems. Although these are often regarded as

being different expressions of the same underlying phonological deficit that also is

responsible for phonological awareness problems (see, e.g., Morton, 2004i Ramus,

2006), this interpretation is not universally accepted (see, e.g., Wolf & Bowers, 1999).Similarly, thc eflbct of hearing impairments on reading could be mediated by a

phonological deficit resulting from impoverished input to the phonological systern.

Rerated arguments can be made for temporal and cercbellar processing deficits (see,e.g., Frith, 1999; Morton, 2004; however, see Galaburda, 1999, for a diflerentinterpretation).

We also know that diMculties in learning to read words can be associated with

language factors that are not clearly phonological in nature, such as semantic deficits

(e.g., Shu, Meng, Chen, Luan, & Cao, 2005), morphological processing deficits (e.g.,Schiff & Raveh, 2007), and orthographic processing deficits (e.g., Badian, 1997, 2005;

Ho et al., 2004), as well as factors outside of the language system such as visual

memory (Ho et al., 2004), visual attention span (Bosse et al,, 2007), and motivation

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R, Parrila

(e.g., Lepola, Poskiparta, Laakkonen, & Niemi, 2005; Stephenson et al., 2008). Inaddition, the ease with which children learn to read words may be aflbcted by at least

some aspects efthe home environment (e.g., Burgess, Hecht, & Lonigan, 2002; Evans,

Shaw, & Bell, 2000; Stephenson et al., 2008), the severity of their difilculties, and the

teaching methods employcd at their school (e,g., Landerl, 20001 Papadopoulos, 2001).The point of this list is not to be exhaustive but rather to illustrate that even when

we are looking at an academic task that Hkely has a strong biological and neurological

basis, the list of factors that can negatively aflect individuals' performances, and that

may need to be addressed in order for an intervention to be successfu1 (Andreassen,Knivsberg, & Niemi, 2006; Niemi, Poskiparta, & Vauras, 2001), is likely to be much

tonger than the usual lists of causal factors.

Hewever, many individuals with phonological problems do Iearn to read words

(e.g., Bishop & Adams, 1990; Parrila et al,, 2007; Wilson & Lesaux, 2001). What,

then, are the protective factors that allow at least some individuals to develop

functional word reading skills? On theoretical grounds (see, e.g., Coltheart, Curtis,

Atkins, & Haller, 1993), an obvious candidate for a cognitive protective factor is

orthographic knowledge, While the current evidence on this is mixed, several studies

have reported orthographic knowledge as a relative strength (e.g., Mrucr-Shaul, 2005;

see also Siegel, Share, & Geva, i995) or as a possible compensatory tool (Leinonen,MUIIer, Leppanen, Aro, Ahonen, & Lyytinen, 2001; van der Lelj & van Daal, 1999),

makirig it likely that it is a protective factor for at least some individuals.

Elbro (1993), in turn, suggested that the ease of lexical access determines thedegree to which individuals with reading disabilities can compensate for their primary

phonological deficit by using more whole-word oriented strategies. Elbro (1993)provided preliminary evidenec for this position by showing that adolescents with

dyslexia who used more whole-word oriented reading strategies aiso had faster

picture naming times. In a second study, Elbro (1993) showed that this relation did

not extend to readers who were not dyslexic.

Yet another possibility is that relatively intact morpholo.ifical knowledge compen-

sates for poorer phonological skMs. Here again, the evidence is mixed, with sorne

studies showing at least reading-age appropriate pcrformancc level on morphological

tasks (e.g., Elbro & Arnbak, 1996; Leong, 1999) and others not (e,g., Deacon, Parrila,

& Kirby, 2006; Joanisse et al., 2000), with one possible explanation fbr those

difflerences being the aspects of morphology that each study fbcused on (see Deacon,Parrila, & Kirby, in press, for a review). In addition to possible protective factors

within the cognitive system, we know that good home literacy environment (Torppa,Poikkeus, Laakso, Tolvanen, Leskinen, Leppanen, Puolakanaho, & Lyytinen, 2007),early interventions (e.g., Byrne & Fielding-Barnsley, 1995), and motivational orienta-

tion can have a positive impact on future readang development, so that these f'actorsshould perhaps be added to the list of interactants whose status is assessed. Needlesste say, as research on word reading development progresses, some of the current and

perhaps poorly defined interactants will be replaced by better defined ones, some wiIIbe dropped, and new ones will be added.

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-





In summary, several systerns have been implicated as possible risk and protectivefactors in word reading development. While the phonological subsystem is likely moreheavily weighted than any other, it cannot be assumed to have entire control of the

developmental process. Therefore, for assessment to be maximally infbrmative and

the resulting interventions maximally efiective, multiple systems need to be addressed.

Note that in order to increase the chances of future success, this is true even if a

phonological deficit is identified and remediated (see, e.g., Niemi et al., 200I).

Summary and Conclusions

The present article has argued that in order to understand reading development

and disabilities fu11y, both within and across diffk}rent Ianguages, a better meta-

theoretical t'ra'mework is needed to guide both the research itself and also the

interpretation of research findings in relation to educational practice. One such

framework, the multiple systems model ofreading, was presented briefly. This model

looks at normal reading developrnent and disabilities as diflbrent states of the same

complex developing system, with no single interactant being allocated the entire

causal control of the developmental process.

This does not mean that researchers should give up the search fbr specific

genetic, neural, or cognitive mechanisms that contribute to reading development, or

the development of theories that explain the contribution of these mechanisms. Onthe contrary, such work is necessary and has greatly increased our understanding of

the genetic, neural, and cognitiVe factors that should be included in a cemprehensive

model (see, e,g,, Ramus, 2006, for a review). What the multiple systems rmodel of

reading contends, instead, is that theories will be enriched if' they conceptualize

development at all levels as construction and focus on identifying the interactants ofthis process (see, e.g., Galaburda, LoTurco, Ramus, Fitch, & Rosen, 2006, f'or an

example in the genetic-neural level), and that none of these theories per se constitutes

a sufEcient explanation for the development of the target behavior, reading,

In particular, educational practice is well served by respecting the complex, and

sometimes idiosyneratic, nature of the developing organism, and by not allocating

causal responsibility and all the assessrnent and remedial e'flbrts of possible reading

problems to any single cause.

Author Note

I would like to thank John Kirby, Jari-Erik Nurrr]i, Robert Klassen, JenniferBarber, Sancly Lai and Hisao Maekawa fbr their comments on the earlier draft of this

paper. The preparation ol' the ideas presented in this paper has been partiallysupported by grants from Social Sciences and Humanities Research Council of

Canada, Killam Research Fund, and Faculty of Education, University of Alberta. All

correspondence regarding this paper should be addressed to Rauno Parrila at rauno.

[email protected].

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R. Parrila

References

Adams, M. J. (l990) Beginning to read. MIT Press, Cambridge, Massachusetts.Ahissar, M, (2007) Dyslexia and the anchoring-deficit hypothesis, TYends in Cbgnitive S2:iences,

11, 458-465.

Andreassen, A, B., Knivsberg, A, M., & Niemi, P, (2006) Resistant readers 8 months later:

Energizing the student's lcarning milieu by targeted counselling. Dystexia, 12, 1 15-138.

Aunola, K., Nurmi, J.-E., Niemi, P., Lerkkanen, M.-K., & Rasku-Puttonen, H. (2002) Developmental dynamics of achievement strategics, reading performance, and paren-

tal beliefs. Reading Researoh qpaarterly, 37, 310 327.Badian, N. A. (1997) Dyslexia and the Double Deficit hypothesis. Annats of' Qysimia, 47,

69-88.Badian, N. A. (2005) Does a visual-erthographic deficit contribute to reading disability?

Annats of' D)slexia, 55, 28-52.Badian, N. A,, Duffy, F, H., Als, H,, & McAnulty, G. B. (1991) Linguistic profiles of

dyslexlc and good readers. Annals of I]tyslexia, 41, 221 245.Birch, S. & Chase, C. (2004) Visual and language processing deficits in compensated and

uncempensated eollege students with dyslexia. .lburaat

qf Leaming Disabilities, 37, 389-

410,

Bishop, D. V. & Adams, a. (1990) A prospective study of the relationship between specific

language impairment, phenological disorders and reading retardation. Jburnal of C:hild llsJcholegy and Rtychiat[); and Allied Disoptines, 31, 1027-1050,

Bosse, M.-L., Tainturier, M. J., & Valdois, S. (2007) Developmcntal dyslexia: The visual

attention span deficit hypothesis. Cbgnition, 104, 198 230,Buchholz, J. & McKone, E. (2004) Adults with dysLexia show deficits on spatial t'requency

doubling and visual attention tasks. Ilyslkxia, 10, 24-4S.

Burgess, S. R,, Hecht, S. A., & Lonigan, C. J. (2002) Relations of the home literacy

environment (HLE) to the developmcnt ufreading'-relatcd abilities: A olle-year longitu-

dinal study. Reading' Research Qztarterly, g7, 408-426.

Bus, A, G,, van IJzendoorn, M. II., & Pcllegrini, A. D. (1995) Joint book reading makes fbr

success in learning to read: A meta-analysis on intergencrational transmission of

literacy. Review of Edttcational Research, 65, 1-21.

Byrne, B., & Fielding-Barnsley, R, (1995) Evaluation of a program to teach phonemic

awareness to young children: A 2- and 3-year fo11ow-up and a new preschool trial.

.lburnal of Educational RsJchology, 87, 488-503.

Coltheart, M., Curtis, B., Atkins, P., & Haller, M, (l993) Models of reading aloud:

Dual-route and parallel-distributed-processing approaches. Ils"choiQgical Review, 100,

589-608.Corkett, J. K,, Hein, S. F,, & Parrila, R. (2008) 7Jhe role of Personal characterdstics in comPensat-

ing for reading dijficulties: A gualitative inevestigation of' universiip students' espen'encas.

Manuscript submittcd for publication.Corkctt, J, K., Parrila, R., & Hein, S. F, (2006) Learning and study strategies of university

students who report a significant history of reading difficulties. Deveiopmental Disabitities

Bultetin, 34, 57-79J

--

398




Understanding Rcading Disabilities

de Jong, P. F. & van der Leij, A. (1999) Specific contributions of phonQlogical abilities to

early reading acquisition: Results from a Dutch latcnt variable Iongitudinal study.

.lburnal of Educational RiJtholqgy, 91, 450 476.

Deacon, S. II., ?arrila, R., & Kirby, J. R. (2006) The status of morphological processing in

compcnsated dyslexics. Annats of Qystkxia, 56, 103-128.Deacon, S. H., Parrila, R., & Kirby, J, R. (in press) A review of the evidence on

rnorphological processing in dyslcxics and poor rcaders: A strength or weakness? In F.

Manis, A. Fawcett, G. Reid, & L. Siegel (Eds.), Pyslexia handbook. Sage Publications,

London.Egan, J. & Pring, L. (2004) The processing of infiectional morphology: A comparison of'

children with and without dyslexia. Reading and uaitin.a, 17, 567 -591, .

Elbro, C. (1993) Dyslexic reading strategies and lexical access: A comparison and validation

of' reading strategy distributions in dyslexic adolescents and younger, normal readers.

In R. M. Joshi & C. K, Leong (Eds.), Reading disabilities: Diagnosis and component Processes. KIuwer, Dordrecht, 239-251.

Elbro, C. & Arnbak, E. (1996) The role ef morpheme recognition and morphological

awarencss in dyslexia, Annats of l]lyslexia, 46, 209 2<LO,Ellis, N. C., Natsume, M,, Stavropoulou, K., Hoxhallari, L,, van Daal, V. H., Polyzoe, N,,

Tsipe, M.-L., & Petalas, M. (2004) The eflects of orthographic depth on learning to

read alphabetic, syllabic, and logographic scripts. Reading Research Quarterly, 39,

438-460.Entwisle, D. R. & Hayduk, L, A, (1988) Lasting eflects of elementary school, Sociolagv qf Education, 61, 147-159.Erskinc, J. M, & Seymour, P. H. K. (2005) Proximal analysis of developmental dyslexia in

adulthood: The cognitive mosaic modcl. Jlburnag qf Eduaational Rsycheiogy, 97, 406-424.

Evans, M. A,, Shaw, D,, & Bell, M, (2000) Home literacy activities and their influence on

early literacy skills. thnadian .lburnal

of ]ExPerimental RsJchellzg], 54, 65-75.

Fink, R. P. (1998) Literacy development in successfu1 men and womcn with dyslexia. Annats

of I]lvslexia, 48, Sl1-346.Fletcher, J, M., Lyon, G. R., Fuchs, L. S., & Barnes, M, A. (2007) Learning disabiibties: thom

idbtztofication to intervention. Guiltbrd Press, New York. '

Ford, D. H, & Lerner, R. M, Cl992) DeveloPmental spstems theot:y: An intugnitioe aPPreach. Sage,

Newbury Park, Calithrnia.Frith, U. (]999) Paradoxes in the definition of dyslexia. Ilystdria, 5, 192-214.

Frith, U. (2002) Resolving the paradoxes of dyslcxia. In G. Reid & J. Wearmouth CEds,), l]b,slewia and titeraay,' Theotv and Practice. Wiley, Chichester, UK, 45-68,

Galaburda, A. M. (1999) Developmental dyslexia: A multilevel syndrome. L!pusllaxia, 5,

183 -191.

Galaburda, A. M., LoTurco, J., Ramus, F., Fitch, R. H., & Resen, G, (2006) From genes

to behavior in developmental dyslexia. JVketure dearoscience, 9, 1213-1217.

Georgiou, G. K., Parrila, R,, & Kirby, J, (2006) Rapid naming speed components and early

reading acquisition. Scientijic Stntdies qf Reading, 10, 199-220.

Georgiou, G. K., Parrila, R., & Liao, C.-H. (in press) Rapid naming speed and reading

across languages that vary in orthographic consistency. Reading and uaiting.Georgiou, G. K., Parrila, R., & Papadopo'ulos, T. C. (in press) Predictors of werd decoding

-399-




R. Parrila

and reading fiuency across languages varying in orthographie consistency. .foumal

qf

Educational RF]thology,.

Giraudo, H. (2001) R61e et repr6sentation de I'inibrmation morphologique chez Papprenti

lecteur et 1'enfant dyslexique (The role and representation of morphologieal infbrma-

tion in the beginning reader and in dyslexic children). Annates Ilyssen, 16, 81-90. (in French)

Goswarmi, U. (2003) Why theories about developmcntal dyslexia require developmental

designs. 71ends in Clognitive S2riences, 7, 534-540.Goswami, U., Thomson, J., Richardson, U., Stainthorp, R., Hughes, D,, Rosen, S., & Scott,

S, K, (2002) Amplitude envelope onsets and developmental dyslexia: A new hypothe-

sis. PLIVIAS, 99, 10911-10916.

Gottlieb, G. (198B) The psychobiological approach to developmental issues. In M, M.

Haith & J. J. Campos (Eds.), lldndbook of child Pspchelogy (4th ed., VoL 2). Wiley, New

York, 1･-26.

Gottlieb, G. (l997) Synthesicing nature-nurture: Prenatal roots qf' instinctieve behaevior, Lawrenee

Erlbaum Associates, Mahwah, New Jersey.Gottlieb, G. & Halpern, C. T. (2002) A relational view of causality in norrnal and abnormal

development. Dewetopment and RsJchopathology, 14, 421-435.

Gettlieb, G., Wahlsten, D., & Lickliter, R. (2e06) The significance of biology fbr human

development: A developmcntal psychobiological systems view. In R, M. Lerner & W.

Damon (Eds.), Hbndbook of child Psychology (6th ed., Vo]. 1). Wiley, Hobokcn, New

Jersey, 210-257.Ho, C. S.-H., Chan, D. W,-O., Lee, S.-H., Tsang, S.-M,, & Luan, V, H. (2004) Cognitive

profiling and preliminary subtyping in Chinese dcvelopmental dyslexia. Cbgnition, 91,

4S-75.Ho, a. S.-H., Chan, D. W.-O., Tsang, S.-M., 8t Lee, S.-H. (2002) The cognitive profile and

multiple-deficit hypothesis in Chinese developmental dyslexia. Deveiopmental Rsychology,

38, 543-553.

Howard, J, H., Jr., Howard, D. V., Japikse, K. C., & Eden, G. F. (2006) Dyslexics are

impaired on implicit higher-order sequence learning, but llot on implicit spatial

context learning, Muropsycholagia, 44, 1I31-1144.

Jackson, N. E, (2005) Are university students' component reading skills related to their text

cemprehension and academic achievement? Learning and individual Diplrrences, 15,

113-139,

Joanisse, M. F,, Manis, F., Keating, P,, Seidenberg, M. S. (2000) Language specific deficits

in dyslexic children: Speech perception, phonology, and morphology. Jhurnal o.f

ErPerimental Child RsJchology, 77, 30-60.

Keim, J., McWhirter, J. J., & Bernstein, B. L. (1996) Academic success and university

accommodation fbr learning disabilities: Is there a relationship? .lburnal of Cbltage

Student DewelQPment, 37, 502- 509,King, W. M., Lombardino, L. J., Crandell, C. C., & I.eonard, a. M. (2003) Comorbid

auditory processing disorder in developmental dyslexia. Ear and Hlaan'ng, 24, 448-456,

Kinsbourne, M., Rufo, D. T,, Gamzu, E., Palmer, R. L., & Berliner, A. K. (l991) Neuropsychological deficits in adults with dyslexia. Deweiopmental Medicine and Child

.IV17urology, 33, 763-775. '

- 400

-





Kirby, J. R., Parrila, R. K., & Pfeifik]r, S. L. (2003) Naming speed and phonological awareness as predictors of reading development. Jbermal Qf Educationat Ilsyohotogy, 95,

453-4･64.

Kirby, J, R., Silvestri, R., Alligham, B,, Parrila, R., & La Fave, C, B. (2008) Learning

strategies and study appreaches of collcge and university students with dyslexia.

.lbumat qf Learning Disabitities, 41, 85-96.Landcrl, K. (2000) Influenc¢ s of' orthographic consistency and reading instruction on the

development of nonword reading skills. European Jbttrnal of Rg]chology qf Education, l5, 239-257,Lcikin, M. & zur Hagit, E. (2006) Morphological processing in adult dyslexia. .lburnal of Rgychok'nguistic Research, 35, 471-490,Leinoncn, S., Mti11er, K., Leppanen, P., Are, M., Ahoncn, T,, & Lyytinen H. (2001) Hetcrogeneity in adult dyslexic readers: Relating processing skills to the speed and

accuracy of oral text reading, Reading and vaniting, 14, 265-296.

Leong, C. K. (1999) Phonological and morphological processing in adult students with

learning!reading disabilities. .lburnat

of Learning Disabitities, 32, 224-238,Lepola, J., Poskiparta, E,, Laakkonen, E., & Niemi, P. (2005) Development ol' and relation-

ship between phonological and motivational processes and naming speed in predicting word recognition in Grade l, Sicientijic Studies of' Readiag, 9, 367-399,Liao, C.-H., Georgiou, G. K., & Parrlla, R. (in press) Rapid naming speed and Chinese

character recognition. Reading' and uaiting.Lyytinen, H., Aro, M., Eklund, K., Erskine, J., Gllttorm, T., Laakso, M.-L,, Lepptinen, P.

T., Lyytinen, P., Poikkou, S. A., & Richardson, U. <2004) The development ef children

at familial risk fbr dyslexia: Birth to early school age. Annals of Qysimia, 54, 184-220.Manolitsis, G., Georgiou, G., Stephenson, K., & Parrila, R, (submitted) Baginning to vaad

across laaguages vanying in orthagrophic consistenay: Comparin.cr the qi7i7cts qf' non-cagnitive and

cagnitive predictors. Manuscript submitted ['or publication.McBride-Chang, C., Shu, H., Zhou, A., Wat, C. P., & Wagner, R. K. (2003) Morphological

awareness uniquely predicts young children's Chinese charaeter recognition. Jburnal of Educational Rsychotog),, 95, 743-751.Meyler, A. & Breznitz, Z. (2003) Processing of phonological, orthegraphic and cross-modal

word representations among adult dyslcxic and normal readers. Reading. and maiting,

16, 785-803.

Miller-Shaul, S. (2005) The characteristics of young and adult dyslcxics readers on reading

and reading related cognitive tasks as coinpared to normat readers. L!ysZlrxia, 11, 132

151.

Monis, R. D., Stuebing, K. K., Flctcher, J. M., Shaywitz, S. E,, Lyon, G. R.,.Shankweiler,

D, P., Katz, L., Francis, D. J., & Shaywitz, B. A. (1998) Subtypes of reading disability:

Variability around a phonological core. Jlburnal of Educational Rtycholqgy, 90, 347-373.Morton, J. (2004) Uitderstandin.a devetQPmentag disotdkrs: A causat modeting approach. Blackwell

Publishing, Maldcn, Massachusetts,Nicolson, R. I. & Fawcett, A, J, (1990) Automaticity: A new framework for dyslexia

rescarchl/' Cbg'nition, 35, 159-182.Niemi, P., Poskiparta, E,, & Vauras, M, (2001) Benefits of training in linguistic awareness

dissipate by grade S? .lburnal of the Ubllenic RsJcholagical Society, 8, 330-337.

-401




R. Parrila

Olson, R. K. & Gayan, J. (2eOI) Brains, genes, and environment in reading development,

In S. B. Neuman & D. K. Dickinson (Eds,), Uitndbeok of early titeraay researth. Guiltbrd

Press, New York, 81 -94.

Oyama, S., Griffiths, P. E., & Gray, R. D. (20el) Introduction: What is developmental

systems theory? In S. Oyama, P. E. GriMths, R. D. Gray (Eds,), ([lyales oj' contingentl)J:

Deevelopmental systems and eevotution. MIT Press, Cambridge, Massachusetts, 1-11.PapadopoulQs, T. C. (2001) Phonological and cognitive correlates of word-reading acquisi-

tion under two different instructional approaches in Gr ¢ ck, European .lbumal of Rs]chology of Educatien, 16, 549-568.Parrila, R., Georgiou, G., & Corkett, J. (2007) University students with a significant history

of rcading diMculties: What is and is not compensated? Erccoptionality Education ( Zinado,

17, 195-220.Parrila, R., Kirby, J, R., & McQuarrie, L. (2004) Articulation rate, naming speed, verbal

short-term memory, and phonological awareness; Longitudinal predictors of early

reading development. Stientijc Studes qf Reading, 8, 3-26.Pennington, P. F. (20e6) From single to multiple deficit models of developmental disorders.

Cbgnition, IOI, S85-413.Rack, J. (1997) Issues in the assessment of dcvelopmental dyslexia in adulLs: Theoretical

and applied perspectives. .11?urnag of Research in Reading, 20, 66-76.

Rarnus, F. (2006) A neurological model of dyslexia and other domain-specific develep-

mental diserders with an associated sensorimotor syndrorne, In G. D. Rosen (Ed.), 7he

dystexic brain: Mw Pathways in neuroscience dircoverpJ. Lawrence Erlbaum Associates,

Mahwah, New Jersey, 75-IOI,Ramus, E, Rosen, S., Dakin, S, C,, Day, B, L,, Castellote, J. M., White, S., & Frith, U. (200S) Theories oi' developmental dyslexia: Insights from a multiple case study of dyslexic

adults. Brain, I26, 841-865.Ramus, F. & Szenkovits, G, (2008) "Jhat phonological deficit? Qpaarterly

.lburnal qf' ExPerimen-

tal Aychology, 61, 129-141,

Reid, A, A., Szczerbinski, M., Iskierka-Kasperek, E., & Hanscn, P, (2007) Cognitive prefilcs of adult developmental dyslexics: Theoretical implications. QysZkxia, 13, 1-24.

Reis, S. M,, McGuire, J. M., & Ncu, T. W. (2eOO) aompensation strategies used by

high-ability students with learning disabilities who succeed in college. G(fted enild

QFearterly, 44, 123-134,Ruban, L. M,, McCoach, D, B., McGuire, J. M,, & Rcis, S. M. (2003) The diflerential

impact of academic seltLregulatory methods on academic achievement among univer-

sity students with and without learning disabilities. .lburnal

of Leaming Disabilities, 36, 268-284.

Schiff R. & Raveh, M. (2007) Defieient morphological processing in adults with develop-

mcntal dyslexia: Another barrier to eMcient word recognition? Qptslaxia, 13, 1IO-129.Seymour, P. H. K., Aro, M., & Erskine, J. M, (2003) Foundation literacy acquisition in

European orthographies. British .lburnat

of Rtvehology, 94, I4S-174,Share, D. L. (1995) Phonological reeoding and selftteaching: Sine qua non of reading

acquisition. Cagnitien, 55, 151-218.

Shaywitz, S. E,, Escobar, M. D., Shaywitz B. A., Fletcher, J. M., & Makuch, R. (1992) Evidence that dyslexia may represent the lower tail ofa normal distribution of rcading

-

402 -





ability, rvlrw En.aland .lbumal

of Medicine, S26, 145-150.Shu, H., McBride-Chang, C., Wu, S,, & Liu, II. (2006) Understanding Chinese develop-

mental dyslexia: Morphological awareness as a core cognitive construct. .lburnal of Educational ilrychotogy, 98, 122-,133,Shu, H., Meng, X., Chcn, X., Luan, H,, & Cao, F, (2005) Thc subtypes of developrmental

dyslexia in Chinese: Evidence from three cases. 1]tvsilexia, 11, Sl1-329.

Siegel, L. S. (1992) An evaluation of the discrepancy definition of dyslexia. .lburnal

qf Learning Disabilities, 25, 618-629.Siegel, I., S., Sharc, D., & Geva, E. (t995) Evidcnce for superior orthographic skills in

dyslexics. Rslcholagical Stience, 6, 250-254.Silinskas, G., Leppanen, U,, Aunela, K., Parrila, R. & Nurmi, J.-E, (submitted) (:iiiidrenle

academic skill Pvadicts Parental teac'hing. Manuscript submitted Ibr publicatien.Singleton, C. &. Trottcr, S. (2e05) Visual strcss in adults with and without dyslexia. .lburnal

of Research in Reading, 28, S65-378. '

Snowling, M. J. (2000) ,Qyslexia (2nd ed.). Blackwell, Oxford, England.

Snowling, M. J. C2001) From language to reading and dyslexia. Qyslexia, 7, 37-46,

Stanovich, K. E. (1988) Explaining the diff'erences between the dyslexic and the garden-

variety poor reader: The phonological-core variable-diflerence modei. .lburnag

of Learning Ddsabilities, 21, 590 604, 612.

Stephenson, K. A., Parrila, R. K., Georgiou, G, K., & Kirby, J. R. (2008) Effects of homc

literacy, parents' beliefs, and children's task-focused behavior on emergent literacy

and word reading skills. Stientipc Studies of Reading, 12, 24-50.Szenkovits, G. & Ramus, F. C2005) Exploring dyslexics' phonologieal deficit I: Lexical vs

sub-lexical and input vs output proeesses. Ilystexia, l1, 25S-268.Tallal, P., Miller, S. L,, Jenkins, W, M., & Merzenich, M. M. (l997) The role of temporal

processing in developmental language-based learning disorders: Research and clinical

implications. In B. A. Blachman (Ed.), Fbundations of reading acquisition and dyslexia: inzpiications for early intevaention, I.awrence Erlbaum Associates, Mahwah, N'ew Jersey, 49-66,

Tan, L. H,, Spinks, J. A., Eden, G. F., Perl'etti, C. A., & Siok, W. T. (2005) Reading dcp ¢ nds

on writing, in Chinese. PIV/AS, 102, 8781-8785.

Torppa, M., Poikkeus, A.-M,, I.aakso, M,-L., Tolvanen, A., Leskinen, E,, Leppljnen, P. II.,

Puolakanaho, A., & Lyytinen, H. (2007) Modeling the early paths of phonological

awareness and factors supporting its development in children with and without

f'amilial risk of dyslexia. SZ'ientijic Studies e.f Readirrg, 1], 7B-103.Torppa, M., Tolvanen, A., Poikkeus, A.-M., Eklund, K., Lerkkanen, M.-K., Leskinen, E.,

& Lyytinen, H. (2007) Reading developme]t subtypes and their early characteristics.

Annals of' IItvsimia, 57, S-S2.van der Leij, A. & van Daal, V. H, P. (1999) Automatization aspects of dyslexia: Speed

limitations in word identifieation, scnsitivity to increasing task demands, and ortho-

graphic compensation, Jburnal of' Leaming Disabilities, 32, 417-428.

Vellutino, F. R., FIetcher, J. M., Snowling, M. J., & Scanlon, D. M. (2004) Specific rcading

disability (dyslexia): What havc wc lcarned in the past four decades? .lburnal qf enild

AJchotogy and Ilslchiatrv, 45,2 40.Vellutino, F. R., Scanlon, D. M., & Tansman, M, S. (1991) Bridging the gap between

- 4e3

-




R. Parrila

cognitive and neuropsychological conceptualizations ofreading disability. Leamin,g and

inchvithtat Dij7ierences, 3, l81-203.

Vellutino, F. R,, Scanlon, D. M., Small, S,, & Fanuele, D. P. (2006) Response to intervention

as a vehicle fbr distinguishing between children with and without reading disabilities:

Evidence fbr the role ofkindergarten ancl first-grade interventions. Jrburnal of Learning Disabilities, 39, 157-169.Vogel, S. A. & Adelman, P. B. (1990) Intervention eff'ectiveness at the postsecondary level

fbr the learning disabled. In T, Scruggs & B. Wong (Eds.), intervention resean'h in leaming

daabitities. Springer-Verlag, New York, 329-344.

Vogel, S. A. & Adelman, P. B. (l992) The success of college students with learning

disabilities: Factors related to educational attainrnent, .lbumag

ctf Learning Disabifities,

25, 430-441.

Wilson, A. M, & Lesaux, N. K, (2eOl) Persistence of phonological processing deficits in

college students with age-appropriate reading skills, Jrburnat of Leaming Ddsabitities, 34, 394--400.Wolg M. & Bowers, P. G (1999) The Double-Deficit hypothesis fbr the developmental

dyslexias. Jrbumal qf Educational RyJchology, 91, 415-4S8.Yamada, J. & Banks, A. C1994) Evidence tbr and characteristics of dyslexia among

Japanese children. Annals of' P;vslexia, 44, 105-l19.

Ziegler, J. C. & Goswami, U. (2005) Reading acquisition, developmental dyslexia, and

skilled reading across lunguages: A psycholinguistic grain size theoTy. Rs2eholagical

Bulhetin, 131, S-29.

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January 31, 2008; Accepted February 23, 2008-

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