Verbal Learning Abilities and Stimulus Modalities in Children with Dyslexia

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Stimulus modality and working memoryperformance in Greek childrenwith reading disabilities: Additionalevidence for the pictorial superiorityhypothesisFofi Constantinidou a & Christiana Evripidou ba Department of Psychology, University of Cyprus, Nicosia, Cyprusb Ministry of Education and Culture, The Republic of Cyprus,Nicosia, Cyprus

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To cite this article: Fofi Constantinidou & Christiana Evripidou (2011): Stimulus modality andworking memory performance in Greek children with reading disabilities: Additional evidence forthe pictorial superiority hypothesis, Child Neuropsychology, DOI:10.1080/09297049.2011.602013

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Child Neuropsychology, 2011, iFirst, 1–25http://www.psypress.com/childneuropsychISSN: 0929-7049 print / 1744-4136 onlinehttp://dx.doi.org/10.1080/09297049.2011.602013

Stimulus modality and working memory performance

in Greek children with reading disabilities: Additional

evidence for the pictorial superiority hypothesis

Fofi Constantinidou1 and Christiana Evripidou2

1Department of Psychology, University of Cyprus, Nicosia, Cyprus2Ministry of Education and Culture, The Republic of Cyprus, Nicosia, Cyprus

This study investigated the effects of stimulus presentation modality on working memory performancein children with reading disabilities (RD) and in typically developing children (TDC), all native speak-ers of Greek. It was hypothesized that the visual presentation of common objects would result inimproved learning and recall performance as compared to the auditory presentation of stimuli. Twentychildren, ages 10–12, diagnosed with RD were matched to 20 TDC age peers. The experimental tasksimplemented a multitrial verbal learning paradigm incorporating three modalities: auditory, visual,and auditory plus visual. Significant group differences were noted on language, verbal and nonverbalmemory, and measures of executive abilities. A mixed-model MANOVA indicated that children withRD had a slower learning curve and recalled fewer words than TDC across experimental modalities.Both groups of participants benefited from the visual presentation of objects; however, children withRD showed the greatest gains during this condition. In conclusion, working memory for commonverbal items is impaired in children with RD; however, performance can be facilitated, and learningefficiency maximized, when information is presented visually. The results provide further evidencefor the pictorial superiority hypothesis and the theory that pictorial presentation of verbal stimuli isadequate for dual coding.

Keywords: Reading disabilities; Verbal learning; Working memory; Stimulus modality; Languageprocessing; Language networks; Dual coding; Language learning disabilities; Pictorial hypothesis.

INTRODUCTION

Contemporary models of reading disabilities (RD) have proposed a multidimensionalapproach to the disorder where neurobiology, core cognitive processes (such as memory),and environmental factors interact and contribute to the presentation of the disorder.Working memory (WM) has been the focus of extensive research because it is a prerequi-site for successful reading attainment (Berninger et al., 2010; de Jong, 1998; Gathercole

The authors would like to thank the children, parents, and teachers who participated in this study andthe Cyprus Ministry of Education and Culture. Additionally, we thank Timotheos Papadopoulos and GeorgeSpanoudis, Department of Psychology University of Cyprus for their valuable suggestions during the earlierstages of this study.

Address correspondence to Fofi Constantinidou, Department of Psychology, University of Cyprus,75 Kallipoleos St., P.O. Box 20537, 1678, Nicosia, Cyprus. E-mail: [email protected]

© 2011 Psychology Press, an imprint of the Taylor & Francis Group, an Informa business

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2 F. CONSTANTINIDOU & C. EVRIPIDOU

& Baddeley, 1993; Gathercole et al., 2006; Montgomery, Magimairaj, & Finney, 2010;Swanson, 1992 Swanson & Jerman, 2007; Swanson & Zheng, 2009). Provided that both ofthese domains (i.e., WM and reading attainment) are problematic for children with read-ing disabilities, strong arguments have been put forward suggesting that working memoryimpairments may account in part for some of the academic problems of children withreading disabilities (Baddeley, 1986, 1990; Gathercole & Baddeley, 1993; Gathercole &Pickering, 2004 Swanson & Berninger, 1995).

While reading difficulties typically surface in kindergarten or early school years,many children with RD have a history of language learning disorders. These childrenmay have received early oral language intervention during their preschool years, yet, theymay lag behind in their linguistic competency (i.e., phonological, orthographic, syntac-tic, and morphological abilities) that can hinder literacy achievement during grade school(Berninger et al., 2010). While children with RD are not a homogeneous clinical group,the literature has established that WM is implicated in the disorder and certain aspects ofWM in relationship to language processing are critical to reading success. Berninger andassociates reported that word-level working memory is an important predictor for readingand writing abilities in second, fourth, and sixth graders.

Working memory (WM) abilities improve during childhood as children’s organi-zational abilities, executive skills, and encoding strategies expand in response to taskdemands through the expectations of their academic curriculum and experience. For exam-ple, English-speaking children in fifth and sixth grade demonstrated significantly betterword recall performance as compared to children in second and third grade during multi-trial verbal learning memory tasks (Constantiniou, Danos, Nelson, & Baker, 2011). Thisexpansion and development involves the incorporation of strategy (through executive sys-tem mechanisms) and is thought to be mediated by the continued neuronal proliferationof the frontal lobes and cortical association areas, a combined result of biological matura-tion and experience (Cummings & Mega, 2003; Egeland et al., 2005). The current studyincorporated older elementary school children with RD and typically developing childrenin order to determine the effects of stimulus presentation modality on learning, recall, andrecognition performance. Identifying effective ways of presenting information to school-age children (with RD) could maximize verbal learning and improve WM performance.Additionally, this study is the first study exploring verbal learning and modality prefer-ences with native speakers of Greek. Most WM tasks in English consist primarily of simplemonosyllabic words and/or numbers (e.g., digit-recall tasks). However, the Greek lexicondoes not contain hardly any monosyllabic nouns, numbers, or verbs. Given the mediatingrole of language on verbal memory tasks and the fact that Greek has a different morphol-ogy, syntax, phonology, and orthography than English, this study will fill some of the gapsin knowledge on the effects of RD and stimulus modality on three important aspects ofmemory: verbal learning, retention, and recognition performance. In the next sections, weprovide information regarding the theoretical frameworks and the background research thatinformed the design of this study.

Theoretical Framework of Working Memory

Since the 1960s, human memory has been the focus of several theoretical frame-works. Recently, memory models have offered theoretical constructs of working memory,especially in the context of language processing and cognitive organization (MacDonald

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STIMULUS MODALITY AND READING DISABILITIES 3

& Christiansen, 2002; Montgomery et al., 2010). For example, Just and Carpenter (1992)proposed a single, nonmodality specific, WM system that processes linguistic informationand whose success is highly affected by individual differences. On the contrary, Waters andCaplan (1996) adopt a modular approach where WM is separate from language process-ing and linguistic knowledge and proposed two types of working memories: one type forconscious and verbally mediated tasks and another for unconscious processing involvedin online linguistic comprehension (MacDonald & Christiansen, 2002; Waters & Caplan,1996). Finally, MacDonald and Christiansen (2002) offer a connectionist model whereverbal WM capacity is not distinguishable from language comprehension or language pro-cessing. A thorough review of the WM theories is certainly beyond the scope of this articleand the reader is referred to Montgomery et al. (2010) for further reading on the topic. Thisstudy implements Baddeley’s theory of working memory (Baddeley, 1986, 2000, 2001,2003; Baddeley & Hitch, 1974). We believe that this framework has considerable utility inpopulations with memory disorders (Sander, Richardson, Constantinidou, Wertheimer, &Paul, 2007).

According to the systems model of WM proposed by Baddeley and associates, mem-ory consists of a set of interrelated systems and subsystems. When information arrives viathe sense organs, that is, perceptually encoded, it is deposited into an immediate workingmemory system that is divided into three subsystems specialized for different functions(Baddeley, 1986): a control system or the executive network of attention and two slavesystems each handling different types of information: the visuospatial sketchpad and thephonological or articulatory loop. Visual (e.g., color and shape) and spatial (i.e., loca-tion and orientation) information is held and manipulated in the visuospatial sketchpad.Cortical areas that are involved in visual perception (the occipital lobe) and spatial orient-ing (the parietal areas, especially the right parietal lobe) subserve the operations of thissketchpad (Farah, 1988; Jonides et al., 1993). Sounds, especially auditory speech sounds,are stored and processed by the phonological or articulatory loop, a term that empha-sizes its prototypical activity of recycling acoustic information to keep it activated. Morerecently, Baddeley and Wilson (2002) proposed a memory buffer mechanism responsiblefor integrating information between the phonological and visuospatial systems and storinginformation that exceeds the span capacities of the two subsystems. The neuroanatomicalcorrelates of this additional system have not been confirmed, but it seems that its functionsmight be dependent on the frontal lobe. This working memory buffer deploys effectiveorganization strategies (such as chunking) and pulls information from long-term memorystores that will assist with semantic processing and information manipulation and orga-nization into already known schemata or will create new schemata. Demanding workingmemory tasks that exceed the typical span of seven items (+ or – two items) and tasks thatrequire delayed recall after presentation will require active engagement of the buffer forsuccessful task completion. The supralist tasks implemented in the present study (basedon the aforementioned model) should engage active encoding strategies and the memorybuffer.

Studies of the capacity of working memory often use a task in which a sequence ofitems (e.g., letters or digits) is presented to a subject who must reproduce them immediatelyfrom memory in the correct order. The length of the longest sequence (in terms of numberof digits/letters) correctly produced, termed the letter or digit span, is an index of the sizeof short-term memory that some believe is correlated with IQ measures of intelligence(Kyllonen & Christal, 1990). However, others suggest that this span reflects the capacityof the phonological loop rather than the entire working memory system and the role of the

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phonological loop in general cognitive function has been called into question (Baddeley,1995; Conway et al., 2005; Unsworth & Engle, 2007). The phonological loop appears tobe necessary, however, for language acquisition, either the early childhood learning of anative language or multiple languages (Gathercole & Baddeley, 1990) or in adult learningof foreign languages (Baddeley, Papagno, & Vallar, 1988; Papagno, Valentine, & Baddeley,1991).

True working memory capacity of the executive network that has been shown torelate to higher cognitive functioning (Salthouse, 2005) is better measured by tasks thatrequire either dual-processing or inhibiting prepotent responses; both activities that arethe hallmark of flexible control of attention (Colflesh & Conway, 2007; Conway et al.,2005; Kane & Engle, 2002, 2003). Tests that measure static spans (e.g., forward spanof the Wechsler Adult Intelligence Scale [WAIS] or the Wechsler Memory Scale-III[WMS-III]) are dissociable from those that measure the more active processes involvedin attentional control such as digit span backwards and verbal learning paradigms likethe Rey Auditory Verbal Learning Test (AVLT) or the California Verbal Learning Test(CVLT) (Conway et al., 2005; Kane et al., 2004; Sander et al., 2007). In relation toBaddeley’s model, the aforementioned paradigms are demanding and require the recruit-ment of attentional resources to guide performance (i.e., executive system) as well as theactivation of the phonological loop. While the delayed-recall task does tap into long-termmemory (LTM), WM gets reactivated during the retrieval process from LTM becausethe individual is required to engage in retrieval strategies and to monitor retrieval accu-racy. The aforementioned multitrial tasks are able to assess the following: auditoryspan (initial recall trial), estimation of learning curve across the repeated presentationand recall trials, and the ability to maintain information in the presence of delay andcompeting information (Retroactive Interference). The present study implements com-plex multitrial verbal learning paradigms in order to explore WM performance in childrenwith RD.

Working Memory and RD

Kramer, Knee, and Delis (2000) used the California Verbal Learning Test-Children’sVersion (CVLT-C) to assess verbal learning in 57 children with reading disabilities and114 matched controls. Results suggested that participants with reading disabilities weredeficient in their ability to use efficient working memory strategies to learn new verbalmaterial in comparison to their control group participants. Participants with reading dis-abilities had lower recall performance, were more vulnerable to interference effects anddemonstrated a slower learning rate across all five learning trials. In addition, their recog-nition performance was impaired suggesting deficient encoding and poor retrieval skills incomparison to controls.

According to de Jong (1998) there is a strong relationship between WM capacity andearly reading acquisition for the following two reasons: First, for the emergent reader, worddecoding is a slow and effortful process since the conversion of graphemes to phonemeshas yet to become automatic. Working memory networks are engaged in the decoding pro-cess because grapheme-phoneme conversion rules need to be held in the working memorybuffer zone, while the remaining segments of the word are being processed. Moreover, oncethe grapheme-phoneme conversion has been completed, the resulting phonemes need to beheld in working memory so they can be blended effectively to produce the word. Based on

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Baddeley’s model, it could be argued that early reading depends on the central executivesystem of working memory and the phonological loop. Second, working memory affectsthe development of metalinguistic abilities, including phonological awareness, a primarydeterminant of early reading acquisition and a possible causal factor of reading disabilities.Since phonological awareness tasks (i.e., phoneme addition and phoneme deletion) requirethe simultaneous storage and manipulation of phonemes, they employ working mem-ory. Accordingly, working memory capacity can either facilitate or hinder early readingacquisition (Ramus, 2002).

The relationship between WM and reading abilities was also investigated byGathercole and Pickering (2001). Seven hundred and thirty-four children aged 4 to 15 yearswere tested using the Working Memory Test Battery for Children (WMTB-C), whichincluded four measures of the phonological loop, three measures of the visuospatial sketch-pad, and three verbal WM span measures believed to tap central executive resources.Of these children, a total of 98 children (13%) were identified by their schools as hav-ing learning difficulties in the areas of language and reading. These children performedpoorly in all areas of WM suggesting that WM plays a paramount role in the acquisition ofreading skills.

The connection between WM and early reading ability centers on the system’s capac-ity to process and store concurrent information (Montgomery et al., 2010). It appears thatgreater WM capacity enables children to read without imposing extensive demands on arestricted resource pool. As a result, children with a larger WM capacity would have moreresources available for storage while reading and comprehending a passage. Consequently,more information is processed and held for later retrieval (Just & Carpenter, 1992).Moreover, WM provides a buffer zone that allows the learner to integrate informationretrieved from long-term memory with new material being read. Essentially, poor work-ing memory capacity will compromise a child’s ability to carry out the aforementionedcognitive manipulations and to integrate old with newly learned information (Swanson &Beebe-Frankenberger, 2004; Swanson, 2003). Consequently, children with poor WM skillsmay have difficulties with learning activities requiring great demands on WM, thereby fail-ing to achieve normal incremental progress in complex academic domains such as readingand mathematics (Gathercole, Alloway, Willis, & Adams, 2006; Gathercole, Pickering,Ambridge, & Wearing, 2004; Gathercole, Tiffany, Briscoe, & Thorn, 2005).

Stimulus Modality and Working Memory

In addition to task complexity, stimulus presentation modality may affect workingmemory performance. Thompson and Paivio (1994) used a set of three different exper-iments to assess the relationship between stimulus modality presentation and workingmemory in free recall tasks. Stimulus lists consisted of (a) pictures, (b) correspondingenvironmental sounds, and (c) picture-sound pairs. Participants were 169 undergraduatestudents of the University of Western Ontario who were assigned to one of three con-ditions: (a) incidental learning condition, (b) intentional-distracter group, or (c) standard-intentional group. In the first condition (i.e., incidental learning), participants were requiredto count backwards by threes from a given number during the stimulus presentation withoutbeing told that they would have to later recall the stimuli presented. In the second condition(i.e., intentional-distracter), participants were told they would be tested for memory ofthe items presented and they were also asked to perform the distracter task. In the thirdcondition (standard-intentional), participants were aware of the upcoming memory test

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but unlike participants in the other two conditions they did not perform any distractertasks. As expected, recall was higher in the standard-intentional learning condition fol-lowed by the intentional-distracter condition. Moreover, recall in the picture-sound paircondition was significantly higher than the other two modality presentations (pictures andcorresponding environmental sounds) regardless of condition. According to the authors,these results suggest that auditory and visual information are mnemonically independentthus benefiting encoding and producing an additive effect, especially in the presence of adistracter task.

Research studies conducted by Constantinidou and Neils (1995), Constantinidou,Neils, Bourman, Lee, and Shuren (1996), Constantinidou (1999), Constantinidou andBaker (2002), and Constantinidou et al. (2011) demonstrated similar advantages for visualmodality presentation (and possible dual coding) in young adults with brain injuries, inneurologically normal adults, and in typically developing elementary school children.In the Constantinidou studies, a multitrial free recall paradigm was used, implementingthree different modality conditions: (a) auditory, (b) visual, and (c) simultaneous auditoryplus visual condition. Participants were presented with a target List A of 15 items in oneof the three modalities. After the fifth presentation of the list, participants were exposedto a distracter List B of 15 items, presented in the same stimulus modality as List A.Immediately after the presentation of List B, participants were asked to recall as manyitems as possible from List A (Trial 6). Thirty minutes after the last trial, during whichtime participants completed other neuropsychological tests, participants were again askedto recall as many items as possible from List A (Trial 7).

Results from these studies indicated that the simultaneous auditory-visual and thevisual presentation modality yielded better recall performance than the auditory stimulusmodality alone. No significant difference was found between visual and auditory-visualpresentations. Furthermore, presentation modality continued to affect performance in thedelay trials in a similar manner as the preceding learning trials. The authors concluded thatthe visual (pictorial) presentation of common objects results in superior learning, recall,and recognition performance (Constantinidou & Baker, 2002).

Even though studies link working memory deficits to RD, modality preferences havenot been explored in children with RD. The purpose of the present study is to assessthe effect of stimulus presentation modality (auditory, visual, auditory-visual) on verballearning, recall, and retrieval abilities in children with RD and in typically developing chil-dren (TDC). Results from this study can provide evidence on effective ways of presentinginformation to school-age children (with RD) in order to maximize verbal learning andworking memory performance. In addition to the experimental tasks and verbal memorymeasures, the study incorporated nonverbal memory and cognitive tasks and explored thelink between those measures and memory performance. Specifically, we hypothesized thatTDC and children with RD will perform better on complex working memory measuresand recall more items per learning trial during the pictorial presentation of information.Additionally, the pictorial presentation will result in better performance (as compared tothe auditory presentation alone) during short and long delay recall (recall after interference)for both TDC and children with RD. Furthermore, we hypothesized that there will be adifference in the verbal learning performance of children with RD during multitrial exper-imental tasks and standard memory measures such as the Auditory Verbal Learning Testas compared to TDC. Finally, children with RD would score lower than TDC on nonverbalcognitive tasks measuring memory, attention, and speed of information processing.

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METHODS

Participants

Participants were 40 elementary school-age children ages 10.50 to 12.25 years.Twenty participants were children diagnosed with RD and were receiving special educa-tion services at the time of participation in the study. The children with RD were diagnosedby the multidisciplinary team of the Republic of Cyprus Ministry of Education and Culture(MEC) consisting of a speech-language pathologist, a special educator, the classroomteacher, and an educational psychologist. According to procedures set by the MEC, ser-vices were provided based on the type of diagnosis and severity. All of our participantswith RD received special education services for their reading difficulties. Six (30%) of thechildren also received speech-language therapy for their concurrent verbal language diffi-culties; the rest of the children with RD did not have a history of communication disordersnor had they received speech-language services in the past. Children with a diagnosis ofmental retardation, psychiatric history (including depression or conduct disorder), neuro-logical history (such as epilepsy or traumatic brain injury), or attention deficit disorderwere excluded from the study.

The remaining participants were 20 typically developing age peers. Participants werematched on age, socioeconomic status, and general intellectual abilities. Children metstudy inclusion/exclusion criteria and had no history of psychiatric, neurological, or devel-opmental disorder. None of the typically developing children received specialized servicesor were ever on an individualized educational plan.

The group of children with RD consisted of 11 boys and 9 girls with an averageage of 11.5 years (SD = 5.07) and 5.40 years of education (SD = 0.502).The control groupconsisted of 9 boys and 11 girls with an average age of 11.6 years (SD = 5.70) and 5.6 yearsof education (SD = 0.502). There was no significant difference (α = .05) between the twogroups on age, t(38) = −0.440, p = .75, or years of education, t(38) = −1.258, p = .20.Additionally, the two groups were similar on indicators of socioeconomic status such asyears of maternal education, t(38) = 0.233, p = .817 (M = 14.50 years, SD = 1.98 for theTDC; M = 14.35 years, SD = 2.08 for the RD group), and years of paternal education,t(38) = 1.697, p = .098 (M = 16.15 years, SD = 2.81 for the TDC; M = 14.85 years,SD = 1.95 for the RD group). Participants in both groups were native speakers of Greek.The required institutional permissions and caregiver consent were obtained in order torecruit children for the study.

Procedures

In order to establish that participants in both groups had similar nonverbal cognitiveabilities, the Matrices subscale of the Cognitive Assessment Test (Papadopoulos, Georgiou,Kendeou, & Spanoudis, 2007) was administered. Participants in the two groups performedsimilarly on this nonverbal task, t(38) = 1.77, p = .85. Reading measures were alsoadministered to verify that the two groups differed in their reading abilities. Specifically,Maze 1, Maze 2, and Maze 3, Word attack, Word Identification, and Orthographic Choice(Papadopoulos, Georgiou, & Kendeou, 2009) were administered. As anticipated, childrenwith reading disabilities were deficient in their reading skills as compared to typicallydeveloping children (see Table 1 for group test scores).

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Table 1 Performance of Typically Developing Children (TDC) and Children with RD on NeuropsychologicalTests.

TDC RD

Test F(1, 38) p d power M (SD) (n = 20) M (SD) (n = 20)

Reading Tests

Maze 1 71.06 .000 .652 1.000 8.30 (2.13) 3.50 (1.40)Maze 2 50.29 .000 .570 1.000 7.50 (2.46) 3.00 (1.41)Maze 3 51.28 .000 .574 1.000 7.10 (2.15) 2.80 (1.61)Word ID in 60 sec 58.30 .000 .605 1.000 63.25 (7.92) 42.10 (9.52)Word attach in 60 sec 237.98 .000 .862 1.000 41.30 (3.15) 18.75 (5.73)Orthographic Score 21.66 .000 .363 .995 20.85 (4.75) 15.45 (2.09)

Verbal Language Tests

WISC similarities 11.10 .002 .226 .901 13.85 (4.02) 10.20 (2.80)WISC vocabulary 11.97 .001 .240 .921 24.85 (6.75) 18.10 (5.52)

Verbal Picture description

Number interpretiveconcepts

6.61 .014 .148 .708 5.65 (1.14) 4.60 (1.43)

Number literalconcepts

2.18 .148 .054 .301 7.80 (1.32) 7.05 (1.85)

Total concepts 8.82 .005 .188 .825 13.45 (2.04) 11.65 (1.78)

Attention and Memory Tests

Digits forward 1.76 .192 .044 .254 7.65 (.81) 7.05 (1.84)Digits backward 5.37 .026 .124 .618 5.35 (1.56) 4.05 (1.96)Digits Total 5.51 .024 .127 .629 13.00 (1.86) 11.20 (2.88)Spatial Span Forward 1.14 .292 .029 .181 8.30 (2.13) 7.60 (2.01)Spatial Span

Backward4.02 .052 .096 .498 6.75 (1.80) 5.65 (1.66)

Spatial Span Total 2.51 .121 .062 .340 15.00 (3.67) 13.30 (3.08)Figure reproduction

immediate11.23 .002 .228 .904 80.00 (6.37) 68.20 (14.40)

Figure reproductiondelayed

16.56 .000 .303 .977 53.40 (13.45) 38.00 (10.27)

Stroop 1 1.00 .324 .026 .164 40.00 (.00) 39.95 (.22)Stroop 2 2.92 .095 .071 .385 40.00 (.00) 39.80 (.52)Stroop 3 9.61 .004 .202 .856 40.00 (00) 38.45 (2.23)

Neuropsychological Tests. In addition to the above tests, a battery of widelyused standard language and cognitive paper and pencil measures was administered priorto the experimental task. The battery consisted of the following language, memory, andattention-executive measures:

1. Oral Verbal Tasks: (a) The Similarities and Vocabulary subtests of the WechslerIntelligence Scale for Children, third edition (Georgas, Paraskevopoulos, Bezevegis,& Giannitsas, 1997) was used to assess vocabulary knowledge; (b) Oral PictureDescription Task from the Boston Diagnostic Aphasia Examination (Goodglass &Kaplan, 2000). Participants were asked to make a story about the picture; the total

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number of concepts as well as the number of interpretive and concrete concepts werecalculated.

2. Verbal Working Memory: (a) Auditory Verbal Learning Test (AVLT; Lezak, 1983). Thismultitrial verbal learning paradigm is used to assess working memory. It provides infor-mation regarding a learning curve across five different presentation recall trials, theeffects of proactive and retroactive interference, and the ability to retain, to retrieve,and to recognize information after a 30-minute delay period; (b) Forward digit span(Wechsler Memory Scale III (WMS-III); Wechsler, 1997) to assess auditory attentionspan; (c) Backward digit span (WMS-III) to assess auditory working memory.

3. Nonverbal Working Memory: (a) Forward spatial span (WMS-III) to assess visual-spatial attention; (b) Backward spatial span (WMS-III) to assess visual-spatial workingmemory; (c) Design reproduction (WMS-III) for complex visual construction andimmediate and delayed visual memory.

4. Selective Attention-Executive Abilities: (a) Stroop Task (Trennery, Crosson, DeBoe, &Leber, 1989). The three Stroop tasks assess the ability to selectively attend to specificaspects of visual stimuli while ignoring irrelevant information. During Stroop Task 1,participants read a list of 40 words as fast as possible. In Stroop Task 2, they namethe colors of 40 small red, green, yellow, and blue colored blocks. For Stroop Task 3,participants name the color of the ink that the words were written in and filtered outthe actual word. For each of the tasks, measures of response accuracy and speed ofprocessing were obtained.

Experimental Tasks. In order to compare verbal learning and memory per-formance under three different modalities the Stimulus Modality Task described inConstantinidou and Baker (2002) was used. The original items by Constantinidou andBaker were translated and adapted into Greek and have been used in studies with Greek-Cypriot patients with epilepsy (Constantinidou, Papacostas, Nicou, & Themistocleous,2008).

The items in each list were chosen based on criteria that have been documented toaffect memory and word retrieval and therefore were highly familiar and concrete (i.e.,simple nouns that can be easily depicted as line drawings). The experimental items con-sisted of 144 stimuli that were randomly assigned to three modalities: (a) auditory, (b)visual, (c) auditory plus visual (see Appendix A). Each modality consisted of target ListA and List B. Under the auditory condition participants listened to the words, under thevisual condition participants viewed the line drawings representing the words (presentedon a computer screen), and under the auditory-plus-visual condition participants viewedthe pictures and listened to the words simultaneously.

Experimental Procedure

The study followed a multitrial paradigm similar to that used in the AVLT and otherverbal learning tasks. At the beginning of each condition, participants were given one prac-tice trial. After the practice trial, a target list (List A) was presented five times. The subjectwas asked to recall the items from List A after each presentation.

An interference list of 15 items (List B) was presented as Trial 6. The items in List Bwere presented using the same stimulus modality (auditory, visual, or auditory plus visual)as List A. For example, after five visual presentations of List A, List B was presentedvisually. Immediately following the presentation of List B, the participant was asked to

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recall as many items as possible from List A (Trial 6, Short Delay). Participants were askedto recall as many items from List A after a thirty-minute delay (Trial 7, Long Delay).

After Trial 7, the participants were presented with a recognition task. The list ofitems for the recognition task contained all 15 items from List A and all 15 items fromList B as well as 20 foils; five semantically and five phonetically linked to each of the twoLists (A and B). Participants were asked to indicate via a yes-no response as to whether theitem presented belonged in List A. Items in the recognition list were presented in the samestimulus modality as Lists A and B.

Different lists of 15 items (from the original 45) were used under each condi-tion. Each list was equivalent according to the selection criteria for the items. The orderof the modality condition was counterbalanced to avoid any order effects. Six differentorders were administered for the experimental trials. Participant 1 received the first order,Participant 2 received the second order, Participant 3 received the third order and so on.The same cycle was repeated after the sixth participant.

In order to avoid order effects within the lists, all items of List A and List B werererandomized to create three different forms of List A and List B. One third of the studyparticipants received Form 1, another third Form 2, and the remaining third receivedForm 3. The appendix contains the experimental items.

RESULTS

The purpose of the present study was to assess the effects of stimulus modality pre-sentation (auditory, visual, auditory plus visual) on verbal learning recall and retrieval in agroup of children with reading disabilities and in typically developing children. A multi-variate mixed-model design was implemented in order to compare the two subject groupson three presentation modalities (α = .05).

The Effects of Modality Presentation

The multivariate analysis resulted in a significant overall main effect for modali-ties, F(2, 37) = 44.077, p = .0001, power = 1.0, ηp

2 = .704; trials, F(4, 35) = 101.945,p = .0001, power = 1.0, ηp

2 =.921; and groups, F(1, 38) = 18.334, p = .0001, power= .986, ηp

2 = .853. In order to identify which modalities contributed to the significantmultivariate modality effect, preplanned orthogonal comparisons were used (Helmert con-trasts, alpha level set at .025). The first Helmert contrast compared the auditory modalityto visual and simultaneous auditory-plus-visual modalities. The comparison resulted in asignificant univariate effect, F(1, 38) = 90.498, p = .0001, power = 1, ηp

2 = .704. Thesecond Helmert contrast comparing the visual modality to the simultaneous auditory-plus-visual modality was not significant, F(1, 38) = .903, p = .348. These results suggest thatthe visual and auditory-plus-visual presentations resulted in improved recall performanceas compared to the auditory modality alone, for both groups of participants.

The main effect for trials indicates that both groups of participants recalled morewords during each repeated presentation and recall trial. The group main effect demon-strates that TDC recalled overall more words compared to children with RD. In additionto the main effects, the analyses yielded the following significant interactions: groups bytrials, F(4, 152) = 4.551, p = .004, ηp

2 = .150, modalities by trials, F(8, 31) = 3.215, p =.009, power = .919, ηp

2 = .453, and modalities by trials by groups, F(8, 31) = 3.621, p =.004, power = .950, ηp

2 = .483. The group by trials interaction indicates that the pattern

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of word recall across the five learning trials was different between the two groups. Theunivariate contrast for the groups by trials interaction identified a linear trend, F(1, 38) =5.050, p = .031; TDC had a faster learning rate than children with RD. Table 2 displaysthe marginal means for each group per trial across modalities. Figure 1 is the profile plotof the group by trial interaction.

The modalities-by-trials interaction indicates that the patterns of performance (acrossthe five learning trials) differed among modalities. Univariate preplanned contrasts identi-fied a cubic pattern of performance with accelerated learning during Trials 3 and 4 of thevisual modality, F(1, 38) = 7.021, p = .012. The threefold modalities by trials by groupsinteraction is a result of the aforementioned two-way interactions suggesting that the rate oflearning across modalities differed among groups and that the visual presentation resultedin better performance. Typically developing children performed better across modalitiesand learned faster across trials than children with reading disabilities. Table 3 is the meanfor each trial per group per modality. Figure 2 is the graphic display of the modality bytrials interaction.

Table 2 Estimated Marginal Means for Each Group for Each Trial across Modalities.

Typically Developing Children Children with RD

Mean SD Mean SD

Trial 1 7.17 0.28 5.98 1.31Trial 2 8.90 1.41 7.23 1.72Trial 3 10.08 1.54 8.38 2.05Trial 4 10.88 1.36 8.91 2.01Trial 5 11.41 1.37 9.38 1.92

Estimated Marginal Means 9.69 7.98

12.00

10.00

8.00

Esti

ma

ted

Marg

inal M

ean

s

6.00

1 2 3

Learning Trails

1-TDC 2-RD

1.00

2.00

4 5

Figure 1 Profile plot and mean scores for each group under Trials 1–5 demonstrating the group by trialsinteraction effect.

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Tabl

e3

Est

imat

edM

argi

nalM

eans

for

Eac

hG

roup

for

Eac

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rial

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ssM

odal

ities

.

12

34

5To

tal

Lis

tBT

6T

7

Aud

itor

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ials

Typi

cally

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ng(n

=20

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6.15

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SD0.

881.

661.

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251.

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(n=

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141.

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12

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11.00

10.00

9.00

8.00

7.00

6.00

5.00

1 2 3

Trials

4 5

mods

1 = Auditory

2 = Visual

3 = Auditory & VisualE

sti

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ted

Marg

inal M

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s

Figure 2 Profile plot of the modality by trials by interaction effect.

Short-Delay and Long-Delay Recall

Participants’ performance in the short-delay (SD) and long-delay (LD) recall con-ditions was assessed by comparing the results of Trial 5, Trial 6, and Trial 7 of theverbal learning paradigm. A mixed-model multivariate analysis of variance was performed(α = .05) to determine the effects of interference and the effect of modality presentation onSD and LD recall performance. The two within factors were the stimulus modalities andrecall trials (Trial 5, Trial 6 [SD], and Trial 7 [LD]). Consistent with previous results,the analyses resulted in a significant modalities effect, F(2, 37) = 25.56, p = .0001,power = 1, ηp

2 = .580, suggesting that participants’ short-delay and long-delay recallresults were impacted by presentation modality. In order to identify which modalities con-tributed to the significant multivariate modality effect, preplanned orthogonal comparisonswere used (Helmert contrasts, alpha level set at .025). The first Helmert contrast com-pared the auditory modality to visual and simultaneous auditory-plus-visual modalities.The comparison resulted in a significant univariate effect, F(1, 38) = 51.38, p = .0001,power = 1, ηp

2 = .575. The second Helmert contrast compared the visual modality tothe simultaneous auditory-plus-visual modality. The comparison did not reach statisticalsignificance F (1, 38) = 0.41, p = .526, power = .096. These results suggest that the visualand auditory-plus-visual presentation resulted in better performance during the delayedconditions as compared to the auditory modality alone, for both groups of participants.

The mixed-model MANOVA also showed significant trials, F(2, 37) = 24.58,p = .0001, power = 1, ηp

2 = .571,and group effects, F(1, 38) = 27.878, p = .0001, power= .999, ηp

2 = .423. The main effect for trials indicates that the performance declinedacross delayed conditions. The pattern of decline followed a linear trend, F(1, 38) = 45.94,

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11.00

10.00

12.00

9.00

8.00

1 2

Trials

3

1-TDC 2-RD

1.00

2.00

Esti

ma

ted

Marg

inal M

ean

s

1 = Trial 5 3 = Long Delay2 = Short Delay

Figure 3 Profile plot per group for Trial 5, short delay, and long delay demonstrating the group by trialsinteraction effect.

p = .001. The main effect for groups demonstrates that, overall, children with RD recalledfewer items across the delayed conditions as compared to the TDC. Figure 3 is the groupby trials (delay) effect.

In addition to the main effects, the mixed-model analysis of variance also showed asignificant modalities by group interaction, F(2, 37) = 3.52, p = .040, power = .621, ηp

2

= .160 and a significant threefold modality by trials by group interaction, F(4, 35) = 4.77,p = .004, power = .923, ηp

2 = .353. Univariate within-subjects contrasts indicate that thevisual modality effect was greater for participants with RD as compared to the TDC group,F(1, 38) = 7.22, p = .001, ηp

2 = .160.

Recognition Results

Following the long-delay recall trial (Trial 7) participants completed a forced-choicerecognition trial where they had to recognize from a list of 50 items which items belongedto target List A. The recognition score was calculated by subtracting the Trial 7 score(LD) from the recognition score (false positives). A mixed-model analysis of variancewas performed that resulted in a significant, group effect, F(1, 38) = 26.393, p = .0001,ηp

2 = .410, power = .999, and modalities effect, F(2, 37) = 17.63, p = .0001, ηp2 =

.488, power = 1.0, suggesting that participants with LD scored lower than TDC and thatrecognition results were impacted according to the presentation modality. Results frompreplanned orthogonal comparisons (Helmert contrasts, alpha level set at .025) indicatedthat the auditory modality was statistically significantly different from the visual modal-ity and the combined auditory-plus-visual modality, F(1, 38) = 36.21, p =.0001, ηp

2 =.488, power = 1.0. No significant differences were found between the visual modality and

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the combined auditory-plus-visual modality, F(1, 38) = 0.462, p = .501, power = .102.The gain in recognition performance under the auditory modality can be attributed to thefact that the free recall score was lower under the auditory presentation (during the LDcondition) as compared to the visual modalities. Therefore, the forced-choice recognitionparadigm enhanced word retrieval during the auditory modality performance resulting in ahigher difference score as compared to the visual modalities.

The recognition paradigm consisted of 15 words of List A, the 15 words of ListB, and 20 words phonetically or semantically related to Lists A and B. The number offoils falsely recognized (e.g., the subject indicated with a “yes” that the foil was part ofList A) was obtained for each subject for each of the experimental conditions and theAVLT. Because of the low number of false positives in each group (performance rangedfrom 0.15 to 1.0), a nonparametric procedure was used. The Mann-Whitney U analyses forindependent measures (Bonferroni α/k = .01) compared the two groups on the total num-ber of foils recognized during each of the experimental conditions. The p value reportedis approximated from the z statistic. There were no significant group differences acrossthe auditory, visual, or auditory-plus-visual modalities (p = .989, p = .883, and p = .429,respectively).

Neuropsychological Test Results

Apart from the experimental items, participants in both groups were administereda number of common formal neuropsychological tests in order to assess various aspectsof cognition relating to memory and verbal learning. Univariate analyses (α = .05) com-paring the two groups on these neuropsychological tests indicated that the performance ofthe two groups was significantly different across a number of tests examining language,memory, and executive functions, including nonverbal working memory tasks such as theRey Complex Figure Test (immediate and delayed recall conditions).

The AVLT, similar to the experimental modalities test, assessed auditory verbal learn-ing. A mixed-model MANOVA resulted in a significant trials effect, F(4, 35) = 55.17,p = .000, ηp

2 = .863, power = 1, and a significant between groups difference, F(1, 38) =23.173, p = .0001, ηp

2 = .379, power = .997. Furthermore, there was a significant groupby trials interaction indicating that the rate of learning across the five trials was differentbetween the two groups; the TDC had a faster rate of learning than children with RD, F(4,35) = 3.869, p = .010, ηp

2 = .307, power = .853. The average per trial for the TDC was9.010 words as compared to 6.85 words for children with RD. Table 4 displays the recallscore per trial for each group.

Correlations between Experimental Tasks, Neuropsychological

Measures, and Reading Measures

Three groups of Pearson correlation analyses were conducted to examine relation-ships between experimental tasks, neuropsychological measures, and reading measures.The first group determined the relationship between the experimental tasks and stan-dardized verbal learning tasks. Results indicated that there were strong and significantcorrelations (Bonferroni α/k = .012) between the AVLT total score, and the total scoresof the three experimental modalities (Auditory, r = .946, Visual, r = .861, and simulta-neous Auditory-Visual modality, r = .838). As anticipated, the auditory modality had thehighest correlation with the AVLT because both are auditory verbal learning tasks. Both,

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Table 4 Estimated Marginal Means for each Group for each AVLT Trial.

Typically Developing Children Children with RD

Mean SD Mean SD

Trial 1 5.55 1.39 4.80 1.28Trial 2 8.0 1.65 5.7 1.86Trial 3 9.45 1.53 7.20 1.90Trial 4 10.60 1.50 7.85 2.18Trial 5 11.45 2.03 8.70 2.25

Estimated Marginal Means 9.10 6.85

the AVLT and the experimental tasks incorporate supraspan tasks consisting of unrelateditems. Success on these measures requires the implementation of active memory strategiesand internal organization techniques that facilitate information storage and retrieval.

The second group of analyses examined the relationship between reading, workingmemory measures, and the Matrices (general cognitive nonverbal abilities task). Moderatesignificant correlations were found (Bonferroni α/k = .005). As depicted in Table 5, theMatrices score correlated with all the three Maze scores, the AVLT total score, digit spanand visual span scores, and the design reproduction scores. The vocabulary scores alsocorrelated significantly with the Maze scores and with a few of the memory measures suchas the AVLT and the digits total score.

The third group of correlational analyses was performed to examine the relation-ship between standardized working memory tests and reading measures. Some workingmemory measures correlated (moderately strong) with the reading measures (Bonferroniα/k = .001). Specifically, there was a moderate-strong significant correlation between theMaze scores and the AVLT performance and moderate correlation with the digits back-wards tasks. Mazes 1 and 2 also correlated significantly with the digit backwards and totalbackwards scores. Partial correlations between reading and memory measures were con-ducted with the Matrices score as a control variable. All three Maze scores were againmoderately and significantly (α = .01) correlated with the total AVLT score (r = .486,p = .001; r = .497, p = .001; and r = .453, p = .001, respectively). Furthermore,the Maze 2 score was significantly correlated with the digits backwards score, r = .358,p = .013. These results are in line with the notion that working memory relates to readingperformance. Table 5 displays the correlations.

DISCUSSION

Stimulus Modality and Verbal Learning

The primary purpose of the study was to determine whether one of the three modal-ity conditions (auditory, visual, auditory & visual) would result in better verbal learningand recall performance in children with reading disabilities and typically developing chil-dren. It was hypothesized that stimulus presentation would influence working memoryperformance in these verbal learning tasks.

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Tabl

e5

Cor

rela

tions

betw

een

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Tabl

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The present results support the modality presentation hypothesis because all par-ticipants recalled more items under the visual condition. The visual superiority was alsoevident in the short- and long-delay recall trials. Subjects recalled more items during thevisual and the simultaneous auditory-plus-visual conditions versus the auditory condition.There was no difference between the visual condition and the simultaneous auditory andvisual condition.

The pictorial superiority effect observed in the present study with Greek-speakingchildren with RD and in TDC is consistent with our previous findings with English-speaking, TDC children (Constantinidou et al., 2011). Therefore, the visual modalitybenefit seems to be independent of the syllabic structure and word length. All of the Greekwords in the present study consisted of two to four syllables; in contrast, all of our previousstudies in this area incorporated monosyllabic English words.

Verbal learning (as measured in this study) required the use of working memorymechanisms and particularly active engagement of the phonological loop coupled withexecutive system processes. Based on the dual code theory, when experimental items werepresented visually, the visuospatial sketchpad enhanced the work of the phonological loopand the executive system and, therefore, facilitated performance. It is possible that thevisual presentation of common objects prompted participants, at a subconscious level, toname the objects (subvocally) based on the premise that, during memory tasks, individ-uals assign a lexical meaning to objects (unless they are abstract and nonsense stimuli)(Lezak, 1995). This subvocal naming may have resulted in deeper semantic processingas suggested by Craik and Lockhart (1972). Consequently, visual (pictorial) presentationwas adequate for dual coding and therefore the external auditory input was superfluousand hence hearing the name of the picture added nothing more in the learning process(Constantinidou et al., 1996, 2011).

The present study implemented highly imageable and concrete concepts that wereaccurately depicted as line drawings. It is possible that in multitrial verbal learning tasksconsisting of abstract visual stimuli, which could not be accurately depicted and could notautomatically generate a subvocal naming of the stimulus, the addition of the simultaneousauditory presentation of the name could provide additional perceptual features (from theauditory code) and could trigger a multimodal additive effect in line with the Thomson andPaivio (1994) theory.

Working Memory and Reading Disabilities

Another study hypothesis stated that children with reading disabilities would performworse than their typically developing cohorts on working memory tests. During verballearning tasks, participants with reading disabilities were able to learn new items duringeach subsequent learning trial. However, the number of words per trial was significantlydifferent between the two groups and the slope of learning diverged with successive trials.This finding is in line with existing literature linking WM capacity and RD and suggestingthat WM capacity in children with reading disabilities is impaired as compared to the work-ing memory capacity of TDC (Baddeley, 1986, 1990; Gathercole et al., 2006; Gathercole& Baddeley, 1993; Kirby, Marks, Morgan, & Long, 2004; Kramer et al., 2000; Swanson &Berninger, 1995).

Moreover, participants with RD consistently demonstrated lower delayed recall andrecognition performance as compared to their typically developing age peers. The perfor-mance of children with RD was affected by retroactive interference as demonstrated by

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a reduction during the short-delay and long-delay recalls. Delayed recall performance forchildren with RD was better during the pictorial presentation of information. Furthermore,children with RD demonstrated superior recognition performance in forced-choice tasks(as compared to their delayed free recall score) suggesting that part of their memorydeficiencies relate to encoding and retrieval problem versus storage difficulties.

In addition to the AVLT and the experimental verbal learning task, the two groupswere different in other memory measures such as immediate and delayed figure repro-duction (suggesting deficits in the visual-spatial sketchpad, part of Baddeley’s workingmemory model) and backward digit recall (suggesting deficits in the interaction of thecentral executive and the phonological loop). Moreover, children with reading disabilitiesperformed differently on executive functioning tasks as measured by reduced organizationand increases in processing time compared to typically developing children. Perhaps thedecline in visual-spatial abilities was a result of increase in processing time that resultedin a decline in the working memory buffer capacity, rather than specific difficulties invisual-spatial memory.

Research shows that English-speaking children with reading disabilities usually tendto do better than typically developing children on the third Stroop task, where they haveto selectively attend to the color of the letters in the word and not the word itself per se(August & Garfinkel, 1990; Lufi, Cohen, & Parish-Plass, 2006; Willcutt et al., 2001). Ourresults, however, have not shown such a pattern of performance because the performanceof children with RD on the Stroop 3 was low. It is possible that this difference may bedue to differences between English and Greek orthography. The English written languagesystem is characterized by deep orthographic structure. However, the Greek orthographicsystem follows closely the phonological system and perhaps makes it more difficult forchildren with RD to inhibit the written words and to focus on the color of the word asthe task requires, resulting in declines in both speed and accuracy. Future research shouldreplicate these findings with a larger pool of participants.

The present results support the existence of a working memory deficit in childrenwith reading disabilities. The left occipito-temporal region and associated networks playan important role for the phonological aspects of language, early reading acquisition, andworking memory (Shaywitz et al., 2004; Swanson, Zheng, & Jerman, 2009). The find-ings from this study suggest that the visual presentation modality provided extra supportto children with RD and perhaps facilitated executive control and processing of verbalmaterial in WM. Visual materials in the form of simple pictures can reduce the burden ofprocessing verbal material since children with RD in the present study also demonstratedslower speed of processing in comparison to TDC. Therefore, incorporating visual aids inthe form of pictures, diagrams, concept maps, and sketches (consisting of simple, clear,and salient information) could enhance classroom learning for students with RD and TDC.For children with RD visual aids in the form of simple pictures along with systematiccognitive strategies and direct instruction as suggested by previous literature could maxi-mize improvement (Swanson & Hoskyn, 1998). The use of simple drawings could also behelpful during language learning tasks during speech-language therapy since several chil-dren with RD also experience language difficulties and are treated by a speech-languagepathologist.

The findings of the present study are in line with the notion that working memoryrelates to reading performance. Additionally, general cognitive efficiency, working mem-ory capacity, and reading efficiency do share some common variance but cannot be used as

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accurate predictors of performance as a large percentage of variance remains unaccountedand is mediated by other factors.

Limitations and Future Research

This was an exploratory study consisting of a small homogenous sample of childrenwith reading disabilities. Future studies should incorporate a larger and more diverse groupof participants to replicate the present findings. Children from various socioeconomic strataand regions should be included. Furthermore, future studies with larger sample sizes mayincorporate subgroups of children with RD who have frequently occurring comorbidities(such as oral language deficits and attention deficit/hyperactivity disorder) in order to iden-tify different patterns of performance. For example, it would be interesting to determinehow variation in language performance impacts both reading performance and also work-ing memory abilities (or the reverse relationship). In the current study, vocabulary scoreswere correlated with verbal learning abilities.

Another suggestion for future studies is the modification of the experimental tasksand the creation of new lists that can be analyzed for semantic clusters or categories aswell as the inclusion of abstract items that cannot be easily depicted. This would provideinformation about the effects of modality preferences, semantic clustering, and possibleinteractions between these two variables in respect to working memory.

CONCLUSION

Contemporary models of reading disabilities have proposed a multidimensionalapproach to the disorder where the neurobiology, core cognitive processes (such as mem-ory), and the environment interact and contribute to the presentation and the subtypes ofthe disorder. Working memory has been the focus of extensive research because it is a pre-requisite for successful verbal language and reading attainment. Findings from the currentproject demonstrate that children with reading disabilities have impaired working memoryabilities when compared to same age typically developing children. Consequently, infor-mation should be presented in a modality that best facilitates learning and retrieval, therebycompensating somewhat for working memory deficiencies. The present study supports theuse of simple pictures during verbal memory activities. In addition, cognitive trainingin children with reading disabilities should incorporate working memory strategies thatinclude organization of target information to facilitate learning and recall performance.Furthermore, the diagnostic workup could incorporate demanding working memory taskssuch as the AVLT or the CVLT to thoroughly assess verbal learning abilities.

Original manuscript received May 4, 2011Revised manuscript received June 13, 2011

REFERENCES

August, G. J., & Garfinkel, B. D. (1990). Comorbidity of ADHD and Reading disabilities amongclinic-referred children. Journal of Abnormal Child Psychology, 18(1), 29–45.

Baddeley, A. D. (1986). Working memory. Oxford, UK: Oxford University Press.

Dow

nloa

ded

by [

Fofi

Con

stan

tinid

ou]

at 1

0:35

26

Sept

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11


Baddeley, A. D. (1990). Human memory: Theory and practice. Hove, UK: Lawrence ErlbaumAssociates Ltd.

Baddeley, A. D. (1995). Working memory. In M. S. Gazzaniga (Ed.), The cognitive neurosciences(pp. 755–764). Cambridge, MA: MIT Press.

Baddeley, A. D. (2000). The episodic buffer: A new component of working memory? Trends inCognitive Sciences, 4, 417–423.

Baddeley, A. D. (2001). Is working memory still working? American Psychologist, 56(11), 851–863.Baddeley, A. (2003). Working memory and language: An overview. Journal of Communication

Disorders, 36, 189–208.Baddeley, A. D., & Hitch, G. (1974). Working memory. In G. A. Bower , The psychology of learning

and motivation (Vol. 8, pp. 47–89). New York, NY: Academic Press.Baddeley, A., Papagno, C., & Vallar, G. (1988). When long-term learning depends on short-term

storage. Journal of Memory and Language, 27(5) 586–595.Baddeley, A. D., & Wilson, B. A. (2002). Prose recall and amnesia: Implications for the structure of

working memory. Neuropsychologia, 40, 1737–1743.Berninger, V. W., Abbott, R. D., Swanson, H. L., Lovitt, D., Trivedi, P., Lin, S. J., et al. (2010).

Relationship of word-and sentence-level working memory to reading and writing in second,fourth, and sixth grade. Language, Speech, and Hearing Services in Schools, 41, 179–193.

Colflesh, G., & Conway, A. (2007). Individual differences in working memory capacity and dividedattention in dichotic listening. Psychonomic Bulletin, & Review, 14, 699–703.

Constantinidou, F. (1999). The effects of stimulus modality on interference and recognition perfor-mance following brain injury. Journal of Medical Speech-Language Pathology, 7, 283–295.

Constantinidou, F., & Baker, S. (2002). Stimulus modality and verbal learning performance in normalaging. Brain and Language, 82, 296–311.

Constantinidou, F., Danos, S., Nelson, D., & Baker, S. (2011). Effects of modality presentation onworking memory in school-age children: Evidence for the pictorial superiority hypothesis. ChildNeuropsychology, 17(2), 173–196.

Constantinidou, F., & Neils, J. (1995). Stimulus modality and verbal learning after moderate to severeclosed head injury. Journal of Head Trauma Rehabilitation, 10, 90–100.

Constantinidou, F., Neils, J., Bouman, D., Lee, L., & Shuren, J. (1996). Pictorial superiority duringverbal learning tasks in moderate to severe closed head injury: Additional evidence. Journal ofGeneral Psychology, 123, 173–184.

Constantinidou, F., Papacostas, S., Nicou, M., & Themistocleous, D. (2008). The effects of chronicepilepsy on neuropsychologic performance and quality of life. Archives of Physical Medicineand Rehabilitation, 89(10), e25.

Conway, A., Kane, M., Bunting, M., Hambrick, D., Wilhelm, O., & Engle, R. (2005). Workingmemory span tasks: A methodological review and user’s guide. Psychonomic Bulletin & Review,12, 769–786.

Craik F. I. M., & Lockhart, R. S. (1972). Levels of processing: A framework for memory research.Journal of Verbal Learning and Verbal Behavior 11, 672–684.

Cummings, J. L., & Mega, M. S. (2003). Neuropsychiatry and behavioral neuroscience. New York,UK: Oxford University Press.

de Jong, P. F. (1998). Working memory deficits of reading disabled children. Journal of ExperimentalChild Psychology, 70, 75–96.

Egeland, J., Landro, N. I., Sundet, K., Asbjornsen, A., Lund, A., Roness, A., et al. (2005). Validationof distinct amnestic and executive type memory deficit in a psychiatric sample based on retrievalperformance. Scandinavian Journal of Psychology, 46, 201–208.

Farah, M. J. (1988). Is visual imagery really visual? Overlooked evidence from neuropsychology.Psychological Review, 95, 307–317.

Gathercole, S. E., & Baddeley, A. D. (1990). Phonological memory deficits in language disorderedchildren: Is there a causal connection? Journal of Memory and Language, 29, 336–360.

Dow

nloa

ded

by [

Fofi

Con

stan

tinid

ou]

at 1

0:35

26

Sept

embe

r 20

11


Gathercole, S. E., & Baddeley, A. D. (1993). Working memory and language. Hove, UK: LawrenceErlbaum Associates Ltd.

Gathercole, S. E., & Pickering S. J. (2001). Working memory deficits in children with specialeducational needs. British Journal of Special Education, 28, 89–96.

Gathercole, S. E., & Pickering S. J. (2004). Distinctive working memory profiles in children withspecial education needs. Educational Psychology, 24(3), 393–408.

Gathercole, S. E., Pickering S. J., Ambridge, B., & Wearing, H. (2004). Working memory skills andeducational attainment: Evidence from national curriculum assessments at 7 and 14 years ofage. Developmental Psychology, 40, 177–190.

Gathercole, S. E., Tiffany, C., Briscoe, J., & Thorn, A. (2005). Developmental consequences of poor-phonological memory function in childhood. Journal of Child Psychology and Psychiatry, 39,3–27.

Gathercole, S. E., Alloway, T. P. Willis, C., Adams, A. M. (2006). Working memory in children withreading disabilities. Journal of Experimental Child Psychology 93, 265–281.

Georgas, D. D., Paraskevopoulos, I. N., Bezevegis, I. G., & Giannitsas, N. D. (1997). Greek WISC-III:Wechsler Intelligence Scale for Children. Athens, Greece: Ellinica Grammata.

Goodglass, H., Kaplan, E., & Barresi, B. (2000). Boston Diagnostic Aphasia Examination (3rd ed.).San Antonio, TX: The Psychological Corporation.

Jonides, J., Smith, E. E., Koeppe, R. A., Awh, E., Minoshima, S., & Mintun, M. A. (1993). Spatialworking memory in humans as revealed by PET. Nature, 363, 623–625.

Just, M. A., & Carpenter, P. A. (1992). A capacity theory of comprehension: Individual differencesin working memory. Psychological Review, 99, 122–149.

Kane, M. J., & Engle, R. W. (2002). The role of prefrontal cortex in working-memory capac-ity, executive attention, and general fluid intelligence: An individual-differences perspective.Psychonomic Bulletin & Review, 9, 637–671.

Kane, M. J., & Engle, R. W. (2003). Working-memory capacity and the control of attention: Thecontributions of goal neglect, response competition, and task set to Stroop interference. Journalof Experimental Psychology: General, 132, 47–70.

Kane, M., Hambrick, D., Tuholski, S., Wilhelm, O., Payne, T. W., & Engle, R. W. (2004). Thegenerality of working memory capacity: A latent variable approach to verbal and visuospatialmemory span and reasoning. Journal of Experimental Psychology: General, 133, 189–217.

Kirby, M. Y., Marks, W., Morgan, S., & Long, C. J. (2004). Specific impairments in developmen-tal reading disabilities: A working memory approach. Journal of Learning Disabilities, 37,349–363.

Kramer, J. H., Knee, K., & Delis, D. C. (2000). Verbal memory impairments and dyslexia. Archivesof Clinical Neuropsychology, 15(1), 83–93.

Kyllonen , P. C., & Christal, R. E. (1990). Reasoning ability is (little more) than working memorycapacity. Intelligence, 14, 389–433.

Lezak, M. D. (1983). Neuropsychological assessment (2nd ed.). New York, NY: Oxford UniversityPress.

Lezak, M. D. (1995). Neuropsychological assessment (3rd ed.). New York, NY: Oxford UniversityPress.

Lufi, D., Cohen, A., & Parrish-Plass, J. (2006). Identifying ADHD with the WISC-R and the StroopColor and Word Test. Psychology in Schools, 27(1), 28–34.

MacDonald, M. C., & Christiansen, M. H. (2002). Reassessing working memory: Comment on Justand Carpenter (1992) and Waters and Caplan (1996). Psychological Review, 109(1), 35–54.

Montgomery, J. W., Magimairaj, B. M., & Finney, M. C. (2010). Working memory and specificlanguage impairment: An update on the relation and perspectives on assessment and treatment.American Journal of Speech-Language Pathology, 19, 78–94.

Dow

nloa

ded

by [

Fofi

Con

stan

tinid

ou]

at 1

0:35

26

Sept

embe

r 20

11


Papadopoulos T. C., Georgiou, K. G., & Kendeou, P. (2009). Investigating the double-deficit hypoth-esis in Greek: Findings from a longitudinal study. Journal of Learning Disabilities, 42(6),528–547.

Papadopoulos, T. C., Georgiou, K. G., Kendeou, P., & Spanoudis, G. (2007). Greek Das – NaglieryCognitive Assessment System (CAS). Nicosia, Cyprus: Department of Psychology, University ofCyprus.

Papagno, C., Valentine, T., & Baddeley, A. (1991). Phonological short-term memory and foreign-language vocabulary learning. Journal of Memory and Language, 30(3), 331–347.

Ramus, F. (2002). Outstanding questions about phonological processing in dyslexia. Dyslexia, 7(4),197–216.

Salthouse, T. A. (2005). Relations between cognitive abilities and measures of executive functioning.Neuropsychology, 19, 532–545.

Sander, A. M., Richardson, R., Constantinidou, F., Wertheimer, J., & Paul, D. (2007). Memoryassessment on an interdisciplinary rehabilitation team: A theoretically based framework.American Journal of Speech-Language Pathology, 16, 316–330.

Shaywitz, B. A., Shaywitz, S. E., Blachman, B. A., Pugh, K. R., Fulbright, R. K., Skudlarski, P.,et al. (2004). Development of left occipitotemporal systems for skilled reading in children aftera phonologically-based intervention. Biological Psychiatry, 55, 926–933.

Swanson, H. L. (1992). Generality and modifiability of working memory among skilled and lessskilled readers. Journal of Educational Psychology, 85, 1–31.

Swanson, H. L. (2003). Age-related differences in learning disabled and skilled-readers’ workingmemory. Journal of Experimental Child Psychology, 84, 473–488.

Swanson, H. L., & Beebe-Frankenberger, M. (2004). The relationship between working memory andmathematical problem solving in children at risk and not at risk for serious math difficulties.Journal of Educational Psychology, 96(3), 471–491.

Swanson, H. L., & Berninger, V. W. (1995). The role of working memory in skilled and less skilledreaders’ comprehension. Intelligence, 21, 83–108.

Swanson, H. L., & Hoskyn, M. (1998). Experimental intervention research on students with learningdisabilities: A metal-analysis of treatment outcomes. Review of Educational Research, 86(3),277–321.

Swanson, H. L., & Jerman, O. (2007). The influence of working memory in reading growth in sub-groups of children with reading disabilities. Journal of Experimental Child Psychology, 96,249–283.

Swanson, H. L., & Zheng, X. (2009). Working memory, short-term memory, and reading disabilities:A selective meta-analysis of the literature. Journal of Learning Disabilities, 32(1), 260–287.

Swanson, H. L., Zheng, X., & Jerman, O. (2009). Working memory, short-term memory, and readingdisabilities: A selective meta-analysis. Journal of Learning Disabilities, 42, 260–287.

Thompson, V., & Paivio, A. (1994). Memory for pictures and sounds: Independence of auditory andvisual codes. Canadian Journal of Experimental Psychology, 48(3), 380–396.

Trennery, M., Crosson, B., DeBoe, J., & Leber, W. (1989). Stroop Neuropsychological ScreeningTest manual. Odessa, FL: Psychological Assessment Resources (PAR).

Unsworth, N., & Engle, R. W. (2007). The nature of individual differences in working memory capac-ity: Active maintenance in primary memory and controlled search from secondary memory.Psychological Review, 114, 104–132.

Waters, G. S., & Caplan, D. (1996). The capacity theory of sentence comprehension: Critique of Justand Carpenter (1992). Psychological Review, 103, 761–772.

Wechsler, D. (1997). Wechsler Memory Scale (3rd ed.). San Antonio, TX: The PsychologicalCorporation.

Willcutt, G. E., Olson, R. K., Pennington, B. F., Boada, R., Ogline, J., Tunick, R., & Chhabildas,N. (2001). A comparison of the cognitive deficits in reading disabilities and ADHD. Journal ofAbnormal Psychology, 110(1), 28–34.

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APPENDIX A

Experimental Stimuli

Lists A & B

List A List B

1. Head 1. Sink2. Glass 2. Spoon3. Tie 3. Snail4. Gate 4. Nail5. Coat 5. Chain6. Bear 6. Sheep7. Ball 7. Chick8. Fish 8. Rake9. Watch 9. Queen

10. Rock 10. Swing11. Shoe 11. Cheese12. Girl 12. Flame13. Ice 13. Web14. House 14. Net15. Ring 15. Knife16. Ship 16. Well17. Back 17. Deer18. Cloud 18. Match19. Man 19. Vase20. Egg 20. Bow21. Wall 21. Key22. Boat 22. Fin23. Cup 23. Brush24. Heart 24. Leaf25. Bird 25. Ghost26. Tree 26. Fist27. Car 27. Tack28. Saw 28. Cab29. Safe 29. Straw30. Hat 30. Peach31. Sun 31. Gown32. Roof 32. Stool33. Feet 33. Tub34. Dog 34. Lock35. Ear 35. Thorn36. Hair 36. Braid37. Door 37. Mouse38. Face 38. Curl39. Hand 39. Shell40. Chair (seat) 40. Thread41. Book (page) 41. Veil42. Fly 43. Rope44. Mouth (lip) 44. Coil45. Neck 45. Meat

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Verbal Learning Abilities and Stimulus Modalities in Children with Dyslexia

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Transcript of Verbal Learning Abilities and Stimulus Modalities in Children with Dyslexia