DYSLEXIA Published online 8 September 2014 in Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002/dys.1483

■ Reasoning and Dyslexia: is Visual Memory a Compensatory Resource? Alison M. Bacon* and Simon J. Handley Plymouth University, Plymouth, UK Effective reasoning is fundamental to problem solving and achievement in education and employment. Protocol studies have previously suggested that people with dyslexia use reasoning strategies based on visual mental representations, whereas non-dyslexics use abstract verbal strategies. This research presents converging evidence from experimental and individual differences perspectives. In Experiment 1, dyslexic and non-dyslexic participants were similarly accurate on reasoning problems, but scores on a measure of visual memory ability only predicted reasoning accuracy for dyslexics. In Experiment 2, a secondary task loaded visual memory resources during concurrent reasoning. Dyslexics were significantly less accurate when reasoning under conditions of high memory load and showed reduced ability to subsequently recall the visual stimuli, suggesting that the memory and reasoning tasks were competing for the same visual cognitive resource. The results are consistent with an explanation based on limitations in the verbal and executive components of working memory in dyslexia and the use of compensatory visual strategies for reasoning. There are implications for cognitive activities that do not readily support visual thinking, whether in education, employment or less formal everyday settings. Copyright © 2014 John Wiley & Sons, Ltd. Keywords: dyslexia; reasoning; visual memory; Visual Patterns Test

The idea that individuals with dyslexia think in an inherently visual way is not new, with prolific anecdotal evidence having drawn on case studies of individuals employed in creative occupations, or retrospective analyses of the character and work of eminent artists and scientists (e.g. Aaron & Guillemard, 1993; Morgan & Klein, 2000; Vail, 1990). West (1997), Davis and Braun (2010) and Grant (2005) have also written extensively about individuals who have dyslexia and for whom visualisation is a primary mode of thought, compensating for verbal difficulties when processing information presented in written or auditory formats. The present research is concerned with how people with dyslexia draw on visual cognitive resources during reasoning. Reasoning can be defined as the mental manipulation of information in order to make inferences and draw conclusions. As such, it is fundamental to learning and decision making, underpinning success in education and employment as well as affecting many more informal aspects of day to day life. The way we reason influences our life plans and choices, the setting and achievement of goals and the ability to deal effectively with day to day problems (Baron, 2008; Leighton, 2004). Understanding how reasoning processes work is imperative if we are to support individuals in maximising their potential (Leighton, 2004). *Correspondence to: Dr Alison M. Bacon, School of Psychology, PlymouthUniversity, Drake Circus, Plymouth PL4 8AA, UK. E-mail: [email protected]

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Given the anecdotal evidence for superior visual ability in dyslexia, it is perhaps surprising to find that empirical studies have presented equivocal results. Research has tended to focus on comparing dyslexic and non-dyslexic participants on the capacity to mentally manipulate the visuospatial characteristics of shapes and objects. For instance, Steffert (1998) found that students with dyslexia performed better than their non-dyslexic counterparts at a mental rotation task, and Von Károlyi (2001) found that they were faster, although no more accurate, in identifying impossible objects than non-dyslexics. This enhanced processing speed was taken to indicate a visuospatial advantage in dyslexia. Rusiak, Lachmann, Jaskowski, and van Leuwen (2007) suggested that dyslexics performed more slowly, but no less accurately, than non-dyslexics in letter rotation, whereas the groups were comparable in both speed and accuracy when rotating shapes. Overall, although there is some evidence for superior performance on some aspects of some visuospatial tasks, most research has suggested that dyslexic participants either perform comparably, or less well, than non-dyslexics on a range of measures (e.g. Brosnan et al., 2002; Winner et al., 2001). However, Attree, Turner and Cowell (2009) have argued that many laboratory measures of visuospatial ability lack ecological validity. Their studies employed what they described as a pseudo-real life task involving immersion in a virtual environment, and participants with dyslexia attained significantly higher scores than controls. On the other hand, Brunswick, Martin and Marzano (2010) systematically compared dyslexic and nondyslexic adults on a series of visuospatial ability measures, tests of everyday visuospatial knowledge and a test of way finding in a virtual environment. They found very few differences between dyslexic and control participants. Given the equivocality of these research findings, it may be that a preference for visual thinking is not facilitated simply by enhanced ability, but driven by the need to compensate for deficits in the verbal domain. The present research aims to explore this possibility, employing tasks that have been widely used in conventional reasoning research. This has generally involved asking participants to complete simple logical problems, of which syllogisms are arguably the most widely used. Syllogistic problems comprise two premises, for example, All golfers are artists; Some jugglers are golfers; which describe the relationship between three terms (artists, golfers and jugglers in this example). Each premise contains one of four possible quantifiers (either All, Some, None or Some…not), which indicate the relationships. The classic syllogistic inference is to determine, assuming the information given to be true, the one relationship, which is not explicitly stated, that between the two non-repeated terms, and this forms the conclusion (i.e. Some artists are not jugglers). Such problems may appear abstract and circumscribed, but they can provide a test of everyday thinking processes such as identification of assumptions, use of stored knowledge and evaluation of arguments, in a simple and controllable format (Galotti, 1989; Gilhooly, 1996; Johnson-Laird & Bara, 1984). This makes syllogisms a useful tool for teasing out information about the reasoning strategies people use. Although research using this type of problem has been established for many years, only a couple of studies have previously considered dyslexia, and these have relied largely on verbal and written protocol data to make inferences about how people reason. This method involves asking participants to ‘think aloud’ and/or ‘write down their working out’ whilst completing reasoning problems. Bacon, Handley, and McDonald (2007) and Bacon and Handley (2010) reported how Copyright © 2014 John Wiley & Sons, Ltd.

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dyslexics constructed rich and explicit visuospatial representations during reasoning. They frequently described a strategy involving not only the generation of a visuospatial representation, but also a visualisation of physical characteristics, which they attributed to the terms. Bacon et al. present examples of written and verbal protocols, which show that even when problem terms are fairly abstract (such as single letters or nonsense words), dyslexics assign physical properties to them, drawing on stored semantic knowledge to embellish premise information to make it both more meaningful and more memorable. In contrast, non-dyslexic participants tended to adopt strategies that involved a basic manipulation of information in its written, propositional, form, frequently simply swapping around the terms in the premises. These participants presented little evidence of reasoning based upon the meaning of the premises or using visual processes and representations. In view of their recognised deficits, it is perhaps unsurprising that dyslexics do not employ verbal strategies for these reasoning tasks. However, whether this is simply down to preference, or is a necessary compensation, is open to question. The reasoning problems are presented in written form, and there is evidence that dyslexics process language differently to non-dyslexics and may draw on visuospatial resources in doing so. Davis and Braun (2010) have suggested that dyslexics possess no inner monologue, instead generating a mental representation using the semantics (or image of meaning) of narrative, and case study evidence is presented for dyslexics who are able to draw on visuospatial abilities in order to partly compensate for language difficulties (e.g. Goulandris & Snowling, 1991; Snowling & Hulme, 1989). We propose that reasoning strategies in dyslexia may be similarly underpinned by an ability to draw on intact visual resources to compensate for less effective verbal ones. Furthermore, there is already some evidence that dyslexics draw on visual memory resources selectively in this way. The structure of human memory is most frequently represented in terms of the tripartite model originally proposed by Baddeley and Hitch (1974). This comprises a central executive (CE), responsible for controlling and manipulating information stored in two slave subsystems, the phonological loop (PL) dealing with verbal information, and the visuospatial sketchpad (VSSP) for visuospatial material (see Baddeley, 2007, for a more detailed account of the working memory model). Impairments in verbal memory processes are well documented in dyslexia and are thought to play an implicit role in the reading and spelling difficulties these individuals experience (e.g. Ackerman & Dykman, 1993; Jeffries & Everatt, 2004; Kibby, Marks, Morgan, & Lang, 2004; Miles, 1993; Pickering, 2006). Dyslexics consistently show deficits on tests of simple verbal memory storage, such as the digit span, in which participants are asked to recall series of digits of increasing length. A low score on this measure is a common marker of dyslexia and frequently tested as part of dyslexia assessment (McLoughlin, Fitzgibbon, & Young, 1994). Conversely, visuospatial memory is thought to be intact, with VSSP deficits compared with non-dyslexics typically observed only with complex Working Memory (WM) tasks, which also implicate the CE (e.g. Reiter, Tucha, & Lange, 2004; Smith-Spark & Fisk, 2007). In terms of the present research, reasoning tasks are known to make diverse and powerful demands upon working memory, particularly those areas where dyslexics may have most difficulties, the PL and CE whilst placing relatively little burden on the VSSP (e.g. Capon, Handley, & Dennis, 2003; Gilhooly, Logie, Wetherick & Wynn, 1993; Gilhooly, Logie, & Wynn, 1999). Furthermore, there is much evidence that Copyright © 2014 John Wiley & Sons, Ltd.

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the visual and spatial components of the VSSP are dissociable (e.g. Della Sala, Gray, Baddeley, Allamano & Wilson, 1999; Logie & Pearson, 1997; Pickering, 2001) and Della Sala, Gray, Baddeley and Wilson (1997) developed the Visual Patterns Test (VPT) as a measure of specifically visual short-term memory. Della Sala et al. (1997, 1999) present findings from a range of studies to show that the VPT draws on distinctly visual, as opposed to verbal or spatial memory processes. In Bacon and Handley’s (2010) work on reasoning, they supported protocol evidence with data to show that scores on the VPT were predictive of reasoning accuracy for dyslexic participants, in other words, dyslexics with higher visual memory ability reason more accurately. This relationship was not observed for non-dyslexics, even though VPT span scores were comparable across both groups of participants. Overall, reasoning tasks make useful instruments with which to compare how dyslexic and non-dyslexic individuals draw differentially on the visual memory subsystems. A preference for visual reasoning in dyslexia may be a possible indicator of those individuals attempting to compensate for deficits elsewhere. An additional way to test this possibility is by examining how participants with dyslexia perform on reasoning tasks, which may not lend themselves to visual processing as easily as do syllogisms. Propositional reasoning problems (e.g. Braine, Reiser, & Rumain, 1998) present a logical argument, which describes the relationship between three or more abstract objects, often denoted by capital letters. The relationships are defined in terms of four possible connectives (if, and, or, not). For example, If there is an N, then there is not a B or an I It is false that there is not an N Conclusion: There is an I

The task is to evaluate the truth of the conclusion, assuming the information given about the relationship between objects to be true (in the aforementioned example, the conclusion shown is true). These problems are of interest in the present context because of evidence that performance is impaired by verbal, but not visuospatial, concurrent tasks (Farmer, Berman, & Fletcher, 1986). The extent of interference between primary (in this case reasoning) and secondary concurrent tasks indicates the degree of involvement of a given cognitive component in both tasks (Farmer et al., 1986; Gilhooly et al., 1993). In this case, we assume that a reasoning strategy drawing on verbal processes predominates as a concurrent task, which also draws on these processes interferes with reasoning performance. Later work by Klauer, Stegmaier, and Meiser (1997) has indeed shown that reasoning with this type of problem is typified by a strategy based on linguistic characteristics. In summary, although there has been a paucity of research on reasoning in dyslexia, recent work has presented two key findings: that individuals with dyslexia spontaneously adopt a reasoning strategy based on explicit visual representations, and that performance on a measure of specifically visual memory is predictive of reasoning accuracy for these participants. However, a limitation of this work is that it has relied heavily on protocol data. A number of disadvantages to this method have been highlighted, particularly around the accuracy of introspections and potential subjectivity in analysis (e.g. Cabello & O’Hora, 2002), and, as such, the present research aimed to provide direct quantitative evidence for the Copyright © 2014 John Wiley & Sons, Ltd.

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involvement of specifically visual memory resources in syllogistic reasoning in individuals with dyslexia. Our second aim was to extend the investigation to propositional reasoning for which there is no extant data relating to dyslexia. Given evidence to suggest that the dominant approach is likely to draw significantly on verbal processes, we might anticipate that propositional reasoning will be difficult for people with dyslexia who are impaired in the verbal domain. As such, we were interested to discover whether they would instead draw on visual cognitive resources on this task. We present two studies that address these aims. In Experiment 1, we examine the extent to which visual memory was related to reasoning performance in both dyslexic and non-dyslexic participants, on both syllogistic and propositional tasks. In Experiment 2, a secondary task was employed, which required participants to keep in mind and recall a visual pattern whilst simultaneously engaging in their primary reasoning tasks. This allowed for a comparison of dyslexic and nondyslexic reasoners in terms of the extent to which reasoning was impaired by a concurrent visual processing load. EXPERIMENT 1 Experiment 1 aimed to provide quantitative evidence for individual differences in reasoning strategies. If, as we propose, individuals with dyslexia draw on specifically visual memory processes in reasoning and that this is an index of difference between dyslexics and controls, we predicted that scores on a measure of visual memory would be positively associated with reasoning accuracy for dyslexic but not for non-dyslexic participants. Methods Participants

Seventy student volunteers took part. They were undertaking a range of degree courses and were at various stages of undergraduate or postgraduate studies. They were recruited via noticeboard advertisements on campus and through an established participant pool run by the School of Psychology. All participants were Native English speakers and none had received formal training in logic. They were paid £6 for participation. Dyslexic participants (n = 35, 21 females, 14 males, mean age 27.5 years). These participants had all been formally diagnosed by chartered educational psychologists employed at the university. As such, all had received a recent, full-scale, diagnostic assessment and received a formal statement certifying their dyslexic status and indicating the absence of other co-morbid learning difficulties. Non-dyslexic participants (n = 35, 28 females, 7 males, mean age 26.7 years), selfreported as not having dyslexia, any previous or current literary difficulties or a diagnosis of any other learning disability. Nicolson and Fawcett (1997) have shown that self-reports of non-dyslexia tend to be highly accurate. Materials and procedures

Each participant completed two reasoning tasks and a measure of visual memory (the VPT) as detailed in the succeeding text: Copyright © 2014 John Wiley & Sons, Ltd.

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Syllogistic reasoning: This task comprised 16 syllogistic problems as used by Bacon et al. (2007). The premise terms were denoted by hobbies/occupations as in the example previously, and participants were asked to deduce the logical conclusion from the two premises given. Propositional reasoning: This task presented 16 propositional problems, taken from the work of Braine et al. (1998). Each problem presented a logical argument, which described the relationship between three or more abstract objects represented by capital letters as in the earlier example. The task was to evaluate the truth of the conclusion, assuming the information given about the relationship between objects to be true. Two possible response options, true/false, were presented as is the usual method with this type of problem. Visual memory measure: we administered the VPT (Della Sala et al., 1997), which tests the ability to remember static visual patterns. The test presents matrices of squares, some of which are filled to form a visual pattern. Following a 3-s presentation, participants are asked to recall the pattern by shading the appropriate squares on a blank matrix. Three matrices are presented at each level of difficulty, from 2–15 filled squares. Version A of the two parallel versions of the test was used here and testing ceased at the point at which each participant was unable to recall any of the three patterns at a given level correctly. Span score was calculated as the mean number of filled squares correctly recalled in the last three correct patterns, irrespective of level. Della Sala et al. (1997) suggest this to be a more sensitive measure of performance than simply the highest pattern recall level achieved. The reasoning tasks were presented on paper in separate booklets. Each problem was presented on a separate page and participants asked to write down their conclusion beneath (syllogistic) or circle the appropriate response (propositional). In each task, the 16 problems were presented in a different random order for each participant and accuracy calculated as the percentage of correct responses. A 10-min time limit was imposed for each booklet. Half of each group completed the propositional task first and half the syllogistic task first. Finally, all participants completed the VPT. Results

Table 1 presents the mean accuracy for the reasoning tasks and visual memory span (VPT) scores for dyslexic and non-dyslexic participants. As this shows, the two groups performed comparably on all three measures. Table 2 presents correlations to indicate the relationship between reasoning accuracy and visual memory ability. For the dyslexics, visual memory (VPT) is strongly related to reasoning accuracy on both types of problem. No relationship is apparent for the non-dyslexics. Table 2 also shows that the difference between correlations for the two groups is significant, in line with the prediction that they draw differentially on visual memory resources. To test this further, two multiple linear regressions were conducted, with syllogistic and propositional reasoning performance as the dependent variables. Each analysis contained three predictor variables, dyslexic Copyright © 2014 John Wiley & Sons, Ltd.

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Table 1. Experiment 1: Performance data for all three tasks Propositional reasoning (% correct) mean Dyslexic Non-dyslexic Between-group comparison

Syllogistic reasoning (% correct)

SD

mean

74.6 18.1 80.6 16.1 t(68) = 1.68, p = 0.14

VPT score

SD

Mean

39.5 14.1 41.8 19.5 t(68) = 0.57, p = 0.57

SD

8.2 2.1 8.4 1.6 t(68) = 0.46, p = 0.64

VPT, Visual Patterns Test.

Table 2. Experiment 1: Correlations between reasoning accuracy and measure of visual memory ability. Statistical comparison of correlations between groups is also shown, significant p values in bold Syllogistic reasoning Dyslexic VPT Non-dyslexic VPT Comparison (2 tailed)

Propositional reasoning

0.69**

0.55**

0.05 z = 3.19; p = 0.001

0.08 z = 2.21; p = 0.03

VPT, Visual Patterns Test. **Correlation significant at the 0.01 level

status, VPT score (converted to a z-score) and an interaction variable computed as the product of these scores and dyslexic status. A significant interaction would suggest that VPT differentially predicts reasoning accuracy across the two dyslexic status groups. Table 3 presents the results of these analyses. As Table 3 indicates, for both types of reasoning, a significant interaction between VPT and dyslexic status was observed. This suggested that visual memory was differentially predictive for the two groups of participants. Further withingroup regressions confirmed these findings. On propositional problems, visual memory was a significant predictor for dyslexics, R2 = 0.55; β = 0.55, t = 3.82, p = 0.001; but not non-dyslexics, R2 < 0.08; β = 0.08, t = 0.48, p = 0.63. On syllogistic problems, the picture was the same with visual memory predicting accuracy for dyslexics, R2 = 0.48; β = 0.69, t = 5.49. p < 0.001; but not for nondyslexics, R2 = 0.01; β = 0.05, t = 0.26, p = 0.79. Table 3. Experiment 1: Results of multiple linear regression on reasoning accuracy for both types of problem Predictors

Propositional reasoning

Syllogistic reasoning

2

Dyslexic status VPT Dyslexia*VPT

2

R = 0.21; F = 5.75; p = 0.001

R = 0.17; F = 4.48; p = 0.006

β

β

0.19 0.09 0.48

t 1.71 0.50 2.69

Sig. . 09 0.62 0.009

0.05 0.06 0.36

t 0.47 0.33 1.97

Sig. 0.64 0.74 0.05

VPT, Visual Patterns Test.

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The primary aim of Experiment 1 was to provide empirical evidence to support earlier protocol-based studies, which have indicated that dyslexics rely heavily on specifically visual processes during reasoning. Our results are strongly in line with this suggestion. For both syllogistic and propositional reasoning, visual memory capacity (as defined by VPT score) significantly predicted reasoning accuracy for dyslexic, but not for non-dyslexic, participants. Even with propositional reasoning, which previous research has suggested relies primarily on verbal processes, dyslexics seem to draw on their visual resources and those with higher visual memory ability are more accurate reasoners. No such relationship is apparent for non-dyslexics. Overall, the predominant index of difference between dyslexic and nondyslexic reasoners in Experiment 1 was the ability of visual memory capacity to predict reasoning performance for the dyslexics. This provides converging evidence to support earlier research and suggests that a preference for reasoning strategies based on visual processes may be a robust feature of the dyslexic cognitive profile. Experiment 2 tested this idea further. Here, we again present both syllogistic and propositional reasoning tasks, but we constrained the capacity for using visual memory by asking participants to carry out a concurrent secondary task, which required them to remember and subsequently recall a visual pattern. This visual memory task was presented under both high and low memory load conditions. We predicted that if dyslexics were using a reasoning strategy, which significantly involved visual memory, then their reasoning performance would be affected by the visual load to a greater extent than that of the nondyslexic participants.

EXPERIMENT 2 Participants

Sixty student volunteers took part. They were recruited in the same way as for Experiment 1 and the same group allocation criteria applied, that is, all participants classed as dyslexic (n = 30, 21 females, 9 males, mean age 27 years) had received a recent, formal diagnosis by an educational psychologist here at the university. Non-dyslexic participants (n = 30, 24 females, 6 males, mean age 26.1 years) selfdeclared as non-dyslexic. All participants were Native English speakers. None had received formal training in logic and none had taken part in Experiment 1. They were paid £6 for participation. Design and procedures

We employed a dual-task procedure, which required participants to complete a primary reasoning task whilst concurrently remembering, and then subsequently recalling, visual patterns. Primary tasks (reasoning)

Propositional reasoning: this task comprised the same 16 propositional problems used in Experiment 1 but with computerised presentation. For each problem, premises and conclusions were presented simultaneously on-screen with two Copyright © 2014 John Wiley & Sons, Ltd.

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response buttons labelled Yes and No beneath Participants indicated their response by a mouse click to the appropriate button and the computer recorded the response made. Syllogistic reasoning: participants were presented with the same 16 problems as in Experiment 1 and asked to work out the logically valid conclusion, that is, the conclusion that had to be true if the information in the premises was true. Premises were presented simultaneously on-screen with a text box beneath into which participants were asked to type their conclusion. Alternatively, if they thought the problem was invalid (i.e., that there was no valid conclusion), they could type ‘no conclusion’. Secondary task (visual memory)

This task was adapted from the procedures for the VPT (Della Sala et al., 1997) described in Experiment 1. In the present study, we devised a procedure, which, in essence, comprised a computerised version of the VPT at levels 3 (low load) and 6 (high load) with a retention interval during which the reasoning problem was presented. We selected these load levels based on data from our previous work with this task, Bacon and Handley (2010), which presented VPT span scores across two studies (dyslexic M = 8.21; non-dyslexic M = 8.04, p > 0.5) and Experiment 1 earlier (Table 1). A small pilot study (n = 6) indicated that a six shaded square pattern was difficult enough to facilitate interference of the primary task whilst still allowing for pattern maintenance. Instructions for the memory task emphasised the importance of recalling the patterns correctly. In a fully within-subjects design, all participants completed four computerised tasks, which allowed for both syllogistic and propositional reasoning problems to be presented under both high and low concurrent memory load conditions. Within each dyslexic status group, presentation order of the four tasks was counterbalanced in terms of both reasoning type and memory load. Each task was presented in a separate block of 16 trials. Two practice trials were presented at the start of each block, with the 16 experimental trials presented in a different random order for each participant. We used essentially the same reasoning problems in the high and low memory load conditions, but altered the premise terms to create novel, but structurally equivalent, items. For each test item, the procedure had three stages. (1) Pattern displayed on-screen for 3 s; (2) completion of reasoning problem and appropriate response given; (3) pattern recall—a blank matrix of the relevant size was presented and participants clicked on appropriate squares to indicate the remembered pattern. Results Reasoning accuracy

Table 4 shows the mean percentage reasoning accuracy scores that were entered into a 2 (problem type) × 2 (memory load) × 2 (dyslexic status) ANOVA. Main effects of problem type, F (1, 58) = 539.39, MSE = 159.54, p < 0.001, η2 = 0.90 Copyright © 2014 John Wiley & Sons, Ltd.

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High

Syllogistic

Low

High

Propositional Low

High

Syllogistic Low

High

Pattern recall Propositional Low

Dyslexic 14.17 (20.05) 37.02 (13.67) 54.58 (27.95) 78.33 (20.22) 48.8 (32.6) 56.7 (24.1) 47.1 (31.4) 57.5 (24.5) Non-dyslexic 43.88 (14.06) 44.27 (18.24) 76.76 (9.89) 81.17 (16.92) 69.7 (27.2) 68.4 (17.6) 61.7 (23.6) 69.6 (19.6) Between-group t = 5.04 p < 0.001 t = 1.74 p = 0.11 t = 4.12 p < 0.001 t = 0.59 p = 0.56 t = 2.69 p = 0.009 t = 2.15 p = 0.03 t = 2.78 p = 0.007 t = 0.2.11 p = 0.04 comparison (df = 58)

Task Load

Reasoning accuracy

Table 4. Experiment 2: Mean percentage reasoning accuracy and pattern recall across all four conditions (standard deviations in parentheses)

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and load, F (1, 58) = 26.29, MSE = 377.17, p < 0.001, η2 = 0.31, were observed. These results reflected the overall tendency for participants to perform better on propositional problems compared with syllogisms and better with low as opposed to high concurrent memory load. A main effect of dyslexic status; F(1, 58) = 16.01, MSE = 899.12, p < 0.001, η2 = 0.22, illustrated that the dyslexics were generally less accurate overall than were the non-dyslexics. Most interesting in terms of our research question was a significant interaction between dyslexic status and memory load; F (1, 58) = 17.36, MSE = 377.17, p < 0.001, η2 = 0.23. As Table 4 shows, non-dyslexic participants were significantly more accurate than the dyslexics on both high load conditions. Conversely, with a low concurrent memory load, the two groups performed comparably on both reasoning tasks. No other significant effects were observed. Simple main effects analysis on the within-groups data indicated a significant effect of problem type in the non-dyslexic group; F (1, 29) = 250.14, MSE = 145.87, p < 0.001, η2 = 0.90, reflecting their tendency to perform best on propositional problems. No other significant effects were observed (p > 0.30 in both cases). In the dyslexic group, we observed a similar main effect of problem type, F (1, 29) = 289.27, MSE = 173.20, p < 0.001, η2 = 0.91. However, with these participants, a significant main effect of memory load was also apparent, F (1, 29) = 28.87, MSE = 564.09, p < 0.001, η2 = 0.50. The interaction was not significant (p = 0.81) illustrating that, for dyslexics, a high concurrent load was significantly detrimental to reasoning accuracy on both syllogistic and propositional reasoning. Pattern recall

Table 4 also shows percentage of correctly recalled patterns in each condition. A 2 (problem type) × 2 (memory load) × 2 (dyslexic status) ANOVA on this data showed a significant main effect of memory load; F (1, 58) = 4.80, MSE = 417.17, p < 0.05, η2 = 0.08, reflecting a general tendency to recall patterns more accurately in the low load conditions, which we would expect as the memory task is relatively easy. This also suggests that our load manipulation was effective. An overall main effect of dyslexic status; F (1, 58) = 7.5, MSE = 1710.35, p = 0.004, η2 = 0.13, reflected lower overall recall by dyslexic participants across all four conditions. No other significant effects were observed (p > 0.30 in every case). Overall, dyslexic reasoners were significantly less accurate under high concurrent visual memory load, on both problem types, compared with both non-dyslexics and to low load conditions. The non-dyslexics, however, were relatively unaffected by the secondary task. These results suggest that dyslexic participants draw upon visual memory when reasoning with both syllogisms and abstract propositional arguments. Further evidence for this claim is provided by the observation that participants with dyslexia also recalled significantly fewer visual patterns on the secondary task, across all four conditions. This again suggests a conflict of resources in the visual domain for these participants. Interestingly, in the low concurrent visual memory load conditions, the two groups of participants performed comparably. Consistent with Experiment 1, this suggests that the use of visual processes amongst the dyslexic participants does not in general lead to poorer reasoning performance, on either type of problem. Copyright © 2014 John Wiley & Sons, Ltd.

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GENERAL DISCUSSION Previous research has presented protocol data to suggest that people with dyslexia use reasoning strategies based on rich, and distinctly visual, mental representations, whereas non-dyslexics use simple abstract verbal strategies. The present two studies offer converging evidence for the strategic differences from individual differences and experimental perspectives. Experiment 1 presented no differences in accuracy between groups on either syllogistic or propositional reasoning tasks. However, the relationship between reasoning accuracy and scores on a measure of specifically visual memory (the VPT) suggested that dyslexic participants were drawing on visual resources for both problem types—those with higher visual memory ability reasoned most accurately. We found no evidence that the measure of visual memory capacity predicted reasoning performance for nondyslexics. In Experiment 2, a secondary task loaded visual memory resources by asking participants to remember visual patterns whilst engaging in concurrent reasoning tasks. This disproportionately affected dyslexic participants who were significantly less accurate on both syllogistic and propositional reasoning problems under conditions of high memory load. A reduced ability to subsequently recall the visual patterns further indicated that the secondary memory task and the reasoning tasks were competing for the same visual cognitive resource. Interestingly, performance did not differ between the groups under low concurrent load. This suggests that both dyslexic and non-dyslexics were able to execute effective reasoning strategies, but that these drew on differing cognitive resources with only the dyslexics disadvantaged when competing visual demands were present. Overall, the use of visual processes in reasoning presents an interesting index of difference between dyslexic and non-dyslexic individuals. So what might underpin this difference? The evidence for a general underlying visuospatial talent in dyslexia is not persuasive (Brunswick et al., 2010), and, indeed, we found no evidence that the groups differed in ability on our measure of visual memory (the VPT). One possible explanation relates to WM function, and the present studies raise some interesting questions about the functional architecture of WM in dyslexia. Individuals with dyslexia are known to present a deficit in verbal memory function, and the PL is implicated in reasoning with both syllogistic (e.g. Gilhooly et al., 1993, 1999) and propositional (Farmer et al., 1986; Klauer et al., 1997) problems. However, those taking part in our studies were able to reason as accurately as non-dyslexics in Experiment 1 and in the low concurrent load condition of Experiment 2. Furthermore, our data suggest that they were drawing on distinctly visual processes during both tasks. Non-dyslexic participants were not affected adversely by a high concurrent visual load, nor were their scores on the VPT reflected in their reasoning accuracy. This endorses the suggestion that the VSSP is not a critical resource for reasoning in the general population, further underlining the individual differences between dyslexic and non-dyslexic strategies. We propose that dyslexics adopt a strategy, which is compensatory, drawing on visual resources to offset a verbal deficit. However, there is evidence to suggest that visuospatial working memory in dyslexia may not be wholly intact. Dyslexics have been found to present impairment on tasks designed to draw on the VSSP if they also implicate the CE (e.g. Brosnan et al., 2002; Reiter et al., 2004; Smith-Spark & Fisk, 2007; Smith-Spark, Fisk, Fawcett, & Nicolson, 2003). The CE temporarily stores and processes information Copyright © 2014 John Wiley & Sons, Ltd.

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across modalities and is thought to be central to many cognitive tasks, including reasoning (e.g. Capon et al., 2003). According to García-Madruga, Gutiérrez, Carriedo, Luzón and Vila (2007, p. 379) reasoning requires ‘… the processing, activation, and maintenance of relevant information, and the moment-to-moment control and monitoring of the process of finding a solution’—all key executive activities (e.g. Baddeley, 2007). Furthermore, Miyake, Friedman, Rettinger, Shah, and Hegerty (2001) have indicated that, like the VSSP, the CE may be fractionated into distinct visual and spatial components and visual processes are likely to be involved in many executive tasks. Similarly, executive processes are thought to play a part in memory for visual material (e.g. Hamilton, Coates, & Heffernan, 2003; Vandierendonck, Kemps, Fastame, & Szmalec, 2004) and a meta-analysis by Swanson, Zheng and Jerman (2009) concludes that dyslexic performance on visuospatial WM tasks appears to fluctuate with processing demands. In other words, individuals with reading disabilities such as dyslexia have most difficulty with complex tasks, which place high demands on both storage and maintenance components of the working memory system, implicating the CE. This is clearly the case with Experiment 2 where dyslexics showed a significant decrement in reasoning accuracy and pattern recall under high load conditions. Furthermore, successfully maintaining a secondary visual image whilst reasoning requires sustained concentration and recent work has suggested that dyslexic adults rely heavily on visuospatial working memory to maintain attention to a task. Conversely, in non-dyslexic controls, attention is associated with verbal working memory (Alloway, Wootan, & Deane, 2014). These results have implications for dyslexia in everyday life. Dyslexics are known to experience more cognitive lapses compared with non-dyslexics (McNamara & Wong, 2003; Smith-Spark, Fawcett, Nicolson, & Fisk, 2004), and there is anecdotal evidence that they can and do draw spontaneously on visual strategies to assist them (Davis & Braun, 2010; Grant, 2005; West, 1997). However, reliance on a compensatory strategy may be problematic in situations requiring cognitive flexibility. As Schunn, Lovett and Reder (2001) point out, one of the key ways in which individuals adapt to a changing world is by altering their strategy for performing tasks with differing and novel demands. However, this idea is underpinned by the assumption that individuals have a menu of potential strategies available to them. Bacon, Parmentier and Barr (2013) have suggested that individuals with dyslexia have difficulties with selecting appropriate strategies for complex cognitive tasks and in switching to more effective ones, consistent with a deficit in executive function (e.g. Miyake et al., 2000). This issue of cognitive flexibility is an important one in practical terms with a number of studies indicating everyday implications for individuals who experience difficulties with strategic adaptivity in the workplace (e.g. Griffin & Hesketh, 2003) and in education (Broekkamp & Van Hout-Wolters, 2007). A potential limitation to this work is that we did not include a measure of verbal memory ability, either as a covariate factor in Experiment 1, or to test for a double dissociation in Experiment 2. Although further research should consider this option, we, nonetheless across two studies, have shown clear converging evidence for the use of visual reasoning strategies in dyslexia, further corroborating earlier protocol-based research. To conclude, previous studies employing protocol methods have proposed a clear role for visual imagery in reasoning in dyslexia and suggest that the Copyright © 2014 John Wiley & Sons, Ltd.

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representations constructed are both explicit and analogous. We provide converging evidence for this proposal and extend it to show that these strategies processes that draw significantly on the visual components of working memory. Our results are consistent with an explanation based on limitations in the verbal and executive components of working memory in dyslexia and the use of compensatory visual strategies for reasoning. As such, these results present significant additional evidence for the existence of fundamental cognitive differences between dyslexic and non-dyslexic individuals in terms of visual processes. These results are of interest in terms of our understanding of dyslexia and also in terms of reasoning theory, which has tended to assume universality. However, they also have implications for practitioners working with dyslexia. Reasoning is fundamental to everyday problem solving and vital to educational achievement. Our dyslexic participants may have reasoned differently to non-dyslexics, but when they are able to use their visual strengths, they reason just as accurately. Our findings support the use of educational materials and task formats, which readily afford visual thinking. However, in a society that strongly favours a verbal literacy-reliant, approach to many everyday tasks, the wider recognition and facilitation of individual differences in thinking and problem solving style is long overdue.

ACKNOWLEDGEMENTS This research was supported by the UK Economic & Social Research Council grant no. RES-000-22-1965 awarded to the authors.

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