A Meta-analysis Of The Influence Of Task Administration On The Links Between Children's Card Sorting Tasks And Mathematics Performance - Info and Reading Options

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Executive function is a modern complex concept that is used to describe a set of interrelated cognitive processes responsible for goal-directed behaviour (Bull & Lee, 2014; Lezak et al., 2012). Most scholars agree on three core executive functions: inhibition, working memory, and cognitive flexibility (Diamond, 2013; Miyake et al., 2000; Zelazo & Carlson, 2012). The potential for executive functions to support children’s learning makes it an important dimension of school achievement. Associations between executive function skills and children’s academic outcome, especially mathematic performance, have been extensively studied (Brock et al., 2009; Lee et al., 2009; van der Ven et al., 2012; Willoughby et al., 2012). These subcomponents of executive function may be related to mathematical achievement because they a) help storing and manipulating relevant information such as intermediate results, b) help suppressing irrelevant number facts or procedures during problem-solving, and c) help shifting between strategies or operation when required. While much attention has been paid to the use of different tasks to assess executive functions and its influence on the links between executive functions and academic achievement, little work has been done to examine the impact of the task administration mode. One well-established instrument for executive function assessment is the card sorting task, which requires participants to sort objects such as cards and blocks into categories based on changing rules. Both manual and computerized versions of the task are available, and the task is thus chosen here as an exemplar to help narrow the focus to improve an understanding of the impact of the task format. Among the family of sorting tasks, the Wisconsin Card Sorting Test (WCST) is the most prominent paradigm that was originally developed by Grant and Berg (1948) as a clinical neuropsychological test assessing perseverance, attention, set shifting, and reasoning (Rabin et al., 2005; Diamond, 2013) and was later used to assess aspects of executive functions more broadly in children, adolescents, and adults (Lange et al., 2017; Miles et al., 2021). The Dimensional Change Card Sort (DCCS; Zelazo, 2006) is a simplified version of the WCST that is widely used with young children. Other variations of the card sorting task such as the Multiple Classification Card Sorting Task (MCCST; Podjarny et al., 2017) and the Modified WCST (Cianchetti et al., 2007) have also been developed. Given the differences in the perceptual array and the form of the feedback, there is a debate regarding the equivalence between the tabletop and computerized formats of the WCST. Some studies reported that performance in the manually administered version was comparable to that in the computerized version (Fortuny & Heaton, 1996; Shan et al., 2008; Wagner & Trentini, 2009), whereas others did not (Çelik et al., 2021; Feldstein et al.,1999; Steinmetz et al., 2010). However, these studies have focused exclusively on adult population and in comparison, there is a limited number of studies conducted with children. Two studies found better scores for the manually administered task among school-aged children from different countries (Filippetti et al., 2020; Shu et al., 2000), suggesting that computerized WCST might be more difficult to complete than the manual version for children. Doebel and Zelazo’s (2015) meta-analysis on the DCCS showed inconsistent findings suggesting that the computer-based task format was not more difficult for children as task modality did not account for variance in the switching performance. Hence, it is unclear whether the mode of administration constitutes one of the factors explaining the variability in task performance. Moreover, significant association between the executive functioning scores and children’s mathematics performance has been found in research using a computerised WCST task (Edmonds, 2022; Escobar et al., 2018; Orbach et al., 2020) but not in research using a tabletop version (Knipe, 2009; Monette et al., 2011; Rosselli & Ardila, 1993). Therefore, it is likely that the transformation to computer screen, which introduces changes in task demand and response method, may correlate with and predict mathematical outcome differentially.

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