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Robert Speiser, Matthew Schneps, Amanda Heffner-Wong; The Effect of Minimizing Visual Memory and Attention Load in Basic Mathematical Tasks. Journal of Vision 2010;10(7):733. doi: 10.1167/10.7.733.
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How might minimizing visual working memory and attention load affect students’ ability to perform basic mathematical tasks? Recent work (Schneps et al, 2007) suggests a potential trade-off between central and peripheral visual abilities: ""While the central field appears well suited for tasks such as visual search, the periphery is optimized for rapid processing over broad regions. People vary in their abilities to make use of information in the center versus the periphery, and we propose that this bias leads to a trade-off between abilities for sequential search versus contemporaneous comparisons.""We focus here on two pencil-and-paper algorithms for finding multi-digit products: the familiar standard algorithm (S), which places large demands on visual working memory and visual attention; and an older algorithm (Treviso, 1478). In the latter (T), an elegant spatial layout guides visual attention, and at the same time minimizes demands for visual memory. While algorithm S makes strong use of central (hence sequential) processing, the alternative algorithm T makes effective use of its spatial (therefore more pre-attentive, less sequential) layout. We report results from two experiments in progress, to compare the performance of post-secondary students on these algorithms in two learner populations: typical STEM undergraduates, and STEM undergraduates whose executive functions are believed to be impaired (specifically, those with dyslexia). In the first experiment, fifteen students from each population are tested on accuracy of performance on multi-digit products, comparing methods S and T. In the second experiment, students from each population again perform multi-digit products as above, but in this experiment their eye and hand motions are simultaneously tracked, to assess task dynamics. Results are analyzed statistically, for comparisons within and across both learner populations.
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