Proceedings of the Annual Meeting of the Cognitive Science Society

Important component of expertise is the rapid pickup complex. task-relevant pattern structure, yet such skills seldom trained explicitly. We report initial results ying principles of perceptual learning to the essing of structure in mathematics, specifically the ection between graphed functions and their symbolic essions. Subjects in two experiments viewed graphs inctions and made a speeded, forced choice match from ral equations. Training consisted of many short trials lis active classification task involving examples of a tion (e.g., sine) subjected to various transformations. scaling, shifting, reflection). Experiment 1 used rastive feedback — the graph for a trial was shown erimposed on the canonical function to accentuatejformations. Subjects showed substantial performance s from 45 minutes of training and transferred to new inces, new function families and a new task. In eriment 2, with contrastive feedback removed, subjects ved no transfer to new functions. The results indicate value of perceptual training in producing lematical expertise and the value of contrastive back in particular.