Abstract

Two experiments tested the effect of prior knowledge on attention allocation in category learning. Using eyetracking, we found that (a) knowledge affects dimensional attention allocation, with knowledge-relevant features being fixated more often than irrelevant ones, (b) this effect was not due to initial attention bias to the relevant dimensions but rather gradually emerged in response to observing category members, and (c) the effect grew even after the last error trial, that is, in the absence of error. These results pose challenge to current models of knowledge-based category learning. Because of the importance of categories for human cognition, the manner in which people learn categories has received intensive study. Among many procedures, supervised classification learning has been popular, and a

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