Proceedings of the Annual Meeting of the Cognitive Science Society

In current theories of skill acquisition it is quite common to assume that the input to learning mechanisms is a problem representation based on direct translations of problem instructions or simple inductions from problem solving examples. W e call such a problem representation an execution space because it is made up of operators corresponding to the external actions agents perform while executing problem solutions. Learning proceeds by modifications and combinations of these execution space operators. W e have built a model of geometry expertise based on verbal report evidence which contains operators which can be described as modifications (e.g., abstractions) and combinations (e.g., compositions) of execution operators. However, a number of points of evidence lead us to conclude that these operators were not derived from execution space operators. In contrast, it appears these operators derive from discoveries about the structure and properties of domain objects, particularly, perceptual properties. We have yet to develop a detailed and integrated theory of this "perceptual churJdng", but we present the exp)ert model is a challenge to ciurent dieories of skill acquisition.