This article focuses on the validation and explanatory power of the predominant model of scientific discovery used in cognitive science. Two strategies of validation are identified: validation by reproduction and validation by convergence. It is argued that neither provides a sufficient approach to validation and that a more appropriate strategy would consist in testing the model against current scientific problems to try to generate new discoveries. Another contention of this article is that the explanatory power of the model can be increased by understanding cognitive differences between the small proportion of `discoverers' and the large number of scientists working on a given problem at a given time. This question can best be tackled by studying how experts acquire their expertise from fragmentary and complex knowledge and by understanding expert learning, a topic that has so far been neglected in the cognitive psychology of expertise.
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