Proceedings of the Annual Meeting of the Cognitive Science Society

The power law of learning has frequently been used as a benchmark against which models of skill acquisition should be measured. However, in this paper we show that comparisons between model behavior and the power law phenomenon are uninformative. Qualitatively different assumptions about learning can yield equally good fit to the power law. Also, parameter variations can transform a model with very good fit into a model with bad fit. Empirical tests of learning theories require both comparative evaluation of alternative theories and sensitivity analyses, simulation experiments designed to reveal the region of parameter space within which the model successfully reproduces the empirical phenomenon. Abstract simulation models are better suited for these purposes than either symbolic or connectionist models.