Representing the task in Bayesian reasoning: Comment on Lovett and Schunn (1999)

The RCCL model (M. C. Lovett gr C. D. Schunn, 1999) produces predictions th at are non-novel or that do not truly spring from its principles. However, it offers the valuable insight that learning processes may affect the selec tion of both representations and strategies within those representations, a nd points the way to possible theoretical progress on implicit and explicit control. The authors' account of base-rate neglect under direct experience is compared with RCCL, and it is concluded that learning-based models allo w for tests that are not fostered by representation-based models.