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Sequence learning is essential in cognition and underpins activities such as language and skill acquisition. One classical demonstration of sequence learning is that of the Hebb repetition effect, whereby serial recall improves over repetitions on a repeated list relative to random lists. When addressing the question of which mechanism underlies the effect, the traditional approach is to prevent the action of processes thought to be responsible for sequence learning: If the typical Hebb repetition effect is reduced, these processes are key to the effect, researchers claim. By reanalyzing the data of F. B. R. Parmentier, M. T. Maybery, M. Huitson, and D. M. Jones (2008)-who reported no Hebb effect for sequences of auditory-spatial stimuli-we revealed that error learning can be mistaken for the absence of sequence learning. Indeed, incorrect responses are reproduced increasingly over repetitions. Our findings suggest that the Hebb repetition effect can be associated with response learning as well as stimulus processing.

The authors present 3 decision-tree models of categorization adapted from T. Trabasso, H. Rollins, and E. Shaughnessy (1971) and use them to provide a quantitative account of categorization response times, choice proportions, and typicality judgments at the individual-participant level. In Experiment 1, the decision-tree models were fit to reaction time and choice proportion data from a study reported by A. L. Cohen and R. M. Nosofsky (2003). In Experiment 2, participants were also asked to provide typicality ratings for each stimulus. A process-tracing method called the "4-questions game" (Y. Sayeki, 1969) was used in a posttest phase to identify a decision tree for each participant. In both experiments, the decision-tree models explained a very high proportion of variance in the data and compared favorably with 2 leading exemplar models.