Proceedings of the Annual Meeting of the Cognitive Science Society

This research introduces the switch task, a novel learning modethat fits with calls for a broader explanatory account of hu-man category learning (Kurtz, 2015; Markman & Ross, 2003;Murphy, 2002). Learning with the switch task is a processof turning each presented exemplar into a member of anotherdesignated category. This paper presents the switch task to fur-ther explore the contingencies between learning goals, learn-ing modes, outcomes, and category representations. The pro-cess of successfully transforming exemplars into members of atarget category requires generative knowledge such as within-category feature correspondences – similar to inference learn-ing. Given that the ability to switch items between categoriesnicely encapsulates category knowledge, how does this relateto more familiar tasks like inferring features and classifyingexemplars? To address this question we present an empiri-cal investigation of this new task, side-by-side with the well-established alternative of classification learning. The resultsshow that the category knowledge acquired through switchlearning shares similarities with inference learning and pro-vides insight into the processes at work. The implications ofthis research, particularly the distinctions between this learn-ing mode and well-known alternatives, are discussed.