Classification versus inference learning contrasted with real-world categories
A number of studies have contrasted classification and inference, using a variety of stimuli and tests, but in all cases the difference between these tasks could be attributed to either methodological differences or an inherent difference between the tasks. The inherent difference explanation argues that classification and inference learners use different strategies during learning, which reflect the goals of the tasks. Inference learners focus more on what each category is like, while classification learners focus on finding the information that best predicts category membership. These differences during learning lead to performance differences on later tests of category knowledge. In two experiments, using real-world categories and controlling for methodological differences, inference learners learned more about what each category was like than classification learners. These results suggest that there is an inherent difference between classifying an item and inferring a feature that cannot be explained by methodological differences between the tasks.
University of Illinois - Urbana-Champaign
Networked Digital Library of Theses and Dissertations
University of Illinois at Urbana-Champaign