title: Learning categories composed of varying instances: the effect of classification, inference, and structural alignment.
abstract: The members of a natural category are not usually identical in their appearance, although at some level they can be described as having features in common. For example, birds have wings, but the actual appearance of their wings varies from one bird to another. To examine the effect of this feature variation on category acquisition, subjects in three experiments were asked to learn categories in which individual features were depicted with several different instances. The results of the experiments indicated that subjects had significant difficulty learning these categories when they were given a standard classification learning task. In contrast, subjects were able to acquire the same categories when they were given an inference learning task, in which they learned the categories by predicting a missing feature of a stimulus given the category label and information about the other features. Finally, subjects who were allowed to compare stimuli during learning were able to learn the categories. These results suggest that a common description of different instances emerges in the process of aligning stimuli.
authors.affiliation: Columbia University, New York, New York, USA. takashi+@pitt.edu
authors.forename: T
authors.initials: T
authors.lastname: Yamauchi
authors.forename: A B
authors.initials: AB
authors.lastname: Markman
mesh_terms: D001288:Attention; D003210:Concept Formation; D004193:Discrimination Learning; D006801:Humans; D011939:Mental Recall; D010364:Pattern Recognition, Visual; D011340:Problem Solving