Alignment and category learning.

In 6 studies, the authors showed that alignment is involved in category learning as well, and Representational assumptions of category learning models must be modified to account for the differences between aligned and nonaligned feature matches.

Abstract

Recent research shows that similarity comparisons involve an alignment process in which features are placed into correspondence. In 6 studies, the authors showed that alignment is involved in category learning as well. Within a category, aligned matches (feature matches occurring on the same dimension) facilitate learning more than nonaligned matches do (matches on different dimensions), although nonaligned matches still facilitate learning relative to nonmatches. Analogously, feature matches that cross category boundaries hurt learning more if they occur on the same versus a different dimension, and cross-category feature matches on different dimensions hurt learning relative to nonmatching features. Representational assumptions of category learning models must be modified to account for the differences between aligned and nonaligned feature matches.