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Effects of Category-Learning on Categorization An Analysis of Inference-Based and Classification-Based Learning

Abstract

It is widely acknowledged that categories have many functions, but few studies have actually addressed the impact of these functions on the way categories are learned. For instance, many categorization experiments predominantly rely on classification-based incremental learning. The problem with this approach is that it implicitly assumes that the function of categorization is separable from the way that categories are learned. In this study, we examined the relation between learning and the subsequent use of categories by contrasting three types of category-learning methods — inference-based, classification-based, and a combination of these methods. The results of the experiment indicate that there is an intricate relationship between category-learning and subsequent use of the category. The results further suggest that different processing modes may have been adopted by subjects in the different learning conditions.

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