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Open Access Publications from the University of California

Classification Versus Observation through Within- and Between-Category Comparison

Creative Commons 'BY' version 4.0 license
Abstract

Inductive concept learning requires making inferences about target categories based on specific examples. Two factors which influence this process are type of learning task and the nature of the items available for comparison. However, the literature remains inconsistent on which combination of factors best facilitates concept learning. Moreover, much of the present literature focuses on artificial categories with arbitrary boundaries, leaving open the question of how best to improve learning for natural categories. We report two experiments on natural category learning, which cross learning mode (classification vs observation) with comparison type (match vs. contrast vs. control). Across both experiments, we find evidence of an observation advantage and some evidence for a contrast advantage (Experiment 1). These findings offer evidence against a classification advantage during natural category learning, which some studies have shown, and highlight the critical need for investigating the factors that impact the efficacy of classification and observation learning.