Grouping by Similarity Helps Concept Learning

Abstract

In inductive learning, the order in which concept instances are presented plays an important role in learning performance. Theories predict that interleaving instances of different con- cepts is especially beneficial if the concepts are highly sim- ilar to each other, whereas blocking instances belonging to the same concept provides an advantage for learning low- similarity concept structures. This leaves open the question of the relative influence of similarity on interleaved versus blocked presentation. To answer this question, we pit within- and between-category similarity effects against each other in a rich categorization task called Physical Bongard Problems. We manipulate the similarity of instances shown temporally close to each other with blocked and interleaved presentation. The results indicate a stronger effect of similarity on interleaving than on blocking. They further show a large benefit of com- paring similar between-category instances on concept learning tasks where the feature dimensions are not known in advance but have to be constructed.


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