Combination and Differentiation Theories of Categorization: A Comparison Using Participants' Categorization Descriptions.

Abstract

Differentiation and Combination theories make different predictions about the order in which information is processed during categorization. Differentiation theory posits that holistic processing of a stimulus occurs before individual features are processed. According to Differentiation theory, overall similarity-based categorization is faster and less effortful compared to unidimensional categorization. In contrast, Combination theory posits that individual features are processed first and that information regarding these features must be combined during multidimensional categorization. According to Combination theory, overall similarity-based categorization is more effortful and takes more time compared to unidimensional categorization. In this study, we trained participants to learn artificial categories using classification learning and observation learning procedures. We used participants' categorization descriptions to determine the number of stimuli dimensions used for categorization. Our results from the first three experiments show that participants who used more dimensions took more time to categorize the transfer stimuli, consistent with Combination theory. In Experiment 4, we tested the hypothesis that using more dimensions takes more time solely due to multiple eye fixations and saccades. In our study, we used visual stimuli with features that do not overlap in space. Our results show that while performing a multidimensional task, participants need more time to recall the feature-category associations learned during the experiment, making the task more effortful, as predicted by Combination theory. Further studies are needed to determine whether Combination theory applies to other types of stimuli, particularly those with spatially non-separable features.