Feedback can be superior to observational training for both rule-based and information-integration category structures. Issue 6 (June 2015)

• Record Type: Journal Article
• Authors: Edmunds, C. E. R.; Milton, Fraser; Wills, Andy J.
• Is Part Of: Quarterly journal of experimental psychology. Volume 68:Issue 6(2015)
• Page Start: 1203
• Page End: 1222
• Publication Date: 2015-06
• Subjects: Competition between verbal and implicit systems -- COVIS -- Categorization -- Implicit -- Explicit -- Feedback; Psychology, Experimental -- Periodicals; Psychophysiology -- Periodicals; Psychology, Comparative -- Periodicals; 150.72405
• DOI: 10.1080/17470218.2014.978875
• Languages: English
• ISSNs: 1747-0218

Abstract

The effects of two different types of training on rule-based and information-integration category learning were investigated in two experiments. In observational training, a category label is presented, followed by an example of that category and the participant's response. In feedback training, the stimulus is presented, and the participant assigns it to a category and then receives feedback about the accuracy of that decision. Ashby, Maddox, and Bohil (2002. Observational versus feedback training in rule-based and information-integration category learning. Memory & Cognition, 30, 666–677) reported that feedback training was superior to observational training when learning information-integration category structures, but that training type had little effect on the acquisition of rule-based category structures. These results were argued to support the COVIS (competition between verbal and implicit systems) dual-process account of category learning. However, a number of nonessential differences between their rule-based and information-integration conditions complicate interpretation of these findings. Experiment 1 controlled between-category structures for participant error rates, category separation, and the number of stimulus dimensions relevant to the categorization. Under these more controlled conditions, rule-based and information-integration category structures both benefited from feedback training to a similar degree. Experiment 2 maintained this difference in training type when learning a rule-based category that had otherwise been matched, in terms of category overlap and overall performance, with the rule-based categories used in Ashby et al. These results indicate that differences in dimensionality between the category structures in Ashby et al. is a more likely explanation for the interaction between training type and category structure than the dual-system explanation that they offered.