Memory for exemplars in category learning

C. E.R. Edmunds, Andy J. Wills, Fraser N. Milton

Research output: Chapter in Book/Report/Conference proceedingConference proceedings published in a bookpeer-review

Abstract

Some argue that category learning is mediated by two competing learning systems: one explicit, one implicit (Ashby et al., 1998). These systems are hypothesised to be responsible for learning rule-based and information-integration category structures respectively. However, little experimental work has directly investigated whether people are conscious of category knowledge supposedly learned by the implicit system. Here we report one experiment that directly compared explicit recognition memory for exemplars between these two category structures. Contrary to the predictions of the dual-systems approach, we found preliminary evidence of superior exemplar memory after information-integration category learning compared to rule-based learning. This result is consistent with the hypothesis that participants learn information-integration category structures by using complex rules.

Original languageEnglish
Title of host publicationProceedings of the 38th Annual Meeting of the Cognitive Science Society, CogSci 2016
EditorsAnna Papafragou, Daniel Grodner, Daniel Mirman, John C. Trueswell
PublisherThe Cognitive Science Society
Pages2243-2248
Number of pages6
ISBN (Electronic)9780991196739
Publication statusPublished - 2016
Event38th Annual Meeting of the Cognitive Science Society: Recognizing and Representing Events, CogSci 2016 - Philadelphia, United States
Duration: 10 Aug 201613 Aug 2016

Publication series

NameProceedings of the 38th Annual Meeting of the Cognitive Science Society, CogSci 2016

Conference

Conference38th Annual Meeting of the Cognitive Science Society: Recognizing and Representing Events, CogSci 2016
Country/TerritoryUnited States
CityPhiladelphia
Period10/08/1613/08/16

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Human-Computer Interaction
  • Cognitive Neuroscience

Keywords

  • category learning
  • dual-systems
  • memory
  • recognition

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