Relational labels can improve relational retrieval

Anja Jamrozik, Dedre Gentner

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

Retrieval that is based on common relational structure, such as an underlying principle or pattern, is useful but typically rare. Based on evidence that comparison-derived schema abstraction can improve relational retrieval, we asked whether the use of relational labels can also promote abstraction and improve relational retrieval. Using a cued-recall paradigm, we varied the presence of relational labels at encoding and test. As compared to a no-label baseline condition, relational retrieval improved when relational labels were given at encoding and at test and also when relational labels were given only at encoding. The findings demonstrate that one way to improve relational retrieval is through the use of labels that name relational structure.

Original languageEnglish (US)
Title of host publicationCooperative Minds
Subtitle of host publicationSocial Interaction and Group Dynamics - Proceedings of the 35th Annual Meeting of the Cognitive Science Society, CogSci 2013
EditorsMarkus Knauff, Natalie Sebanz, Michael Pauen, Ipke Wachsmuth
PublisherThe Cognitive Science Society
Pages651-656
Number of pages6
ISBN (Electronic)9780976831891
StatePublished - 2013
Event35th Annual Meeting of the Cognitive Science Society - Cooperative Minds: Social Interaction and Group Dynamics, CogSci 2013 - Berlin, Germany
Duration: Jul 31 2013Aug 3 2013

Publication series

NameCooperative Minds: Social Interaction and Group Dynamics - Proceedings of the 35th Annual Meeting of the Cognitive Science Society, CogSci 2013

Conference

Conference35th Annual Meeting of the Cognitive Science Society - Cooperative Minds: Social Interaction and Group Dynamics, CogSci 2013
Country/TerritoryGermany
CityBerlin
Period7/31/138/3/13

Keywords

  • inert knowledge
  • relational language
  • relational retrieval

ASJC Scopus subject areas

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

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