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Why does cue polarity information provide benefits in inference problems?: The role of strategy selection and knowledge of cue importance
University of Basel, Department of Psychology, Switzerland.
Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology.
Max Planck Institute for Human Development, Berlin, Germany. (University of Basel, Department of Psychology, Switzerland)
Clarkson University, Department of Psychology, USA.
2013 (English)In: Acta Psychologica, ISSN 0001-6918, E-ISSN 1873-6297, Vol. 144, no 1, 73-82 p.Article in journal (Refereed) Published
Abstract [en]

Knowledge about cue polarity (i.e., the sign of a cue–criterion relation) seems to boost performance in a wide range of inference tasks. Knowledge about cue polarity information may enhance performance by increasing (1) the reliance on rule- relative to similarity-based strategies, and (2) explicit knowledge about the relative importance of cues. We investigated the relative contribution of these two mechanisms in a multiple-cue judgment task and a categorization task, which typically differ in the inference strategies they elicit and potentially the explicit task knowledge available to participants. In both tasks participants preferred rule-based relative to similarity-based strategies and had more knowledge about cue importance when cue polarity information was provided. Strategy selection was not related to increases in performance in the categorization task and could only partly explain increases in performance in the judgment task. In contrast, explicit knowledge about the importance of cues was related to better performance in both categorization and judgment independently of the strategy used. In sum, our results suggest that the benefits of receiving cue polarity information may span across tasks, such multiple-cue judgment and categorization, primarily by enhancing knowledge of relative cue importance.

Place, publisher, year, edition, pages
Elsevier, 2013. Vol. 144, no 1, 73-82 p.
Keyword [en]
Category learning, Judgment, Decision making, Knowledge, Computational modeling
National Category
Psychology Physiology
Identifiers
URN: urn:nbn:se:umu:diva-80739DOI: 10.1016/j.actpsy.2013.05.007OAI: oai:DiVA.org:umu-80739DiVA: diva2:652571
Available from: 2013-10-01 Created: 2013-09-25 Last updated: 2018-01-11Bibliographically approved

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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
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  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
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  • nn-NO
  • nn-NB
  • sv-SE
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Output format
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  • asciidoc
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