The effectiveness of feedback in multiple-cue probability learning

Ben R. Newell; Nicola J. Weston; Richard J. Tunney; David R. Shanks

doi:10.1080/17470210802351411

The effectiveness of feedback in multiple-cue probability learning

Ben R. Newell
, Nicola J. Weston
, Richard J. Tunney
, David R. Shanks

College of Health and Life Sciences

University College London

Research output: Contribution to journal › Article › peer-review

18 Citations (Scopus)

Abstract

How effective are different types of feedback in helping us to learn multiple contingencies? This article attempts to resolve a paradox whereby, in comparison to simple outcome feedback, additional feedback either fails to enhance or is actually detrimental to performance in nonmetric multiple-cue probability learning (MCPL), while in contrast the majority of studies of metric MCPL reveal improvements at least with some forms of feedback. In three experiments we demonstrate that if feedback assists participants to infer cue polarity then it can in fact be effective in nonmetric MCPL. Participants appeared to use cue polarity information to adopt a linear judgement strategy, even though the environment was nonlinear. The results reconcile the paradoxical contrast between metric and nonmetric MCPL and support previous findings of people's tendency to assume linearity and additivity in probabilistic cue learning.

Original language	English
Pages (from-to)	890-908
Number of pages	19
Journal	Quarterly Journal of Experimental Psychology
Volume	62
Issue number	5
DOIs	https://doi.org/10.1080/17470210802351411
Publication status	Published - 8 Jan 2009

Funding

Correspondence should be addressed to David R. Shanks, Division of Psychology and Language Sciences, University College London, Gower St, London WC1E 6BT, UK. E-mail: [email protected] The support of the Economic and Social Research Council (ESRC) and The Leverhulme Trust is gratefully acknowledged. The work was part of the programme of the ESRC Research Centre for Economic Learning and Social Evolution, University College London. We thank Joshua Klayman, Nigel Harvey, David Lagnado, and Henrik Olsson for valuable feedback on an earlier version of this article.

Keywords

Categorisation
Feedback
Judgement
Multiple-cue probability learning

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10.1080/17470210802351411

Cite this

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The effectiveness of feedback in multiple-cue probability learning

Abstract

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Keywords

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