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Toward a Science of Learning Games

Paul Howard‐Jones

Corresponding Author

Graduate School of Education, University of Bristol

Paul Howard‐Jones, 35 Berkeley Square, Bristol BS8 1JA, United Kingdom; e‐mail:

paul.howard‐jones@bris.ac.uk

.
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Skevi Demetriou

Graduate School of Education, University of Bristol

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Rafal Bogacz

Department of Computer Science, University of Bristol

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Jee H. Yoo

Department of Computer Science, University of Bristol

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Ute Leonards

Department of Experimental Psychology, University of Bristol

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First published: 21 February 2011
Cited by: 24

Note: Correction added on 14 March 2011 after first publication online on 21 February 2011. The co‐authors, Skevi Demetriou, Rafal Bogacz, Jee H. Yoo and Ute Leonards, and their affiliations, were erroneously missed out. The error has been corrected in this version of the article.

Abstract

Reinforcement learning involves a tight coupling of reward‐associated behavior and a type of learning that is very different from that promoted by education. However, the emerging understanding of its underlying processes may help derive principles for effective learning games that have, until now, been elusive. This article first reviews findings from cognitive neuroscience and psychology to provide insight into the motivating role of uncertain reward in games, including educational games. Then, a short experiment is reported to illustrate the potential of reward‐based neurocomputational models of behavior in the understanding and development of effective learning games. In this study, a reward‐based model of behavior is shown to predict recall of newly learned information during a simple learning game.

Number of times cited: 24

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