Training Anchoring and Representativeness Bias Mitigation Through a Digital Game

Yu Hao Lee, Norah E. Dunbar, Claude H. Miller, Brianna L. Lane, Matthew L. Jensen, Elena Bessarabova, Judee K. Burgoon, Bradley Adame, Joseph J. Valacich, Elissa Adame, Eryn Bostwick, Cameron W. Piercy, Javier Elizondo, Scott N. Wilson

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Objective. Humans systematically make poor decisions because of cognitive biases. Can digital games train people to avoid cognitive biases? The goal of this study is to investigate the affordance of different educational media in training people about cognitive biases and to mitigate cognitive biases within their decision-making processes. Method. A between-subject experiment was conducted to compare a digital game, a traditional slideshow, and a combined condition in mitigating two types of cognitive biases: anchoring bias and representativeness bias. We measured both immediate effects and delayed effects after four weeks. Results. The digital game and slideshow conditions were effective in mitigating cognitive biases immediately after the training, but the effects decayed after four weeks. By providing the basic knowledge through the slideshow, then allowing learners to practice bias-mitigation techniques in the digital game, the combined condition was most effective at mitigating the cognitive biases both immediately and after four weeks.

Original languageEnglish (US)
Pages (from-to)751-779
Number of pages29
JournalSimulation and Gaming
Volume47
Issue number6
DOIs
StatePublished - Dec 1 2016

Keywords

  • anchoring
  • cognitive bias
  • digital game
  • heuristics
  • representativeness

ASJC Scopus subject areas

  • Business, Management and Accounting (miscellaneous)
  • Computer Science Applications

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