Analyzing iterative training game design: A multi-method postmortem analysis of CYCLES Training Center and CYCLES Carnivale

Adrienne Shaw, Brian McKernan, Rosa M. Martey, Jennifer Stromer-Galley, Emilie T. Saulnier, Elizabeth McLaren, Matthew G. Rhodes, James E. Folkestad, Sarah M. Taylor, Kate Kenski, Benjamin A. Clegg, Tomek Stralkowski

Research output: Contribution to journalArticlepeer-review

Abstract

That games can be used to teach specific content has been demonstrated numerous times. However, although specific game features have been conjectured to have an impact on learning outcomes, little empirical research exists on the impact of iterative design on learning outcomes. This article analyzes two games that have been developed to train an adult audience to recognize and avoid relying on six cognitive biases (three per game) in their decision making. The games were developed iteratively and were evaluated through a series of experiments. Although the experimental manipulations did not find a significant impact of the manipulated game features on the learning outcomes, each game iteration proved more successful than its predecessors at training players. Here, we outline a mixed-methods approach to postmortem game design analysis that helps us understand what might account for the improvement across games, and to identify new variables for future experimental training game studies.

Original languageEnglish (US)
Article number46
JournalMultimodal Technologies and Interaction
Volume2
Issue number3
DOIs
StatePublished - Sep 2018

Keywords

  • Cognitive biases
  • Game design
  • Learning
  • Post mortem
  • Quantitative
  • Training
  • Video games

ASJC Scopus subject areas

  • Neuroscience (miscellaneous)
  • Human-Computer Interaction
  • Computer Science Applications
  • Computer Networks and Communications

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