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Seeing Change in Time: Video Games to Teach about Temporal Change in Scientific Phenomena

Journal of Science Education and Technology volume 23, pages 324–343 (2014)Cite this article

Abstract

This article explores how learning biological concepts can be facilitated by playing a video game that depicts interactions and processes at the subcellular level. Particularly, this article reviews the effects of a real-time strategy game that requires players to control the behavior of a virus and interact with cell structures in a way that resembles the actual behavior of biological agents. The evaluation of the video game presented here aims at showing that video games have representational advantages that facilitate the construction of dynamic mental models. Ultimately, the article shows that when video game’s characteristics come in contact with expert knowledge during game design, the game becomes an excellent medium for supporting the learning of disciplinary content related to dynamic processes. In particular, results show that students who participated in a game-based intervention aimed at teaching biology described a higher number of temporal-dependent interactions as measured by the coding of verbal protocols and drawings than students who used texts and diagrams to learn the same topic.

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Acknowledgments

This research was supported partially by grants from DIB-UNAL to Javier Corredor (Grant: Hermes-14780).

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Authors and Affiliations

  1. Psychology Department, Universidad Nacional de Colombia, Carrera 45 No 26–85, Ed. 212, Of. 211, Bogotá, Colombia

    Javier Corredor

  2. Center for Games Learning and Society, University of Wisconsin-Madison, Madison, WI, USA

    Matthew Gaydos & Kurt Squire

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  1. Javier Corredor
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  2. Matthew Gaydos
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Correspondence to Matthew Gaydos.

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Corredor, J., Gaydos, M. & Squire, K. Seeing Change in Time: Video Games to Teach about Temporal Change in Scientific Phenomena. J Sci Educ Technol 23, 324–343 (2014). https://doi.org/10.1007/s10956-013-9466-4

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Keywords

  • Video games
  • Learning
  • Biology
  • Dynamic mental models
  • Dynamic visual representations