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Virtual Environments and the Acceleration of Experiential Learning

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  • Chris Wild

Abstract

Darius et al. (2007) and Nolan & Temple Lang (2007) give examples of virtual environments that can, for specific purposes, substitute for the real world. We are in the early stages of developments that could revolutionize statistics education by making it possible to capture efficiently important aspects of the thinking and practice of professional statisticians previously learned only from long years of experience. The ability of virtual environments to automate processes provides a potent weapon for tackling the tyranny that Time exercises over such modes of learning. We discuss the many new possibilities that are opened up by virtual environments together with cognitive and pedagogical imperatives to be addressed to ensure that environments actually do teach the lessons they were designed to teach. We echo Nolan and Temple Lang's call for the development of environments to be modular and open source. Taking the R‐project as a model, this can lead to a growing repository of building blocks that make the construction of future environments less costly, thus facilitating the realization of more and more ambitious conceptions.

Suggested Citation

  • Chris Wild, 2007. "Virtual Environments and the Acceleration of Experiential Learning," International Statistical Review, International Statistical Institute, vol. 75(3), pages 322-335, December.
  • Handle: RePEc:bla:istatr:v:75:y:2007:i:3:p:322-335
    DOI: 10.1111/j.1751-5823.2007.00033.x
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    References listed on IDEAS

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    1. Joan Garfield & Dani Ben‐Zvi, 2007. "How Students Learn Statistics Revisited: A Current Review of Research on Teaching and Learning Statistics," International Statistical Review, International Statistical Institute, vol. 75(3), pages 372-396, December.
    2. Paul L. Darius & Kenneth M. Portier & Eddie Schrevens, 2007. "Virtual Experiments and Their Use in Teaching Experimental Design," International Statistical Review, International Statistical Institute, vol. 75(3), pages 281-294, December.
    3. George W. Cobb, 2007. "One Possible Frame for Thinking about Experiential Learning," International Statistical Review, International Statistical Institute, vol. 75(3), pages 336-347, December.
    4. Joan B. Garfield & Iddo Gal, 1999. "Assessment and Statistics Education: Current Challenges and Directions," International Statistical Review, International Statistical Institute, vol. 67(1), pages 1-12, April.
    5. Deborah Nolan & Duncan Temple Lang, 2007. "Dynamic, Interactive Documents for Teaching Statistical Practice," International Statistical Review, International Statistical Institute, vol. 75(3), pages 295-321, December.
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    Cited by:

    1. Peter Petocz & Anna Reid, 2010. "On Becoming a Statistician—A Qualitative View," International Statistical Review, International Statistical Institute, vol. 78(2), pages 271-286, August.
    2. Chris J. Wild & Maxine Pfannkuch & Matt Regan & Ross Parsonage, 2017. "Accessible Conceptions of Statistical Inference: Pulling Ourselves Up by the Bootstraps," International Statistical Review, International Statistical Institute, vol. 85(1), pages 84-107, April.

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