Towards an explanatory framework for learning in artificial environments

Authors: Winn W.¹; Windschitl M.²

Source: Cybernetics & Human Knowing, Volume 8, Number 4, 2001 , pp. 5-23(19)

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Abstract:

Learning takes place in a variety of environments, ranging from the natural world to schools. Computer-generated artificial environments can emulate any of these environments and, at the same time, offer the student additional ways to learn. These derive from the ability of artificial environments to completely immerse the student in the environment, to simulate the natural environment, to make properties of the natural world, not normally accessible to the senses, available in a manner that affords interaction, and to build pedagogical strategies seamlessly into the environment itself. Learning in artificial environments, like learning in natural environments, is most successful when students construct knowledge for themselves as they interact with the environment and observe the consequences of their actions. Research in our laboratory and elsewhere is beginning to shed light on how working in artificial environments can help students learn through a process not unlike the dynamic adaptation of any living organism to its environment. This approach suggests that an adaptive, second-order cybernetic view of learning in artificial environments might be a useful theoretical lens through which to view theory and interpret data. In this article, we suggest an explanatory framework that embodies these ideas.

Language: English

Document Type: Research article

Affiliations: 1: College of Education and Human Interface Technology Laboratory, University of Washington, Seattle, WA, USA. Email: billwinn@u.washington.edu 2: Email: mwind@u.washington.edu

Publication date: 2001-01-01