An Empirical Study of Computer System Learning: Comparison of Co-Discovery and Self-Discovery Methods

Kai H. Lim, Lawrence M. Ward and Izak Benbasat
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Kai H. Lim: Department of Decision Sciences, College of Business Administration, University of Hawaii, Honolulu, Hawaii 96822
Lawrence M. Ward: Department of Psychology, University of British Columbia, Vancouver, British Columbia, Canada V6T 1Z4
Izak Benbasat: Faculty of Commerce and Business Administration, University of British Columbia, Vancouver, British Columbia, Canada V6T 1Z2

Information Systems Research, 1997, vol. 8, issue 3, 254-272

Abstract: This paper reports a study that examined two types of exploratory computer learning methods: self-discovery vs. co-discovery, the latter of which involves two users working together to learn a system. An experiment was conducted to compare these two methods and the results were interpreted within a mental model framework. Co-discovery subjects were better than self-discovery subjects at making inferences about the capability and extended functions of the system. Furthermore, while working by themselves after an initial period of learning, they performed better in a similar, though more complex task than the one they encountered at the learning phase. Process tracing analysis showed that self-discovery subjects focused more on surface structures, such as detailed physical actions, for implementing the task. On the other hand, co-discovery groups focused more on relating lower level actions to higher level goals. Therefore, co-discovery subjects had a better understanding of the relationships between the physical actions and goals, and hence formed mental models with higher inference potential than self-discovery subjects.

Keywords: mental models; verbal protocols; computer system learning; co-discovery learning; process tracing; inference (search for similar items in EconPapers)
Date: 1997
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