Analogy as a strategy for supporting complex problem solving under uncertainty

被引:0
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作者
Joel Chan
Susannah B. F. Paletz
Christian D. Schunn
机构
[1] University of Pittsburgh,Learning Research and Development Center
来源
Memory & Cognition | 2012年 / 40卷
关键词
Problem solving; Analogy; Decision making; Reasoning; Judgment;
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摘要
Complex problem solving in naturalistic environments is fraught with uncertainty, which has significant impacts on problem-solving behavior. Thus, theories of human problem solving should include accounts of the cognitive strategies people bring to bear to deal with uncertainty during problem solving. In this article, we present evidence that analogy is one such strategy. Using statistical analyses of the temporal dynamics between analogy and expressed uncertainty in the naturalistic problem-solving conversations among scientists on the Mars Rover Mission, we show that spikes in expressed uncertainty reliably predict analogy use (Study 1) and that expressed uncertainty reduces to baseline levels following analogy use (Study 2). In addition, in Study 3, we show with qualitative analyses that this relationship between uncertainty and analogy is not due to miscommunication-related uncertainty but, rather, is primarily concentrated on substantive problem-solving issues. Finally, we discuss a hypothesis about how analogy might serve as an uncertainty reduction strategy in naturalistic complex problem solving.
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页码:1352 / 1365
页数:13
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