Collaborative learning with multiple cases

机译：具有多种案例的协作学习

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Professional training usually includes some form of learning with case problems. Exposure to problems in a context enables the critical acquisition of experiential and tacit knowledge of specialist comains. Often this form of training is within groups, where discursive processes become the basis for individual learning. In this paper we present a cognitive model of case based learning which characterizes this accumulation of experiential knowledge from exposure to multiple problem cases. In the model, the details of cases are retained whilst immediate abstractions from those details are often incomplete. The mapping of cases to subsequent problems leads to a more complete understanding of the retained cases, hence knowledge of a domain is acquired progres-sively through reuse. We illustrate the model with observations drawn from our studies of collaborative learning with multiple programming problems that have been matched using software patterns.

机译：专业培训通常包括某种形式的学习与案例问题。接触上下文中的问题使得能够批判获得专家的经验和默契知识。通常，这种形式的培训是在分组内，其中话语过程成为个人学习的基础。在本文中，我们提出了一种基于案例学习的认知模型，其特征在于在暴露于多个问题案例中的这种积累。在该模型中，案件的细节保留，而这些细节的立即抽象通常不完整。案例对后续问题的映射导致对保留案件的更完整的理解，因此通过重用来获取域的知识。我们说明了从我们对协作学习的研究中汲取的观察模式，通过使用软件模式匹配的多个编程问题。

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《ISPE international conference on concurrent engineering: Research and applications》|2003年||共6页
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M. Tscholl; J. Dowell; Concurrent Engineering: the Vision for the Future Generation in Research and Applications;
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中图分类专业化与协作;
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Collaborative learning with multiple cases

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