Can Modeling Foster Analogical Reasoning?

Karen Carney; Kenneth D. Forbus; Leo C. Ureel II; Danielle Fisher

Can Modeling Foster Analogical Reasoning?

于Model-Based Approaches to Learning

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Karen Carney

Karen Carney Adler Planetarium Chicago Illinois

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Kenneth D. Forbus

Kenneth D. Forbus Qualitative Reasoning Group, Northwestern University Evanston Illinois

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Leo C. Ureel II

Leo C. Ureel II Qualitative Reasoning Group, Northwestern University Evanston Illinois

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Danielle Fisher

Danielle Fisher School of Social Work University of Chicago Chicago Illinois

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类型:: 章节

Page Range:: 73–109

DOI:: https://doi.org/10.1163/9789087907112_008

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This paper explores the question of whether engaging students in a particular kind of external representation, the creation of computationally supported models, can help students to reason analogically about multiple systems modeled with the same software. We claim that several representational aspects of modeling can be used productively to this end, including constraints on the kind of causal story shown and the limited representational vocabulary and grammar used to make the model itself. We evaluate our design claims with data from seventh grade students taken during a clinical interview task in which they model a system that is analogical to a previously modelled system. Student models and interview data are considered. We find evidence that some students do reason analogically about their models and argue that the representational features of the software have helped them to do so.

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Model-Based Approaches to Learning

Using Systems Models and Simulations to Improve Understanding and Problem Solving in Complex Domains

丛编： Modeling and Simulation for Learning and Instruction, 卷： 4

Cover Model-Based Approaches to Learning

ISBN:: 9789087907112

出版社:: Brill

印刷出版日期:: 01 Jan 2009

Subjects
- Education
  - Educational Technology

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Can Modeling Foster Analogical Reasoning?

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Model-Based Approaches to Learning

Using Systems Models and Simulations to Improve Understanding and Problem Solving in Complex Domains

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