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Analogical Learning: Mapping and Integrating Partial Mental Models
Abstract
Descriptions of scientific and technical systems take a number of different forms. Depending upon thepurpose of a description, it may focus on a system's behavior, causaliiy, physical or functional topology,or structural composition. An analogical explanation used to teach someone about such a system is alsotypically geared to one or another of these purposes. In this paper we describe some research leading tothe development of a theory of the role of explanatory model types in the generation of analogicalmappings. The work is motivated by the larger question of how explanations presented as analogies areapplied by students learning about new domains. Our long term goals are (1) the development of atheory of purpose-guided analogical learning, based on a coherent taxonomy of mental model types, and(2) the development of a theory of the integration of partial mental models during learning, usingprinciples for relating different explanatory model types.
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