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Model-based reasoning
Affiliation:1. University of Oklahoma, USA;2. University of Freiburg, Germany;1. Departamento de Informática, Universidade Federal do Espírito Santo, Av. Fernando Ferrari 541, 29075-910 Vitória ES, Brazil;2. Departamento de Computação e Eletrônica, Universidade Federal do Espírito Santo, Rodovia BR 101 Norte Km. 60, 29932-540 São Mateus, ES, Brazil;3. Department of Computer Science, City University London Northampton Square, London EC1V 0HB, UK;2. State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, China;3. School of Information and Engineering, Huzhou Teachers College, Huzhou, Zhejiang, People''s Republic of China
Abstract:In this paper, there will be a particular focus on mental models and their application to inductive reasoning within the realm of instruction. A basic assumption of this study is the observation that the construction of mental models and related reasoning is a slowly developing capability of cognitive systems that emerges effectively with proper contextual and social support. More specifically, we first will identify some key elements of the structure and function of mental models in contrast to schemas. Next, these key elements of modeling will be used to generate some conjectures about the foundations of model-based reasoning. In the next section, we will describe the learning-dependent progression of mental models as a suitable approach for understanding the basics of deductive and inductive reasoning based on models as “tools for thought.” The rationale of mental models as tools for reasoning will be supported by empirical research to be described in a particular section of this paper. Finally, we will turn to the instructional implications of model-based reasoning by discussing appropriate instructional methods to affect the construction of mental models for performing deductive and inductive reasoning.
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