Induction: processes of inference, learning, and discovery
Induction: processes of inference, learning, and discovery
Mental models: towards a cognitive science of language, inference, and consciousness
Mental models: towards a cognitive science of language, inference, and consciousness
Foundations of cognitive science
Schemata and sequential thought processes in PDP models
Parallel distributed processing
Mental leaps: analogy in creative thought
Mental leaps: analogy in creative thought
Structural Knowledge: Techniques for Representing, Conveying, and Acquiring Structural Knowledge
Structural Knowledge: Techniques for Representing, Conveying, and Acquiring Structural Knowledge
Computers in Human Behavior
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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.