Towards an Intelligent Tutoring System for Logical Reasoning in Multiple Contexts
In this paper we present a participatory approach to design Logic-Muse, an Intelligent Tutoring System that helps learners develop reasoning skills in multiple contexts (situations). The study was conducted jointly with the active participation of experts in the field of logic and the psychology of reasoning. An explicit catalogue of systematic errors in classical logic is built, followed by an explicit representation and encoding of the semantic knowledge behind reasoning as well as reasoning procedural structures and meta-structures. Logic-Muse innovates through its design rationale, which leads to strong structures on which learning is based. It also innovates with the projection of reasoning skills in a variety of well-defined classes of situations to ensure an absolute mastery of reasoning skills regardless of the content effect.
KeywordsIntelligent tutoring system Reasoning skills Formal logic learning
We would like to thank all Logic-Muse team members (J. Bourdeau, M. Bélanger, A, Cloutier, J-B Plouhinec, H. Markovits and M. Sainte-Marie) for their contribution to this work.
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