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Erschienen in:
2019 | OriginalPaper | Buchkapitel
Identifying Knowledge from the Application of Natural Deduction Rules in Propositional Logic
verfasst von : Fabiane F. P. Galafassi, Cristiano Galafassi, Rosa Maria Vicari, João Carlos Gluz
Erschienen in: Advances in Practical Applications of Survivable Agents and Multi-Agent Systems: The PAAMS Collection
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Abstract
Intelligent Tutoring Systems (ITS) are technological resources widely used in teaching-learning processes, and their studies are directed, mainly, at distance learning. In this sense, the purpose of this work is the redesign of a Student Model agent, in the context of an ITS applied to the teaching of Natural Deduction in Propositional Logic (NDPL) for computing. It is expected that the agent will be able to identify and represent the students’ knowledge states. In the modeling stage, we present the details of the knowledge representation, as well as about the inference mechanism, based on Bayesian networks. Regarding the results, students are satisfied with the Heráclito environment and that the agent achieves its main objective, evidencing the possibility of implementing personalized teaching strategies based on individual characteristics and knowledge from the students.