Abstract
The integration of case-based reasoning mechanisms into E-learning systems is not a recent option. These mechanisms allow us to implement reasoning systems using similar experiences in a retrospectively way, which is quite attractive for problem solving in some application areas. Its application promotes the achievement of very interesting solutions, especially when an interesting case base exists a priori, integrating knowledge and appropriate problem-solving methods. In this paper, we present and describe a hybrid reasoning system especially developed to support student knowledge assessment processes in an E-learning platform. The system integrates two autonomous reasoning modules, which combine their functioning during knowledge assessment processes, combining rule-based and case-based knowledge, respecting a set of assessment restrictions defined a priori by a human supervisor.
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This work has been supported by FCT – Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020.
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Leite, J., Belo, O. (2023). Reinforcing Assessment Processes Using Proactive Case-Based Reasoning Mechanisms. In: García Bringas, P., et al. Hybrid Artificial Intelligent Systems. HAIS 2023. Lecture Notes in Computer Science(), vol 14001. Springer, Cham. https://doi.org/10.1007/978-3-031-40725-3_6
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DOI: https://doi.org/10.1007/978-3-031-40725-3_6
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