Abstract
This paper describes an approach to support the decision making process in the Intelligent Tutoring Systems (ITS) and provide graphical presentation of the ITS decisions. The discussion focuses on the issue of explainability of the decisions made by the ITS and their explanation to a human learner. Highlighting the most significant aspects in the interpretation of the learning situation and their further use by the ITS intelligent scheduler is based on the mapping mechanism and the cross-cutting approach to switching between the maps. The feedback synthesis in the form of the dialogue is based on parametric maps and their visualization using CMKD notation. The maps are combined into an atlas, which is used as the basis for decision-making when switching from the combined map to the particular maps. An example of learning situation analysis using the cross-cutting approach in the experimental ITS is discussed in detail.
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Uglev, V. (2023). Case Study of Organization of Decision-Making and Feedback Synthesis in Intelligent Tutoring Systems with a Cross-Cutting Approach. In: Kabassi, K., Mylonas, P., Caro, J. (eds) Novel & Intelligent Digital Systems: Proceedings of the 3rd International Conference (NiDS 2023). NiDS 2023. Lecture Notes in Networks and Systems, vol 783. Springer, Cham. https://doi.org/10.1007/978-3-031-44097-7_11
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