Abstract
E-learning software is oriented to a heterogeneous group of learners. Thus, such systems need to provide personalization to students’ needs and preferences so that their knowledge acquisition could become more effective. One personalization mechanism is the adaptation to the students’ learning modalities. However, this process requires a lot of time when happening manually and is error-prone. In view of the above, this paper presents a novel technique for learning modalities detection. Our approach utilizes the Honey-Mumford model, which classifies students in activists, reflectors, theorists and pragmatists. Furthermore, the automatic detection uses the fuzzy logic technique taking as input the students’ interaction with the learning environment, namely the kind of learning units visited, their type of media, the comments made by students on learning units and their participation in discussions. Our novel technique was incorporated is a tutoring system for learning computer programming and was evaluated with very promising results.
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Troussas, C., Krouska, A., Sgouropoulou, C. (2020). Dynamic Detection of Learning Modalities Using Fuzzy Logic in Students’ Interaction Activities. In: Kumar, V., Troussas, C. (eds) Intelligent Tutoring Systems. ITS 2020. Lecture Notes in Computer Science(), vol 12149. Springer, Cham. https://doi.org/10.1007/978-3-030-49663-0_24
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