Abstract
Augmented Reality has been an important part of engineering education, and more specific in the field of spatial skills training. Based on the literature review, desktop or mobile spatial ability training applications already developed, lack personalization as they do not identify students’ learning styles, and the activities delivered to them are the same complexity for all. In view of the above, this paper presents PARSAT, a developed mobile augmented reality spatial ability training system, which converts students’ knowledge to fuzzy weights, and delivers adaptive learning activities to students’ spatial skills. The innovation of the developed system is that PARSAT is a student-centered system, delivering adaptive domain knowledge content, using the technology of fuzzy weights in a rule-based decision-making module. As a testbed of this research, the developed system has been incorporated in the laboratory course deliveries of a computer-aided-design university course, and has been evaluated by the students during the 2021–22 winter semester.
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Papakostas, C., Troussas, C., Krouska, A., Sgouropoulou, C. (2023). Modeling the Knowledge of Users in an Augmented Reality-Based Learning Environment Using Fuzzy Logic. In: Krouska, A., Troussas, C., Caro, J. (eds) Novel & Intelligent Digital Systems: Proceedings of the 2nd International Conference (NiDS 2022). NiDS 2022. Lecture Notes in Networks and Systems, vol 556. Springer, Cham. https://doi.org/10.1007/978-3-031-17601-2_12
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