Abstract
The growing expansion of smart devices and intelligent technologies encourages the development of intelligent learning environments where a personalized and adaptive learning process is offered. In this regard, we perform research on how to implement appropriate tutoring strategies to provide such a learning process in an Intelligent Educational System (IES) context. The paper discusses good practices in the conceptual model development of an IES within the project ISOSeM. Our research proposes a Knowledge Model for IES that can support dynamic learning path-based personalization. This model includes ontologically represented information about prerequisites, learners, learning goals, teaching strategies, course, educational content resources, and assessing learners’ knowledge. The approaches to an automatic selection and generation of personalized learning paths using the proposed model are considered. The goal is to accommodate tutoring to students’ real-time learning advance and make learning paths, activities, and resources meet learners’ individual needs and preferences.
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Acknowledgements
The authors would like to thank the Research and Development Sector at the Technical University of Sofia for the financial support. This research is supported by the Bulgarian FNI fund through the project “Modeling and Research of Intelligent Educational Systems and Sensor Networks (ISOSeM)”, contract КП-06-H47/4 from 26.11.2020.
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Terzieva, V., Ivanova, T., Todorova, K. (2023). Personalized Learning in an Intelligent Educational System. 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_2
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