Abstract
One of the key requirements of IT learning environments is to possess the adaptation and personalization capabilities necessary for sufficiently efficient, or at least, sufficiently effective learning. Most studies focus on one aspect of adaptation more than others at the risk of creating unbalanced learning situations. Our hypothesis is that the effectiveness of learning is also dependent on multidimensional adaptation. This work aims to propose a model with sufficient adaptability in some of the aspects of the learning situation. A generic model of the domain, with diversified pedagogical structures, is the first half of the response we propose. It represents the foundations for a multi-agent system that will have multi-aspect adaptive faculties, particularly, those related to the management of the support for the learning process.
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Notes
- 1.
This abbreviation may be confusing because it is also widely used for ‘Learning Object’.
- 2.
Gagné’s framework [12] is widely adopted, particularly in the domain of Instructional Design.
- 3.
We considered Gagné’s framework too (instead of Bloom’s taxonomy [13] for instance) to maintain consistency with the preceding attribute (type of knowledge). Different lists of interpreted Gagné’s learning types and learning outcomes exist indeed.
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Tenachi, AeD., Cherrid, H., Boussaha, K. (2024). Towards Multi-Agent Personalized Adaptive Generic Learning System – A Generic Pedagogical Domain Modeling. In: Mylonas, P., Kardaras, D., Caro, J. (eds) Novel and Intelligent Digital Systems: Proceedings of the 4th International Conference (NiDS 2024). NiDS 2024. Lecture Notes in Networks and Systems, vol 1170. Springer, Cham. https://doi.org/10.1007/978-3-031-73344-4_58
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