2023
DOI: 10.14569/ijacsa.2023.0140528
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Towards an Adaptive e-Learning System Based on Deep Learner Profile, Machine Learning Approach, and Reinforcement Learning

Riad Mustapha,
Gouraguine Soukaina,
Qbadou Mohammed
et al.

Abstract: Now-a-days, the great challenge of adaptive elearning systems is to recommend an individualized learning scenario according to the specific needs of learners. Therefore, the perfect adaptive e-learning system is the one that is based on a deep learner profile to recommend the most appropriate learning objects for that learner. Yet, the majority of existing adaptive e-learning systems do not give high importance to the adequacy of the real learner profile and its update with the one taken into account in the le… Show more

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Cited by 2 publications
(1 citation statement)
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“…The outcomes show how learners' learning can be improved by properly presenting learning objects. To create relevant and adaptive courses, Riad et al [23] proposed an intelligent adaptive e-learning system, that takes into consideration the deep learner profile to recommend the most appropriate learning objects for learner. The proposed system uses machine learning and reinforcement learning algorithms to recommending a list of the most appropriate learning objects for learners according to their deep profile.…”
Section: Previous Related Workmentioning
confidence: 99%
“…The outcomes show how learners' learning can be improved by properly presenting learning objects. To create relevant and adaptive courses, Riad et al [23] proposed an intelligent adaptive e-learning system, that takes into consideration the deep learner profile to recommend the most appropriate learning objects for learner. The proposed system uses machine learning and reinforcement learning algorithms to recommending a list of the most appropriate learning objects for learners according to their deep profile.…”
Section: Previous Related Workmentioning
confidence: 99%