Abstract
E-learning systems, also called virtual learning environments, promote education and training activities using modern information and communication technologies. Therefore, e-learning is the application of modern multimedia technologies and the Internet to improve the quality of learning by making resources and services more accessible, as well as exchanges and collaboration at a distance that can help learners in their studies and that can also help teachers to predict the weaknesses, strengths, and level of understanding of learners. Preparing and providing a quality e-learning system and rich learning experience are significant challenges. The lack of interaction, feedback, helping the learner to self-regulate, assessing the degree of knowledge, and adapting teaching methods and resources to the learners’ real needs, which imply a lack of motivation and a high dropout rate, diminish the richness of the learning experience. Hence, we propose in this article a robust model of adaptive e-learning environments to optimize learning for each learner, taking into account the heterogeneity of profiles so that students succeed in their learning experiences.
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Kaiss, W., Mansouri, K., Poirier, F. (2022). Towards a Model of Self-regulated e-learning and Personalization of Resources. In: Maleh, Y., Alazab, M., Gherabi, N., Tawalbeh, L., Abd El-Latif, A.A. (eds) Advances in Information, Communication and Cybersecurity. ICI2C 2021. Lecture Notes in Networks and Systems, vol 357. Springer, Cham. https://doi.org/10.1007/978-3-030-91738-8_26
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DOI: https://doi.org/10.1007/978-3-030-91738-8_26
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