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Mejbri, Nesreen; Essalmi, Fathi; Jemni, Mohamed; Alyoubi, Bader A. – Education and Information Technologies, 2022
Considering that emotions have a great impact on motivation, reasoning, and decision making, affective computing methods, that were designed to attempt to understand and respond to human emotional states, have been used in more than one field including e-learning. Thus, a systematic literature review was conducted on 4 search engines resulting in…
Descriptors: Educational Technology, Technology Uses in Education, Emotional Response, Affective Behavior
Ghallabi, Sameh; Essalmi, Fathi; Jemni, Mohamed; Kinshuk – Smart Learning Environments, 2022
Personalized learning systems use several components in order to create courses adapted to the learners'characteristics. Current emphasis on the reduction of costs of development of new resources has motivated the reuse of the e-learning personalization components in the creation of new components. Several systems have been proposed in the…
Descriptors: Individualized Instruction, Technology Uses in Education, Electronic Learning, Mathematics
Tlili, Ahmed; Denden, Mouna; Essalmi, Fathi; Jemni, Mohamed; Chang, Maiga; Kinshuk; Chen, Nian-Shing – Interactive Learning Environments, 2023
The ability of automatically modeling learners' personalities is an important step in building adaptive learning environments. Several studies showed that knowing the personality of each learner can make the learning interaction with the provided learning contents and activities within learning systems more effective. However, the traditional…
Descriptors: Learning Analytics, Learning Management Systems, Intelligent Tutoring Systems, Bayesian Statistics
Khribi, Mohamed Koutheair; Jemni, Mohamed; Nasraoui, Olfa – Educational Technology & Society, 2009
In this paper, we describe an automatic personalization approach aiming to provide online automatic recommendations for active learners without requiring their explicit feedback. Recommended learning resources are computed based on the current learner's recent navigation history, as well as exploiting similarities and dissimilarities among…
Descriptors: Electronic Learning, Feedback (Response), Information Retrieval, Active Learning