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Sghir, Nabila; Adadi, Amina; Lahmer, Mohammed – Education and Information Technologies, 2023
The last few years have witnessed an upsurge in the number of studies using Machine and Deep learning models to predict vital academic outcomes based on different kinds and sources of student-related data, with the goal of improving the learning process from all perspectives. This has led to the emergence of predictive modelling as a core practice…
Descriptors: Prediction, Learning Analytics, Artificial Intelligence, Data Collection
Nesrine Mansouri; Mourad Abed; Makram Soui – Education and Information Technologies, 2024
Selecting undergraduate majors or specializations is a crucial decision for students since it considerably impacts their educational and career paths. Moreover, their decisions should match their academic background, interests, and goals to pursue their passions and discover various career paths with motivation. However, such a decision remains…
Descriptors: Undergraduate Students, Decision Making, Majors (Students), Specialization
Korchi, Adil; Dardor, Mohamed; Mabrouk, El Houssine – Education and Information Technologies, 2020
Learning techniques have proven their capacity to treat large amount of data. Most statistical learning approaches use specific size learning sets and create static models. Withal, in certain some situations such as incremental or active learning the learning process can work with only a smal amount of data. In this case, the search for algorithms…
Descriptors: Learning Analytics, Data, Computation, Mathematics

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