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Fazeli, Soude; Drachsler, Hendrik; Bitter-Rijpkema, Marlies; Brouns, Francis; Brouns, Wim van der Vegt; Sloep, Peter B. – IEEE Transactions on Learning Technologies, 2018
Recommender systems provide users with content they might be interested in. Conventionally, recommender systems are evaluated mostly by using prediction accuracy metrics only. But, the ultimate goal of a recommender system is to increase user satisfaction. Therefore, evaluations that measure user satisfaction should also be performed before…
Descriptors: Evaluation, Socialization, Accuracy, Prediction
Ortigosa, Alvaro; Carro, Rosa M.; Bravo-Agapito, Javier; Lizcano, David; Alcolea, Juan Jesus; Blanco, Oscar – IEEE Transactions on Learning Technologies, 2019
This paper presents the work done to support student dropout risk prevention in a real online e-learning environment: A Spanish distance university with thousands of undergraduate students. The main goal is to prevent students from abandoning the university by means of retention actions focused on the most at-risk students, trying to maximize the…
Descriptors: At Risk Students, Dropout Prevention, Undergraduate Students, Distance Education