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Imhof, Christof; Comsa, Ioan-Sorin; Hlosta, Martin; Parsaeifard, Behnam; Moser, Ivan; Bergamin, Per – IEEE Transactions on Learning Technologies, 2023
Procrastination, the irrational delay of tasks, is a common occurrence in online learning. Potential negative consequences include a higher risk of drop-outs, increased stress, and reduced mood. Due to the rise of learning management systems (LMS) and learning analytics (LA), indicators of such behavior can be detected, enabling predictions of…
Descriptors: Prediction, Time Management, Electronic Learning, Artificial Intelligence
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Herodotou, Christothea; Hlosta, Martin; Boroowa, Avinash; Rienties, Bart; Zdrahal, Zdenek; Mangafa, Chrysoula – British Journal of Educational Technology, 2019
This study presents an advanced predictive learning analytics system, OU Analyse (OUA), and evidence from its evaluation with online teachers at a distance learning university. OUA is a predictive system that uses machine learning methods for the early identification of students at risk of not submitting (or failing) their next assignment.…
Descriptors: Learning Analytics, Teacher Empowerment, Distance Education, College Faculty
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Herodotou, Christothea; Rienties, Bart; Boroowa, Avinash; Zdrahal, Zdenek; Hlosta, Martin – Educational Technology Research and Development, 2019
By collecting longitudinal learner and learning data from a range of resources, predictive learning analytics (PLA) are used to identify learners who may not complete a course, typically described as being at risk. Mixed effects are observed as to how teachers perceive, use, and interpret PLA data, necessitating further research in this direction.…
Descriptors: Prediction, Learning Analytics, Teacher Role, Teacher Attitudes