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Huang, Karina; Bryant, Tonya; Schneider, Bertrand – International Educational Data Mining Society, 2019
With the advent of new data collection techniques, there has been a growing interest in studying co-located groups of students using Multimodal Learning Analytics to automatically identify collaborative learning states. In this paper, we analyze a multimodal dataset (N=84) made of eye-tracking, physiological and motion sensing data. We leverage…
Descriptors: Cooperative Learning, Artificial Intelligence, Eye Movements, Learning Analytics
Morsy, Sara; Karypis, George – International Educational Data Mining Society, 2019
Grade prediction for future courses not yet taken by students is important as it can help them and their advisers during the process of course selection as well as for designing personalized degree plans and modifying them based on their performance. One of the successful approaches for accurately predicting a student's grades in future courses is…
Descriptors: Grades (Scholastic), Models, Prediction, Predictor Variables