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J. Bryan Osborne; Andrew S. I. D. Lang – Journal of Postsecondary Student Success, 2023
This paper describes a neural network model that can be used to detect at- risk students failing a particular course using only grade book data from a learning management system. By analyzing data extracted from the learning management system at the end of week 5, the model can predict with an accuracy of 88% whether the student will pass or fail…
Descriptors: Identification, At Risk Students, Learning Management Systems, Prediction
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Wang, Yuancheng; Luo, Nanyu; Zhou, Jianjun – International Educational Data Mining Society, 2022
Doing assignments is a very important part of learning. Students' assignment submission time provides valuable information on study attitudes and habits which strongly correlate with academic performance. However, the number of assignments and their submission deadlines vary among university courses, making it hard to use assignment submission…
Descriptors: College Students, Assignments, Time, Scheduling