Accurate, timely, and portable: Course-agnostic early prediction of student performance from LMS logs
In higher education, providing personalized feedback and support to students is a significant challenge. Early warning systems can help by identifying both at-risk and high-performing students, allowing for timely interventions and enhanced learning opportunities. In our study, we used a year's...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-01-01
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| Series: | Computers and Education: Artificial Intelligence |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666920X23000541 |