Predicting at-risk students in the early stage of a blended learning course via machine learning using limited data
Academic failure is a persistent challenge in education. Despite the limited available data, in this study, we focus on identifying at-risk students in a blended learning (BL) course. Several motivational variables are analyzed to determine their effect on student performance. We use a machine-learn...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-12-01
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| Series: | Computers and Education: Artificial Intelligence |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666920X2400064X |
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