Predicting students at risk of academic failure using ensemble model during pandemic in a distance learning system
Abstract Predicting students at risk of academic failure is valuable for higher education institutions to improve student performance. During the pandemic, with the transition to compulsory distance learning in higher education, it has become even more important to identify these students and make i...
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| Auteurs principaux: | , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
SpringerOpen
2021
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/e89539dd763a4f558d88492d3563f365 |
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