Enhancing the Early Student Dropout Prediction Model Through Clustering Analysis of Students’ Digital Traces
Educational Data Mining and learning analytics have gained significant prominence in recent years, garnering attention from researchers worldwide. This is primarily due to their potential to improve decision-making processes within higher education. This study utilizes Educational Data Mining to sug...
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| Автори: | , |
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| Формат: | Artigo |
| Мова: | Inglês |
| Опубліковано: |
IEEE
2024-01-01
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| Серія: | IEEE Access |
| Предмети: | |
| Онлайн доступ: | https://ieeexplore.ieee.org/document/10736593/ |
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