Machine learning's model-agnostic interpretability on the prediction of students' academic performance in video-conference-assisted online learning during the covid-19 pandemic
Background: COVID-19 prompted a global shift to online learning, including video conference-assisted online learning (VCAOL), which necessitated educators understanding students' perspectives. Objective: This study aims to develop machine learning (ML) model-agnostic interpretability that could...
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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/S2666920X24001152 |
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