Predicting learning achievement using ensemble learning with result explanation.
Predicting learning achievement is a crucial strategy to address high dropout rates. However, existing prediction models often exhibit biases, limiting their accuracy. Moreover, the lack of interpretability in current machine learning methods restricts their practical application in education. To ov...
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Main Authors: | , |
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Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2025-01-01
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Series: | PLoS ONE |
Online Access: | https://doi.org/10.1371/journal.pone.0312124 |
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