Addressing Threats to Validity in Supervised Machine Learning: A Framework and Best Practices for Education Researchers
Given the rapid adoption of machine learning methods by education researchers, and the growing acknowledgment of their inherent risks, there is an urgent need for tailored methodological guidance on how to improve and evaluate the validity of inferences drawn from these methods. Drawing on an integr...
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| Format: | Article |
| Language: | English |
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SAGE Publishing
2024-12-01
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| Series: | AERA Open |
| Online Access: | https://doi.org/10.1177/23328584241303495 |
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