Education
Inside the Black Box: Detecting and Mitigating Algorithmic Bias across Racialized Groups in College Student-Success Prediction
H. Anahideh, M. P. Ison, et al.
This study by Hadis Anahideh, Matthew P Ison, Anuja Tayal, and Denisa Gándara delves into the profound bias present in college student success prediction models, revealing significant racial disparities, particularly against Black and Hispanic students. The researchers explore multiple machine learning approaches and bias mitigation techniques, ultimately highlighting the challenges in achieving fairness in educational predictions.
Playback language: English
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