The Illusion of Fairness: A Systematic Study of Unsupervised Domain Adaptation on Sparse Educational Data
Abstract
Through a systematic evaluation using the Open University Learning Analytics Dataset (OULAD), this study ex-amines Correlation Alignment (CORAL) across 42 transfer pairs (N= 32,593). The findings reveal a pervasivefailure mode: CORAL consistently degraded model accuracy in 93% of cases (Mean Drop: -18.0%) and failedto yield reliable improvements in fairness metrics. These results suggest that the ”feature structure destruction”inherent in sparse, one-hot encoded data, coupled with significant label shift, renders naive alignment methodscounterproductive in educational contexts.
Fields of Study & Subjects
Advanced Graph Neural Networks
Domain Adaptation and Few-Shot Learning
Computational and Text Analysis Methods
Publication details
- Publication date
- 3 January 2026
- Document type
- Preprint