The Illusion of Fairness: A Systematic Study of Unsupervised Domain Adaptation on Sparse Educational Data

Read full text
Authors: Arjun Adhikari
Cited by: 0

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