A personalized federated deep learning framework predicts student performance in large-scale examinations across heterogeneous regional distributions
The findings indicate that regionally adaptive models can support targeted resource allocation, while cautioning that systems predicting attainment from environmental context risk formalising the disadvantage they measure.