Fair and Skill-Diverse Student Group Formation via Constrained k-Way Graph Partitioning
We introduce a constrained k-way graph partitioning approach for automated student group formation that maximizes skill diversity while ensuring fairness. Using Laplacian eigenmaps for dimensionality reduction of student course marks, our method balances group composition with respect to sensitive attributes while promoting diverse skill sets within each group. Our algorithm is now used routinely by 3 European universities.