A multi-objective optimization approach for the group formation problem

Group formation is one of the essential stages of collaborative learning. This paper proposes an intelligent computational approach to optimize the group formation process taking into account multiple criteria: inter-homogeneity, intra-heterogeneity, and empathy. More specifically, it uses a genetic algorithm to maximize the number of different student profiles in each group. The proposed method was evaluated regarding its computational performance comparing against three baselines; and in a real educational application, where it was compared with random and self-organized methods. The results showed the potential of the proposed method from both the computational and pedagogical points of view.