Genetic Algorithm for Forming Student Groups Based on Heterogeneous Grouping

Student group formation plays a critical role in terms of enhancing the success of academic learning. It involves structuring groups in order to help students to learn together. Due to the heterogeneity of students in classes, the process of forming student groups is becoming more complex. In this paper, we proposed an approach to form student groups at a university for software development project to ensure that software products can be delivered successfully on time. Our proposed algorithm is called Genetic Algorithm for Heterogeneous Grouping (GAHG). The algorithm aims to achieve both fairness in the group formation and to maximize the students’ skills within the formed groups. An experiment was performed with 48 students to demonstrate the ability of the approach. Experimental results indicate that our approach can optimally allocate students in an efficient way. Key-Words: Fairness in coalition; group formation; genetic algorithm; heterogeneous grouping.