A Genetic Algorithm Approach for Forming Heterogeneous Groups of Students

摘要

The heterogeneity of students' academic levels in the group affects various outcomes of student's learning skills. It also affects a number of aspects in developing software products for an undergraduate program in the major of computer science. Therefore, teachers need to construct appropriate groups of students in order to distribute different students among groups to share their knowledge and complete the computer software projects effectively. However, forming groups of students becomes more complex when the number of students is large and student's attributes are complicated. In this paper, we proposed an approach based on heterogeneity of students by using genetic algorithms to form student groups at a university. The proposed algorithm is called Genetic algorithm for heterogeneous grouping (GA_HeteGroup). The algorithm aims to achieve both fairness and equity in terms of learning performance and programming skills in the group formation by balancing different students in the formed groups. The A case study is conducted to this paper to demonstrate the ability of the algorithm. Experimental results indicate that our approach can optimally assign and distribute the whole of heterogeneous students in the effective way.