Automatic Building of University Student Teams: an experience from English subject

One of the main goals for Higher Education is to educate students to work in teams. Such a skill not only improves their social behavior in the community, but also the ability for solving complex problems. Usually, the process of making teams is carried out by professor of the subject, who has to take into account several criteria (e.g. the presence of leader, heterogeneity of the team according the level of knowledge, sex, among others). When the subject has just few students, this task becomes easy. However, in the case of classes with a large number of students, this task becomes complex and there is no warranty about the accomplishment of the considered criteria. In that sense, the present work proposes a computational solution that automatizes the task of student teams building. Specifically, it was approached as a multi-objective combinatorial optimization problem, which was solved using a Pareto Dominance-based algorithm. In order to validate the proposal we performed several computational experiments involving real case studies from the English subject of three careers at the Technical State University of Quevedo. Results show that the proposed approach is able to build balanced teams according to the considered criteria.