Estratégias para formação de equipes homogêneas e heterogêneas a partir de algoritmos de análise de agrupamentos

Abstract

In academia, teachers often adopt different approaches to promote learning beyond simple content oral exposure in the classroom. A very common approach in all levels of education is to conduct academic activities in teams, where students are divided into groups according to some criteria pre-established by the teacher and each team is responsible for performing its respective task. However, the process of forming teams randomly or from affinities between students does not always favors learning process. In this context, this work presents some strategies based on the use of cluster analysis algorithms, which allow the teacher to guide the process of team building. Results demonstrate the effectiveness of the proposed strategies in both the formation of homogeneous teams as heterogeneous ones allowing the exchange of knowledge and encouraging mutual learning among team members.

Index Terms - Teaming, homogeneity and heterogeneity in teams, mining algorithms educational data, cluster analysis.