Framework Conceitual para Formação de Grupos de Alunos utilizando Trilhas de Aprendizagem em um Ambiente Virtual de Aprendizagem

Resumo

In this paper we propose a conceptual framework for groups formation of students in a virtual learning environment (VLE). We have developed and validated a conceptual framework for group recommendation for collaborative activities, using student characterization based on learning paths (LPs) in an VLE. The approach we following give emphasis to group formation applying K-Means algorithm, using three similarity metrics which are Euclidian, Manhattan and Cosine metrics.The framework validation was performed through the implementation of the M-Cluster tool. Real user interaction data with the tool is used in validation.