A study on grouping strategy of collaborative learning based on clustering algorithm

As educational informatization develops continuously, blended learning has become the focus of increasing amount of research works. Among these studies, researchers indicate that collaborative learning, as an important teaching strategy, is of great effectiveness in promoting students’ learning performance either in E-learning or classroom teaching. However, due to the fact that different students may have different learning styles, it is crucial for teachers to take this factor into consideration. Therefore, to enhance the validity of grouping in collaborative learning, this paper proposes a grouping strategy based on the analysis results of students’ learning styles using K-Means and hierarchical clustering. Results of clustering analysis can provide a valuable reference no matter for homogeneous grouping or heterogeneous grouping. Copyright © 2017 Springer International Publishing AG.