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A Study on Grouping Strategy of Collaborative Learning Based on Clustering Algorithm

  • Qingtang Liu
  • Shen BaEmail author
  • Jingxiu HuangEmail author
  • Linjing Wu
  • Chuanyuan Lao
Conference paper
  • 2.3k Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10309)

Abstract

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.

Keywords

Collaborative learning Learning style analysis Clustering analysis Education data mining Grouping strategy 

Notes

Acknowledgment

This research is supported by the National High-tech Research and Development Program (No. 2015AA015408) and the Fundamental Research Funds for the Central Universities (No. CCNU16A05023).

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.School of Educational Information TechnologyCentral China Normal UniversityWuhanChina

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