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. Copyright © 2017 Springer International Publishing AG.
| Original language | English |
|---|---|
| Title of host publication | Blended learning: New challenges and innovative practices: 10th International Conference, ICBL 2017, Hong Kong, China, June 27-29, 2017, proceedings |
| Editors | Simon K.S. CHEUNG, Lam-for KWOK, Will W.K. MA, Lap-Kei LEE, Harrison YANG |
| Place of Publication | Cham |
| Publisher | Springer |
| Pages | 284-294 |
| ISBN (Electronic) | 9783319593609 |
| ISBN (Print) | 9783319593593 |
| DOIs | |
| Publication status | Published - 2017 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 4 Quality Education
Keywords
- Collaborative learning
- Learning style analysis
- Clustering analysis
- Education data mining
- Grouping strategy
Fingerprint
Dive into the research topics of 'A study on grouping strategy of collaborative learning based on clustering algorithm'. Together they form a unique fingerprint.- APA
- Standard
- Harvard
- Vancouver
- Author
- BIBTEX
- RIS