A Dynamic Group Composition Method to Refine Collaborative Learning Group Formation.
作者： Zhilin Zheng
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摘要: Group formation strategies have the goal of providing participating students with good initial conditions for collaborative learning. Continuing existing methods to set up make peer interaction more likely happen, we propose a method dynamically recomposing learning groups based on intra-group iteration analysis optimize group iteratively.
参考文章(7)
Sabine Graf, Rahel Bekele, Forming Heterogeneous Groups for Intelligent Collaborative Learning Systems with Ant Colony Optimization Intelligent Tutoring Systems. pp. 217- 226 ,(2006) , 10.1007/11774303_22
Julián Moreno, Demetrio A. Ovalle, Rosa M. Vicari, A genetic algorithm approach for group formation in collaborative learning considering multiple student characteristics Computer Education. ,vol. 58, pp. 560- 569 ,(2012) , 10.1016/J.COMPEDU.2011.09.011
Yen-Ting Lin, Yueh-Min Huang, Shu-Chen Cheng, An automatic group composition system for composing collaborative learning groups using enhanced particle swarm optimization Computer Education. ,vol. 55, pp. 1483- 1493 ,(2010) , 10.1016/J.COMPEDU.2010.06.014
Philip C. Abrami, Bette Chambers, Research on Cooperative Learning and Achievement: Comments on Slavin Contemporary Educational Psychology. ,vol. 21, pp. 70- 79 ,(1996) , 10.1006/CEPS.1996.0005
Yiping Lou, Philip C. Abrami, John C. Spence, Catherine Poulsen, Bette Chambers, Sylvia d’Apollonia, Within-Class Grouping: A Meta-Analysis Review of Educational Research. ,vol. 66, pp. 423- 458 ,(1996) , 10.3102/00346543066004423
D. Perera, J. Kay, I. Koprinska, K. Yacef, O.R. Zaiane, Clustering and Sequential Pattern Mining of Online Collaborative Learning Data IEEE Transactions on Knowledge and Data Engineering. ,vol. 21, pp. 759- 772 ,(2009) , 10.1109/TKDE.2008.138
Ahmed Kharrufa, Ammar Al-Qaraghuli, Ammar Al-Qaraghuli, Kalina Yacef, Judy Kay, Roberto Martinez Maldonado, Analysing frequent sequential patterns of collaborative learning activity around an interactive tabletop educational data mining. pp. 111- 120 ,(2010)