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Evaluating collaborative learning by social network analysis with 2-tuple linguistic information
Abstract
The cooperative learning appeared in the globalization of education, it is a new teaching theory and strategy frequently used to study the new things and to solve the new problems by group cooperation. The introduction of cooperative learning to fundamental curriculum reform has been a main direction of various countries' education reforms and develops. In the education and the teaching, how appraises student's cooperation ability, especially the interpersonal skills is count for much, the school and the teacher should give the high value. In this paper, we investigate the multiple attribute decision making problems for social network analysis in the evaluation of collaborative learning research with 2-tuple linguistic information. We extended the TOPSIS model to solve the problems of social network analysis in the evaluation of collaborative learning research with 2-tuple linguistic information. According to the traditional ideas of TOPSIS, the optimal alternative(s) is determined by calculating the shortest distance from the 2-tuple linguistic positive ideal solution (TLPIS) and on the other side the farthest distance of the 2-tuple linguistic negative ideal solution (TLNIS). Finally, a numerical example for social network analysis in the evaluation of collaborative learning research with 2-tuple linguistic information is used to illustrate the applicability and effectiveness of the proposed model.
Paper Details
PaperID: 84877066713
Author's Name: Wu, H., Ying, S., Wang, Y.
Volume:
Issues:
Keywords: 2-tuple, Collaborative learning research, Social network analysis, TOPSIS
Year: 2013
Month: April
Pages: 2537-2542