DocumentCode :
263410
Title :
Grouping Teammates Based on Complementary Degree and Social Network Analysis Using Genetic Algorithm
Author :
Huang Ming Su ; Shih, Timothy K. ; Yung Hui Chen
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Central Univ., Jhongli, Taiwan
fYear :
2014
fDate :
12-14 July 2014
Firstpage :
59
Lastpage :
64
Abstract :
In the past year, Cooperative Learning has become one of the most important teaching strategies. Helping learners group appropriately is now becoming more and more important. To solve the problem, a lot of methods have been proposed. In this paper, we employ a novel approach that considers the complementary degree of learner´s learning state and social networks to enhance interaction and teamwork between learners. Moreover, this paper using genetic algorithm (GA) to generate better grouping results. By recording the learning statuses of learners, we can adjust grouping result from each assignment dynamically. Results show that the proposed approach can optimize the grouping well.
Keywords :
computer aided instruction; genetic algorithms; groupware; team working; GA; complementary degree; cooperative learning; genetic algorithm; heterogeneous grouping; social network analysis; teaching strategies; teamwork; Genetic algorithms; Genetics; Optimization; Social network services; Sociology; Statistics; Wheels; cooperative learning; genetic algorithm; grouping; social network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Ubi-Media Computing and Workshops (UMEDIA), 2014 7th International Conference on
Conference_Location :
Ulaanbaatar
Print_ISBN :
978-1-4799-4267-1
Type :
conf
DOI :
10.1109/U-MEDIA.2014.40
Filename :
6916326
Link To Document :
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