{"title":"Grouping Teammates Based on Complementary Degree and Social Network Analysis Using Genetic Algorithm","authors":"Huang-Ming Su, T. Shih, Yung-Hui Chen","doi":"10.1109/U-MEDIA.2014.40","DOIUrl":null,"url":null,"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.","PeriodicalId":174849,"journal":{"name":"2014 7th International Conference on Ubi-Media Computing and Workshops","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 7th International Conference on Ubi-Media Computing and Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/U-MEDIA.2014.40","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
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.