Grouping teammates based on complementary degree and social network analysis using genetic algorithm

Huang Ming Su, Timothy K. Shih, Yung Hui Chen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

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.

Original languageEnglish
Title of host publicationProceedings - 2014 7th International Conference on Ubi-Media Computing and Workshops, U-MEDIA 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages59-64
Number of pages6
ISBN (Electronic)9781479942664
DOIs
StatePublished - 3 Oct 2014
Event2014 7th International Conference on Ubi-Media Computing and Workshops, U-MEDIA 2014 - Ulaanbaatar, Mongolia
Duration: 12 Jul 201414 Jul 2014

Publication series

NameProceedings - 2014 7th International Conference on Ubi-Media Computing and Workshops, U-MEDIA 2014

Conference

Conference2014 7th International Conference on Ubi-Media Computing and Workshops, U-MEDIA 2014
Country/TerritoryMongolia
CityUlaanbaatar
Period12/07/1414/07/14

Keywords

  • cooperative learning
  • genetic algorithm
  • grouping
  • social network

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