Evaluating learning style-based grouping strategies in real-world collaborative learning environment

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Collaborative learning is defined as situations where multiple learners participate in solving common problems. Collaborative learning provides a way of building knowledge through activities of collaboration with others. Group work is a representative form of collaborative learning and has been used in higher education. In group work, however, one of the widely discussed issues is group composition. Students have different attributes including learning styles, background knowledges, gender, and so on. Typical group formations are homogeneous and heterogeneous compositions. Numerous work addressed the problem and evaluated how learning outcome varies between different group formations both in online and physical environments. In this study, we focus on the group formation for real-world collaboration. We introduce different types of grouping into a class of a theme-based course and discuss the effects of different learning styles in collaborative learning environment. Students are characterized according to Kolb’s learning style inventory and then grouped by homogeneous, heterogeneous, and random strategies. We investigate how intra-group interactions varies with different types of composition; we monitor the activity levels of every group and have students peer-review each other for quantitative evaluation of contributions. We find typical patterns of activities and contributions, and discuss their association to grouping strategies.

Original languageEnglish
Title of host publicationDistributed, Ambient and Pervasive Interactions
Subtitle of host publicationTechnologies and Contexts - 6th International Conference, DAPI 2018, Held as Part of HCI International 2018, Proceedings
EditorsShin’ichi Konomi, Norbert Streitz
PublisherSpringer Verlag
Pages227-239
Number of pages13
ISBN (Print)9783319911304
DOIs
Publication statusPublished - Jan 1 2018
Event6th International Conference on Distributed, Ambient and Pervasive Interactions, DAPI 2018 Held as Part of HCI International 2018 - Las Vegas, United States
Duration: Jul 15 2018Jul 20 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10922 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other6th International Conference on Distributed, Ambient and Pervasive Interactions, DAPI 2018 Held as Part of HCI International 2018
CountryUnited States
CityLas Vegas
Period7/15/187/20/18

Fingerprint

Learning Styles
Collaborative Learning
Collaborative Environments
Learning Environment
Grouping
Students
Chemical analysis
Education
Association reactions
Vary
Peer Review
Strategy
Quantitative Evaluation
Higher Education
Monitor
Attribute

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Taniguchi, Y., Gao, Y., Kentaro, K., & Konomi, S. (2018). Evaluating learning style-based grouping strategies in real-world collaborative learning environment. In S. Konomi, & N. Streitz (Eds.), Distributed, Ambient and Pervasive Interactions: Technologies and Contexts - 6th International Conference, DAPI 2018, Held as Part of HCI International 2018, Proceedings (pp. 227-239). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10922 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-91131-1_18

Evaluating learning style-based grouping strategies in real-world collaborative learning environment. / Taniguchi, Yuta; Gao, Yiduo; Kentaro, Kojima; Konomi, Shinichi.

Distributed, Ambient and Pervasive Interactions: Technologies and Contexts - 6th International Conference, DAPI 2018, Held as Part of HCI International 2018, Proceedings. ed. / Shin’ichi Konomi; Norbert Streitz. Springer Verlag, 2018. p. 227-239 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10922 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Taniguchi, Y, Gao, Y, Kentaro, K & Konomi, S 2018, Evaluating learning style-based grouping strategies in real-world collaborative learning environment. in S Konomi & N Streitz (eds), Distributed, Ambient and Pervasive Interactions: Technologies and Contexts - 6th International Conference, DAPI 2018, Held as Part of HCI International 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10922 LNCS, Springer Verlag, pp. 227-239, 6th International Conference on Distributed, Ambient and Pervasive Interactions, DAPI 2018 Held as Part of HCI International 2018, Las Vegas, United States, 7/15/18. https://doi.org/10.1007/978-3-319-91131-1_18
Taniguchi Y, Gao Y, Kentaro K, Konomi S. Evaluating learning style-based grouping strategies in real-world collaborative learning environment. In Konomi S, Streitz N, editors, Distributed, Ambient and Pervasive Interactions: Technologies and Contexts - 6th International Conference, DAPI 2018, Held as Part of HCI International 2018, Proceedings. Springer Verlag. 2018. p. 227-239. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-91131-1_18
Taniguchi, Yuta ; Gao, Yiduo ; Kentaro, Kojima ; Konomi, Shinichi. / Evaluating learning style-based grouping strategies in real-world collaborative learning environment. Distributed, Ambient and Pervasive Interactions: Technologies and Contexts - 6th International Conference, DAPI 2018, Held as Part of HCI International 2018, Proceedings. editor / Shin’ichi Konomi ; Norbert Streitz. Springer Verlag, 2018. pp. 227-239 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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