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 language | English |
|---|---|
| Title of host publication | Distributed, Ambient and Pervasive Interactions |
| Subtitle of host publication | Technologies and Contexts - 6th International Conference, DAPI 2018, Held as Part of HCI International 2018, Proceedings |
| Editors | Shin’ichi Konomi, Norbert Streitz |
| Publisher | Springer Verlag |
| Pages | 227-239 |
| Number of pages | 13 |
| ISBN (Print) | 9783319911304 |
| DOIs | |
| Publication status | Published - Jan 1 2018 |
| Event | 6th International Conference on Distributed, Ambient and Pervasive Interactions, DAPI 2018 Held as Part of HCI International 2018 - Las Vegas, United States Duration: Jul 15 2018 → Jul 20 2018 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 10922 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | 6th International Conference on Distributed, Ambient and Pervasive Interactions, DAPI 2018 Held as Part of HCI International 2018 |
|---|---|
| Country | United States |
| City | Las Vegas |
| Period | 7/15/18 → 7/20/18 |
Fingerprint
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)
Cite this
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 proceeding › Conference contribution
}
TY - GEN
T1 - Evaluating learning style-based grouping strategies in real-world collaborative learning environment
AU - Taniguchi, Yuta
AU - Gao, Yiduo
AU - Kentaro, Kojima
AU - Konomi, Shinichi
PY - 2018/1/1
Y1 - 2018/1/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85050552959&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85050552959&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-91131-1_18
DO - 10.1007/978-3-319-91131-1_18
M3 - Conference contribution
AN - SCOPUS:85050552959
SN - 9783319911304
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 227
EP - 239
BT - Distributed, Ambient and Pervasive Interactions
A2 - Konomi, Shin’ichi
A2 - Streitz, Norbert
PB - Springer Verlag
ER -