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Abstract
Collaborative learning has been widely used to foster students' communication and joint knowledge construction. However, the classification of learners into well-structured groups is one of the most challenging tasks in the field. The aim of this study is to propose a novel method to form intra-heterogeneous and inter-homogeneous groups based on relevant student characteristics. Such a method allows for the consideration of multiple student characteristics and can handle both numerical and categorical characteristic types simultaneously. It assumes that the teacher provides an order of importance of the characteristics, then it solves the grouping problem as a lexicographic optimization problem in the given order. We formulate the problem in mixed integer linear programming (MILP) terms and solve it to optimality. A pilot experiment was conducted with 29 college freshmen considering three general characteristics (i.e., 13 specific features) including knowledge level, demographic information, and motivation. Results of such an experiment demonstrate the validity and computational feasibility of the algorithmic approach. Large-scale studies are needed to assess the impact of the proposed grouping method on students' learning experience and academic achievement.
Original language | English |
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Title of host publication | LAK 2021 Conference Proceedings - The Impact we Make : The Contributions of Learning Analytics to Learning, 11th International Conference on Learning Analytics and Knowledge |
Publisher | Association for Computing Machinery |
Publication date | 12. Apr 2021 |
Pages | 546-552 |
ISBN (Electronic) | 9781450389358 |
DOIs | |
Publication status | Published - 12. Apr 2021 |
Event | 11th International Conference on Learning Analytics and Knowledge: The Impact we Make: The Contributions of Learning Analytics to Learning, LAK 2021 - Virtual, Online, United States Duration: 12. Apr 2021 → 16. Apr 2021 |
Conference
Conference | 11th International Conference on Learning Analytics and Knowledge: The Impact we Make: The Contributions of Learning Analytics to Learning, LAK 2021 |
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Country/Territory | United States |
City | Virtual, Online |
Period | 12/04/2021 → 16/04/2021 |
Keywords
- Computer-supported collaborative learning (CSCL)
- Group formation
- Mixed integer linear programming (MILP)
- Student-project assignment
Fingerprint
Dive into the research topics of 'An exact algorithm for group formation to promote collaborative learning'. Together they form a unique fingerprint.Related activities
- 1 Conference presentations
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An exact algorithm for group formation to promote collaborative learning
Sun, Z. (Speaker) & Chiarandini, M. (Co-author)
2021Activity: Talks and presentations › Conference presentations
Related projects
- 1 Active
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Algorithm-based Group Formation
Sun, Z. (PI) & Chiarandini, M. (Co-PI)
01/09/2017 → …
Project: Research