Abstract

ABSTRACT Background Roles are the socio‐cognitive interaction patterns in social learning. Analyzing emergent roles provides insights into how students naturally participate and contribute knowledge in productive collaborative argumentation‐based learning (CABLE). However, previous studies lack a comprehensive and in‐depth understanding of the emergent roles in CABLE. In addition, the relationship between the emergent roles and the CABLE performance of groups and individuals needs to be further explored. Objectives This study aims to identify emergent roles in CABLE and explore the relationship between the dynamic fluctuation of emergent roles and learning performance from both individual and group perspectives. Methods To fill this gap, a collaborative argumentation discussion activity was conducted among 33 undergraduate students. The study analyzed the fine‐grained collaborative discourse moves based on the community of inquiry (CoI) framework. Then, the study identified emergent roles and quantified the dynamic fluctuation of emergent roles through sequence clustering and entropy analysis. Finally, the relationship between the emergent roles and the CABLE performance of groups and individuals was explored. Results and Conclusions The findings revealed that students emerged as Discussion facilitators, Viewpoint contributors, and Knowledge integrators during CABLE. Students with high argumentation skills had significantly higher role entropy values than students with low argumentation skills, and they flexibly regulated and transitioned their emergent roles. Furthermore, the higher the dynamic fluctuation of group emergent roles, the better the group learning performance tended to be. Based on the findings, the study proposed implications for instructional design and future research directions to optimize students' CABLE.

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Year
2025
Type
article
Volume
42
Issue
1
Citations
0
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Guoqing Lu, Yubei Chang, Xiaojuan Li et al. (2025). Unveiling the Relationship Between Undergraduate Students' Emergent Roles and Learning Performance in Collaborative Argumentation‐Based Learning: Insights From Sequence Clustering and Entropy Analysis. Journal of Computer Assisted Learning , 42 (1) . https://doi.org/10.1002/jcal.70173

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DOI
10.1002/jcal.70173