Testing individual and group markers of collaboration in a team-based learning classroom

Journal Article (2025)
Author(s)

Y. H.Victoria Chua (Nanyang Technological University)

Justin Dauwels (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Preman Rajalingam (Mohammed Bin Rashid University of Medicine and Health Sciences)

Chew Lee Teo (National Institute of Education)

Suzy J. Styles (Nanyang Technological University)

Research Group
Signal Processing Systems
DOI related publication
https://doi.org/10.1016/j.learninstruc.2025.102215 Final published version
More Info
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Publication Year
2025
Language
English
Research Group
Signal Processing Systems
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository as part of the Taverne amendment. More information about this copyright law amendment can be found at https://www.openaccess.nl. Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Journal title
Learning and Instruction
Volume number
100
Article number
102215
Downloads counter
98
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Abstract

Background: Intra-group discussions during actual TBL sessions play a huge role in knowledge consolidation and learning but are often understudied. Aims: Using a pre-registered study framework, we examined if participation equity (H1), reciprocal interaction (H2), information density (H3), mutual understanding (H4), and emotional rapport (H5) affected how much students learn from their intra-group team-based learning discussions and how they rated their team's discussions. Sample: Participants were 165 undergraduate students assigned to 28 teams. Methods: Using linguistic, conversational, and socio-affective features extracted from recordings of Year 1 and 2 medical students engaging in team-based learning, each construct was conceptualised at the level of the group and the individual. We used linear mixed-effects models and competing models approach to establish which of our metrics best account for the observed variance in individual learning gains and perceived collaboration quality. The analysis plan was preregistered, including correction for multiple comparisons. Results: None of our individual-level or group-level metrics significantly predicted individual learning gains. One of the group-level metrics significantly predicted perceived collaboration quality: reciprocal interaction. Our exploratory analysis found that individual baseline score of the best performer in the team positively predicted individual learning gains for others in their team, regardless of other interaction metrics. Conclusion: While students perceived the highest collaboration quality when turn-taking in their team was evenly distributed, the strongest predicter of learning gains for a student was the knowledge level of their top-scoring team-mate. This finding has implications for classroom equity, group formation and activity planning.

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