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Characterising Individual-Level Collaborative Learning Behaviours Using Ordered Network Analysis and Wearable Sensors

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Advances in Quantitative Ethnography (ICQE 2023)

Abstract

Wearable positioning sensors are enabling unprecedented opportunities to model students’ procedural and social behaviours during collaborative learning tasks in physical learning spaces. Emerging work in this area has mainly focused on modelling group-level interactions from low-level x-y positioning data. Yet, little work has utilised such data to automatically identify individual-level differences among students working in co-located groups in terms of procedural and social aspects such as task prioritisation and collaboration dynamics, respectively. To address this gap, this study characterised key differences among 124 students’ procedural and social behaviours according to their perceived stress, collaboration, and task satisfaction during a complex group task using wearable positioning sensors and ordered networked analysis. The results revealed that students who demonstrated more collaborative behaviours were associated with lower stress and higher collaboration satisfaction. Interestingly, students who worked individually on the primary and secondary learning tasks reported lower and higher task satisfaction, respectively. These findings can deepen our understanding of students’ individual-level behaviours and experiences while learning in groups.

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Acknowledgements

This research was funded partially by the Australian Government through the Australian Research Council (project number DP210100060). Roberto Martinez-Maldonado’s research is partly funded by Jacobs Foundation.

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Correspondence to Lixiang Yan .

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The authors have declared no conflicts of interest.

Ethics Statement

Ethics approval was obtained from Monash University (Project ID: 28026).

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request. The data are not publicly available due to privacy or ethical restrictions.

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Yan, L. et al. (2023). Characterising Individual-Level Collaborative Learning Behaviours Using Ordered Network Analysis and Wearable Sensors. In: Arastoopour Irgens, G., Knight, S. (eds) Advances in Quantitative Ethnography. ICQE 2023. Communications in Computer and Information Science, vol 1895. Springer, Cham. https://doi.org/10.1007/978-3-031-47014-1_5

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  • DOI: https://doi.org/10.1007/978-3-031-47014-1_5

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