Journal Of Capital Development in Behavioural Sciences · ISSN 0000-0000

Collaborative Learning Measures using Collaboration Analytics: Applications, Limitations, and Caveats Review

Lamidi Babatunde AUDU

Lamidi Babatunde AUDU — Department of Educational Technology University: Saarland University, Germany
Vol. 11 (1) Year 2023 Published Mar 13, 2024 Pages 81-93 Access Open
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Abstract

Abstract

There is a widely held belief that social interaction among learners in groups enhances learning. However, for collaborative learning to be effective, it must meet certain requirements, for example, having appropriate goal structures and tasks that demand collective efforts to be solved. Collaboration analytics is a field of research that aims to measure collaborative learning or learning in groups by quantifying qualitative data. Collaboration analytics in research also provides a more reliable tool for handling massive amounts of data. However, for data to be reliable, there is a need for intercoder agreement. The endeavor to quantify qualitative data using collaboration analytics has proven to be useful, but with certain limitations and caveats.

Contributors

Authors

Lamidi Babatunde AUDU

Department of Educational Technology University: Saarland University, Germany
Corresponding author
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Citation

APA

AUDU, L. B. (2024). Collaborative Learning Measures using Collaboration Analytics: Applications, Limitations, and Caveats Review. Journal Of Capital Development in Behavioural Sciences, 11(1), 81-93.

MLA

AUDU, Lamidi Babatunde. "Collaborative Learning Measures using Collaboration Analytics: Applications, Limitations, and Caveats Review." Journal Of Capital Development in Behavioural Sciences, vol. 11, no. 1, 81-93. 2024

Chicago

Lamidi Babatunde AUDU. "Collaborative Learning Measures using Collaboration Analytics: Applications, Limitations, and Caveats Review." Journal Of Capital Development in Behavioural Sciences 11, no. 1 (2024): 81-93.
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