Charting the Development of Collaboration Skills Through Collaborative Learning Analytics Systems

Collaboration skills are fundamental to effective collaborative learning, career success, and responsible citizenship. Collaborative learning analytics (CLA) systems hold significant potential in helping students develop these skills by automatically collecting group interaction data, analyzing skill levels, and providing actionable feedback so students can reflect, practise, and improve. Previously, most collaborative feedback systems have focused on improving collaborative processes rather than serving as instructional systems for developing collaboration skills over time. To identify what is needed to navigate toward this new type of tool, our paper proposes an interdisciplinary framework that serves as a guiding compass for designing and evaluating such systems. Through an extensive literature review, we evaluate 15 selected systems through the lens of each element of this framework. We map out the current state of the field and identify four major gaps that need to be addressed to transition from systems that support collaboration to systems that support the development of collaboration skills. These gaps are unexplored collaboration skills, lack of validated indicators, limited modelling techniques, and pedagogical feedback design. Finally, we propose a set of corresponding research agendas to bridge these gaps, providing a forward-looking roadmap for designing effective and actionable CLA systems for collaboration skills development.

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Publication Details

Journal
Journal of Learning Analytics
Published
2025-03-17
DOI
https://doi.org/10.18608/jla.2025.8523
Citations
1
Primary Topic
Innovative Teaching and Learning Methods
Type
article
Field-Weighted Citation Impact
3.44
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article

Charting the Development of Collaboration Skills Through Collaborative Learning Analytics Systems

Xavier Ochôa, Xiaomeng Huang
1 citations
Journal of Learning Analytics
Innovative Teaching and Learning Methods
3.44
article

Charting the Development of Collaboration Skills Through Collaborative Learning Analytics Systems

Xavier Ochôa, Xiaomeng Huang
article en
1 citations

Abstract

Collaboration skills are fundamental to effective collaborative learning, career success, and responsible citizenship. Collaborative learning analytics (CLA) systems hold significant potential in helping students develop these skills by automatically collecting group interaction data, analyzing skill levels, and providing actionable feedback so students can reflect, practise, and improve. Previously, most collaborative feedback systems have focused on improving collaborative processes rather than serving as instructional systems for developing collaboration skills over time. To identify what is needed to navigate toward this new type of tool, our paper proposes an interdisciplinary framework that serves as a guiding compass for designing and evaluating such systems. Through an extensive literature review, we evaluate 15 selected systems through the lens of each element of this framework. We map out the current state of the field and identify four major gaps that need to be addressed to transition from systems that support collaboration to systems that support the development of collaboration skills. These gaps are unexplored collaboration skills, lack of validated indicators, limited modelling techniques, and pedagogical feedback design. Finally, we propose a set of corresponding research agendas to bridge these gaps, providing a forward-looking roadmap for designing effective and actionable CLA systems for collaboration skills development.

Journal of Learning AnalyticsVol. 12(1)
New York University (US)
Openalex Percentile: Top 11%
Innovative Teaching and Learning Methods
3.44
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