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Human-Centred Teamwork Analytics

Collocated teamwork remains a critical part of many professions. The Human-Centred Teamwork Analytics project is using multimodal activity traces (e.g., location, movement, speech, actions) to assist the formative assessment and improvement of collocated teamwork among nursing students.

The Human-Centred Teamwork Analytics project has made embodied student teamwork ‘visible’ to the simulation ward through state of the art Learning Analytics and Generative AI. Salient features of a team’s interaction during a nursing simulation are captured and visualised in ways that are meaningful to both educators and students. The feedback design is co-designed with the stakeholders, is grounded in learning and teamwork theory, and generated automatically to assist team debriefing by the instructor immediately after an exercise.

The project funded by the Australian Research Council (DP210100060, 2021-24), was led by Monash University (PI: Dragan Gasevic), building on the extensive work with UTS Health Faculty led by Roberto Martinez-Maldonado when he was a CIC postdoctoral research fellow, who with Simon Buckingham Shum co-supervised two PhD projects by Vanessa Echeverria and Gloria Fernandez-Nieto. Here’s an introductory video we shot with our Health Faculty:

Learn more…

The main project website is TeamworkAnalytics.net where you will find details of the team, latest news and research publications reporting how and why we have developed this infrastructure, and how we study its effectiveness. Here’s a snapshot from the most recent research paper, evaluating this in action:

  • Echeverria, V., Zhao, L., Alfredo, R., Milesi, M. E., Jin, Y., Abel, S., Fan, J. X., Yan, L., Dix, S., Wotherspoon, R., Li, X., Jaggard, H. A., Osborne, A., Buckingham Shum, S., Gasevic, D. and Martinez-Maldonado, R. (2025), TeamVision: An AI-powered Learning Analytics System for Supporting Reflection in Team-based Healthcare Simulation. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery. https://doi.org/10.1145/3706598.3713395
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