Abstract
In many situations, it remains critical for team members to develop strategies to effectively use the space and tools available to complete demanding tasks. However, despite the availability of sensors and analytics for instrumenting physical space, relatively little progress has been made in modelling the embodied dimensions of co-located teamwork. This paper explores an in-The-wild pilot study through which we explore a methodology to model embodied mobility teamwork strategies in the context of healthcare education. We developed the means for tracking, clustering and processing student-nurses' mobility data around a patient manikin. We illustrate the feasibility of our approach by discussing ways to make sense of these data to uncover meaningful trends, and the inherent challenges of applying physical space analytics in authentic settings.
Original language | English |
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Title of host publication | UMAP '17 Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization, 9-12 July 2017, Bratislava, Slovakia |
Place of Publication | New York |
Publisher | Association for Computing Machinery, Inc |
Pages | 308-312 |
Number of pages | 5 |
ISBN (Print) | 978-1-4503-4635-1 |
DOIs | |
Publication status | Published - 9 Jul 2017 |
Event | 25th International Conference on User Modeling, Adaptation and Personalization (UMAP 2017) - Bratislava, Slovakia Duration: 9 Jul 2017 → 12 Jul 2017 http://www.um.org/umap2017/ |
Conference
Conference | 25th International Conference on User Modeling, Adaptation and Personalization (UMAP 2017) |
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Country/Territory | Slovakia |
City | Bratislava |
Period | 9/07/17 → 12/07/17 |
Internet address |
Keywords
- Collaboration
- Computer vision
- Group modelling
- Physical analytics
- Proximity data
- Simulation-based learning
- Teamwork