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Conceptualizing Collaborative Team Learning in XR for Medical Education and Training

  • Chris Hartman,
  • Inki Kim,
  • Jeeheon Ryu

摘要

Rapid advancement of extended reality (XR) poses new challenges in the design and implementation of technologies, methods, and curriculums for medical training and education. Particularly, a paucity of research lies in XR-based learning approach to a group of learners: How can we ensure that collaborative team experiences in simulation will transfer to actual patient care? In this regard, we aim to conceptualize new challenges of team learning in XR for next-generation medical education. Contrary to part-task simulation, teamwork involves complex group dynamics for aggregated performance and thus a referent world-model essential for building simulation is not simple to derive. Imagine, for example, the many possible ways that a group of physicians and nurses may collaborate to treat a severely asthmatic patient in diverse clinical settings. To this end, we adopted the abstraction hierarchy to conceptualize an array of issues related to complex team interactions in XR-based professional education and training. As results of this representation, we identified the complex means-end relationships and couplings that exist among goals, functional interactions, and technological elements that altogether allow for team collaboration in XR. Discussions focused on key challenges and frictions within this web of interdependence.