Abstract
Mixed Reality (MR) collaboration enables users to work together in shared immersive environments, yet understanding how user roles naturally emerge and influence interaction preferences remains an open challenge. In this paper, weproposeacomprehensive Role Interpretation Framework based on three core interpersonal dimensions—Dominance, Sociability, and Task Orientation—to systematically capture and explain user roles in MR collaboration. We validate this framework through a two-stage formative study involving two representative scenarios: a hierarchical Expert– Trainee assembly task and a non-hierarchical Co-Creation planning task. Through self-reflective analysisandparticipatoryco-design workshops, we identify seven distinct collaborative roles and map their associated interaction preferences. Finally, we proposed three key recommendations that address role hierarchies, dynamic correspondences, and collaboration modes. This research provides asystematicframeworkforunderstandingmulti-user roles in MRcollaboration.
Keywords
Mixed Reality Collaboration; Multi-Role Collaboration; User Preferences; User Study
DOI
https://doi.org/10.21606/iasdr.2025.704
Citation
Yan, F., Yan, S., Dai, W., Zhao, L.,and Liu, Z.(2025) Exploring and Co-Designing Typical Collaborative Scenarios in Mixed Reality: A Role-Based Approach, in Chang, C.-Y., and Hsu, Y. (eds.), IASDR 2025: Design Next, 02-05 December, Taiwan. https://doi.org/10.21606/iasdr.2025.704
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Conference Track
Track 6 - Co-creation
Exploring and Co-Designing Typical Collaborative Scenarios in Mixed Reality: A Role-Based Approach
Mixed Reality (MR) collaboration enables users to work together in shared immersive environments, yet understanding how user roles naturally emerge and influence interaction preferences remains an open challenge. In this paper, weproposeacomprehensive Role Interpretation Framework based on three core interpersonal dimensions—Dominance, Sociability, and Task Orientation—to systematically capture and explain user roles in MR collaboration. We validate this framework through a two-stage formative study involving two representative scenarios: a hierarchical Expert– Trainee assembly task and a non-hierarchical Co-Creation planning task. Through self-reflective analysisandparticipatoryco-design workshops, we identify seven distinct collaborative roles and map their associated interaction preferences. Finally, we proposed three key recommendations that address role hierarchies, dynamic correspondences, and collaboration modes. This research provides asystematicframeworkforunderstandingmulti-user roles in MRcollaboration.