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Research has identified applications of handheld-based VR, which utilizes handheld displays or mobile devices, for developing systems that involve users in mixed reality (MR) without the need for head-worn displays (HWDs). Such systems can potentially accommodate large groups of users participating in MR. However, we lack an understanding of how group sizes and interaction methods affect the user experience. In this paper, we aim to advance our understanding of handheld-based MR in the context of multiplayer, co-located games. We conducted a study (N = 38) to understand how user experiences vary by group size (2, 4, and 8) and interaction method (proximity-based or pointing-based). For our experiment, we implemented a multiuser experience for up to ten users. We found that proximity-based interaction that encouraged dynamic movement positively affected social presence and physical/temporal workload. In bigger group settings, participants felt less challenged and less positive. Individuals had varying preferences for group size and interaction type. The findings of the study will advance our understanding of the design space for handheld-based MR in terms of group sizes and interaction schemes. To make our contributions explicit, we conclude our paper with design implications that can inform user experience design in handheld-based mixed reality contexts.
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This content will become publicly available on April 25, 2026
A design toolkit for task support with mixed reality and artificial intelligence
Efficient performance and acquisition of physical skills, from sports techniques to surgical procedures, require instruction and feedback. In the absence of a human expert, Mixed Reality Intelligent Task Support (MixITS) can offer a promising alternative. These systems integrate Artificial Intelligence (AI) and Mixed Reality (MR) to provide realtime feedback and instruction as users practice and learn skills using physical tools and objects. However, designing MixITS systems presents challenges beyond engineering complexities. The complex interactions between users, AI, MR interfaces, and the physical environment create unique design obstacles. To address these challenges, we present MixITS-Kit—an interaction design toolkit derived from our analysis of MixITS prototypes developed by eight student teams during a 10-week-long graduate course. Our toolkit comprises design considerations, design patterns, and an interaction canvas. Our evaluation suggests that the toolkit can serve as a valuable resource for novice practitioners designing MixITS systems and researchers developing new tools for human-AI interaction design.
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- Award ID(s):
- 2240133
- PAR ID:
- 10617345
- Publisher / Repository:
- Frontiers in Virtual Reality
- Date Published:
- Journal Name:
- Frontiers in Virtual Reality
- Volume:
- 6
- ISSN:
- 2673-4192
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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