Michael Nebeling (University of Michigan Ann Arbor, Ann Arbor, MI, USA)Maximilian Speicher (University of Michigan Ann Arbor, Ann Arbor, MI, USA)Xizi Wang (University of Michigan Ann Arbor, Ann Arbor, MI, USA)Shwetha Rajaram (University of Michigan Ann Arbor, Ann Arbor, MI, USA)Brian D. Hall (University of Michigan Ann Arbor, Ann Arbor, MI, USA)Zijian Xie (University of Michigan Ann Arbor, Ann Arbor, MI, USA)Alexander R. E. Raistrick (University of Michigan Ann Arbor, Ann Arbor, MI, USA)Michelle Aebersold (University of Michigan Ann Arbor, Ann Arbor, MI, USA)Edward G. Happ (University of Michigan Ann Arbor, Ann Arbor, MI, USA)Jiayin Wang (University of Michigan Ann Arbor, Ann Arbor, MI, USA)Yanan Sun (University of Michigan Ann Arbor, Ann Arbor, MI, USA)Lotus Zhang (University of Michigan Ann Arbor, Ann Arbor, MI, USA)Leah E. Ramsier (University of Michigan Ann Arbor, Ann Arbor, MI, USA)Rhea Kulkarni (University of Michigan Ann Arbor, Ann Arbor, MI, USA)
Significant tool support exists for the development of mixed reality (MR) applications; however, there is a lack of tools for analyzing MR experiences. We elicit requirements for future tools through interviews with 8 university research, instructional, and media teams using AR/VR in a variety of domains. While we find a common need for capturing how users perform tasks in MR, the primary differences were in terms of heuristics and metrics relevant to each project. Particularly in the early project stages, teams were uncertain about what data should, and even could, be collected with MR technologies. We designed the Mixed Reality Analytics Toolkit (MRAT) to instrument MR apps via visual editors without programming and enable rapid data collection and filtering for visualizations of MR user sessions. With MRAT, we contribute flexible interaction tracking and task definition concepts, an extensible set of heuristic techniques and metrics to measure task success, and visual inspection tools with in-situ visualizations in MR. Focusing on a multi-user, cross-device MR crisis simulation and triage training app as a case study, we then show the benefits of using MRAT, not only for user testing of MR apps, but also performance tuning throughout the design process.