Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC) IITSEC 2020 Paper No. 20336 Page 1 of 13 Situational Awareness Methods in Virtual Reality Training: A Scoping Review Kaitlyn M. Ouverson, Melynda Hoover, Stephen B. Gilbert, Michael C. Dorneich, Eliot Winer Iowa State University Ames, Iowa, USA {kmo, mthoover, gilbert, dorneich, ewiner}@iastate.edu ABSTRACT In 2020, the US Military budget for Air Operations Training increased by $197.7m to accommodate additional virtual training, instructor pilots, and air support. These virtual trainers are essential for preparing warfighters for scenarios that are rare, dangerous, and complex. While virtual training has historically been conducted in costly and immobile “big box” simulators, they can now be deployed using consumer-grade immersive virtual reality (VR) head-mounted displays (HMDs). For example, Air Force maintenance airmen use VR HMDs to train on the C-130 due to savings of time and money over live training, without loss of training effectiveness. However, one challenge when using an HMD for training is giving the instructor complete awareness of what the learner is doing both in the virtual environment. Typically, instructors observe a learner’s progress in a simulation from a monitor that provides a window into the virtual environment. This window is missing affordances for interaction that make communicating with the learner difficult. The challenge of the instructor and learner’s different access to the virtual environment, and the resulting lack of situational awareness, can cause a disruption in communication and degrade learning outcomes. The authors propose that this could be mitigated using a number of techniques from existing research. This paper provides a scoping literature review to explore five potential solutions: asymmetric, symmetric, asynchronous, substitutional, and adaptive VR training systems. The authors evaluated each of these innovations in VR collaboration for its impact on 1) instructor-learner workspace awareness and 2) communication in VR simulations to guide industry and interservice training professionals. Results show that each of the current VR collaboration techniques has strengths and weaknesses, and understanding these trade-offs is crucial to derive the maximum benefit for a specific training task. Keywords: Virtual Reality, Training, Asymmetric Technology, Substitutional Reality, Communication ABOUT THE AUTHORS Kaitlyn M. Ouverson is a Ph.D. student at Iowa State University studying Human Computer Interaction. She is currently working on understanding and improving methods for co-located use of Virtual Reality using consumer- ready devices. Her previous research includes evaluating the impact of Intelligent Team Tutoring Systems on team and task performance, user experience research for websites, products, and data collection tools, and translating findings in game design for automation and interface design professionals. Melynda Hoover is a Ph.D. student in Human Computer Interaction at Iowa State University. She is currently researching adaptive Virtual Reality for training simulations. Her previous work includes studying augmented reality for manufacturing and assembly applications and user experience research for training and simulation design. Stephen B. Gilbert, Ph.D., is an associate director of the Virtual Reality Applications Center and director of the Human Computer Interaction graduate program as well as associate professor of Industrial and Manufacturing Systems Engineering at Iowa State University. His research focuses on technology to advance cognition, including interface design, intelligent tutoring systems, and cognitive engineering. Current projects include work with federal agencies and industry to improve the quality of remote collaboration software and to evaluate PTSD interventions through innovative use of virtual reality. Michael C. Dorneich, Ph.D., is an associate professor of Industrial and Manufacturing Systems Engineering at Iowa State University. His research interests focus on human factors of supporting decision making with adaptive