Augmented Reality (AR) has emerged as a rapidly developing technology, capable of a wide scope of applications across a variety of domains. AR technologies allow for a virtual experience to be overlaid on top of a physical environment, creating a hybrid experience in which virtual objects become a part of the user's perceptual and physical environment. Rapid progression of the AR field requires that effective and validated methods of design evaluation be developed. Failure to consider the usability of AR applications during the design process will result in an increase in user errors and accidents, limiting user trust of the technology and undermining user perceptions of the technology, for both AR and Virtual Reality (VR) technologies (Nordrum, 2016). Through a robust and iterative process, a set of Design Heuristics for AR were developed for multidimensional augmented environments with the aim of advancing AR design methods for human factors, ergonomics, and user experience practitioners within the expanding AR community.

Teamwork has become one of the hallmarks of emergency crisis management (ECM). Success in managing emergency situations is highly dependent on teams working together to accomplish prioritized goals. Therefore, given the importance of teamwork, team cognition has been realized as an important component to address the emerging complexity, extreme workload, and uncertain conditions that can underlie emergency response. Many variables affect teams and their subsequent cognition. Understanding the effects of awareness, attention, temporality, common ground, team mental model development, and culture on team cognition provides insight into effective and efficient management of emergencies. As a research group, for more than a decade, we have studied team cognition within the context of ECM through the basis of simulations using the NeoCITIES platform. The purpose of this paper is to share our experiences using the NeoCITIES platform to conduct basic team cognitive research and share our visions for future research trajectories for the greater Human Factors community.

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The next phase of augmented reality (AR) technologies suggest that as both the hardware and software continue to improve, we can expect that AR will become more commonly used as a tool for a variety of applications in complex operational contexts (i.e. training, manufacturing, mission planning). As new applications are designed and developed within these contexts, there is a necessity to be able to measure the effectiveness of these systems and to understand their impact on human performance and workload, so that only the most appropriate designs are selected for use, growing the technology in usefulness, not novel hindrances. A unique opportunity presented by the Microsoft HoloLens platform, as an example of head-worn AR systems, is the ability to collect positional and movement data, which lends itself to the computation of behavioral (or steering) entropy data, which can be related to human workload and performance within the system environment. However, little reference exists to be able to verify the accuracy of tracking of the device with regards to the output data available for collection. Within this practitioner-oriented paper, we extend current entropy measurement theory typically used in control settings within a heads-up display type ‘controls' environment. Our findings indicate that in-situ measurements of entropy utilizing the onboard sensors within the AR platform are more accurate to those collected within a Motion Capture Facility. Extending this work, these measurements can be used as a correlate of performance.

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