Extended reality (XR) can be a useful tool in the battlefield, provided it can perform at least as well as current technology used by the warfighter. The Multi-Domain Operations (MDO) framework, in which many military domains must informationally coordinate, necessitates a move toward technologies capable of delivering vital communications while maintaining situation awareness (SA). In the present work, a novel XR technology (Microsoft HoloLens 2) is compared with a traditional technology (tablet). Prior to administering the study, participants were given structured training in the use of the XR system, as well as in military symbology, units, and scenarios. Thereafter, in the experimental portion of the study, participants separately used two technologies, HoloLens 2 and a tablet. Their task was to understand military scenarios, and performance was assessed for SA, workload as measured by the NASA-Task Load Index (NASA-TLX), and usability as measured by the System Usability Scale (SUS). Within the HoloLens conditions, we measured the impact of displaying units on maps using symbology only or symbology with 3D models. Notably, in contrast to previous studies, results showed SA levels were not significantly different between technologies, and that SA scores were significantly higher for individuals with high training performance. We also saw significant differences in usability, such that the tablet outperformed the HoloLens 2, and the tablet scored lower in terms of workload. On the HoloLens, symbology-only maps were outperformed by symbology and 3D models maps, but only for SA level 3. These findings support the idea that XR technology can be helped by sufficient training to perform alongside more traditional technologies, while identifying a need for design improvements targeting workload and usability before the technology is ready to support MDO efforts, and warfighter.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2020-2601 |
| Date | 01 January 2023 |
| Creators | Laxton, Betsy |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations, 2020- |
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