Abstract
Immersive technologies, such as augmented and virtual reality (AR/VR), are increasingly being utilized for training in various domains, especially the military. Although immersive technology’s potential for meeting specific training needs should be analyzed prior to implementation, an in-depth analysis is not always feasible. Therefore, military acquisition personnel often take an approach focused on logistical constraints when making decisions about acquiring new technology for training though no solution exists to guide these acquisition personnel through that selection process. The goal for this effort is to develop a software tool that will equip acquisition personnel with the ability to make evidence-based decisions about technologies for training prior to their acquisition. This support tool will help users make informed acquisition decision by inquiring about parameters (e.g. group size) and practical constraint (e.g. outdoor environment) considerations through various data extraction techniques. The ultimate goal is more efficient training as a result of guidance during the training technology acquisition process.
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Acknowledgements
This research was accomplished under Contract No N68335-19-C-0089. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of NAWCTSD or the US Government. The US Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation hereon. NAWCTSD Public Release 20-ORL043 Distribution Statement A – Approved for public release; distribution is unlimited.
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Abich, J., Sikorski, E. (2020). Technology for Training: Acquisition Recommender Support Tool. In: Stephanidis, C., Antona, M., Ntoa, S. (eds) HCI International 2020 – Late Breaking Posters. HCII 2020. Communications in Computer and Information Science, vol 1294. Springer, Cham. https://doi.org/10.1007/978-3-030-60703-6_32
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DOI: https://doi.org/10.1007/978-3-030-60703-6_32
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