Advances in recent years have afforded Soldiers the ability to interact with exponentially greater volumes of emerging technologies, regardless of domain or work role. In many cases, the very manner and location in which a Soldier performs their tasking has drastically shifted as technology allows for work to be increasingly asymmetrical and distributed. The impact of technology will only continue to accelerate in the Future Operating Environment (FOE), as Soldiers are continually teamed with increasingly sophisticated and evolving technologies. While technology and new ways of conducting missions afford the Army with new opportunities to obtain success, it also presents a critical challenge as the rate of technological evolution outpaces the Army’s current ability to provide technology-specific training in a timely manner. To address this problem, there is an ever growing need to be able to recruit, select, and train individuals with an aptitude for technological fluency – the ability of Soldiers and units to use and rapidly adapt new intelligent technologies without the need for formal training. Such a model does not currently exist, however, so there is first a research need for building understanding of what enables an individual to be naturally gifted with new technologies.
In this paper we discuss how a competency model for technological fluency can be leveraged to train Soldiers. The preliminary work consists of two main subcomponents: (1) identification of the necessary knowledge, skills, abilities (KSAOs), and other attributes to be technologically fluent; and (2) developing an ontology for technology that supports mapping those KSAOs across the wide assortment of technologies that the Soldier of both today and the FOE employ. We discuss next steps for research to understand how/if Soldiers are currently being trained in the necessary competencies, and where training can be adapted to help Soldiers become more technologically fluent.
Keywords
COMPETENCY BASED TRAINING;PERSONALIZED TRAINING;TECHNOLOGY
Additional Keywords