Stealth Optimized, Adaptive Assessments for Multistage UAS Operator Selection (Stealth Adapt)

Unmanned Aerial System (UAS) operation represents a stressful, cognitively challenging domain where operators are routinely subjected to both occupational and combat stressors and performance failures can have catastrophic effects. Effective performance in such conditions has many dimensions, including technical proficiency, probability of catastrophic failures, mission productivity, resistance to stress symptomology, teamwork, and long-term work engagement. Effective selection methods for UAS operators should accurately, efficiently, and holistically predict these key outcomes. The focus of the proposed Phase II effort is to continue the development of a customized trilogy of adaptive assessment content, for which prototype versions were developed within Phase I. This includes components measuring executive level cognition, personality, and biographical history. These assessments are assembled within a novel content delivery and protection framework that incorporates adaptive content sequencing and generation algorithms, a configurable multistage architecture, and stealth scoring optimization. The format of the assessments ranges from computer administered questions to adaptive, simulation-based assessment content embedded within a realistic drone search and rescue game environment. The Phase II include comprehensive assessment content and software products for integration within existing military assessment frameworks, platform-specific systems for unmanned aviation, and private sector transition clients.