A conceptual model of combat marksmanship

Marksmanship tests are often determined by inherited standards or individual subject-matter experts rather than via a consistent and repeatable framework based on firearms engagements. Better process development in evaluations and better outcome modeling will optimize performance among military and law enforcement, thereby producing greater safety and effectiveness in field performance. Simulation experiments depicted the operational advantage provided by different night vision goggles using either a cognitive experimental approach, a simple Monte Carlo simulation or multiple Monte Carlo simulations integrated into a computation modeling approach. Whereas the cognitive experimental approach could only quantify a combat advantage in terms of reaction times, computational modeling provided a more practical interpretation while fully accounting for data granularity. The combat advantage could be described as a 40% increased likelihood to win in combat rather than a one second advantage. We provide a process-oriented conceptual approach to identify the sequence involved during firearms use. Eight common behavioral and decision nodes are situated with feedback loops that return, where applicable, to prior steps when addressing any errors in the marksmanship process. With this information, military or law enforcement personnel can structure their dialogue around the most important tasks to incorporate when creating a marksmanship evaluation or training program.