Abstract
The present study was designed to empirically examine the effectiveness of adaptive training methods to enhance operators’ performance of unmanned aerial systems commonly used in search-and-rescue missions. In order to do so, a game-based (Stealth Adapt) test was developed to measure a player’s task-prioritization such flight path to search and rescue the targets. This simulated game took into account the player’s ability to quickly integrate disparate information about available targets, based on some gaming scenarios. These gaming scenarios included a variety of established rules of engagement, attending to four factors: 1) proximity to the nearest hostile force, 2) lethality or probability of attack of the nearest hostile force, 3) duration of the time stranded, and 4) survivability in the game. Results demonstrated a change in perceived workload as a result of repeated exposure to the software, and indicated that familiarity with particular programming interfaces may help predict performance in the Stealth Adapt task.