Scenario Engineering for Assessment of Multi-participant Adaptive Training Environment

Large Scale Training exercises such as the Fleet Synthetic Training – Joint (FST-J) demand incredible resources and effective planning. Prioritization of training events cannot guarantee that every training objective for every trainee can be met, particularly in environments where participants are disparately skilled. A new solution is needed to manage the training experiences of all participants. Aptima and the University of Oklahoma (OU) propose to develop Scenario Engineering for Assessment of Multi-participant Adaptive Training Environment (SEAMATE). SEAMATE is a novel approach to training scenario engineering that marries proven technology with established performance measurement theory to provide a seamless learning environment for all participants, despite disparities in skill level or experience. The Aptima/OU Team will leverage Item Response Theory to identify the item equivalent of a scenario experience. These experiences will populate a matrix, from which appropriate experiences can be drawn at the right level of difficulty to meet individual training needs. SEAMATE will expand upon Aptima’s PRESTO and A-Measure technologies to manage the presentation of scenario events, based on pre-test and real-time assessments of performance, tailored to individual training needs to meet training objectives based on pre-test and real-time assessments of performance.