With an objective to provide “a data strategy for measuring the longitudinal impact of synthetic, semi-synthetic, and live training experiences on individual and team competency development,” STEEL-R brings together a variety of standards-based capabilities from the world of synthetic scenario design with the core standards-based capabilities of ADL’s Total Learning Architecture (TLA).

Within a research context, there is a need for large and relevant activity data sets to test hypotheses regarding competency assertion. But where do these data sets come from?