Military and commercial simulation systems are often used in team training, but they are not training systems in a formal sense. Simulators present rich practice opportunities, but generally do not ensure that these are administered in an instructionally efficient manner. We describe a POMDP model that selects, from a large library, the training scenario that will most efficiently advance teams towards expertise given its performance on its previous scenario. Two experiments demonstrate that this model-driven instructional strategy reliably increases team performance on far transfer tasks, relative to a control strategy, hierarchical part task training. We speculate on the cause of this effect and propose research to explore and exploit these effects in military training. |