Maintenance Training based on an Adaptive Game-Based Environment using a Pedagogic Interpretation Engine (MAGPIE)
Small Business Information
Charles River Analytics Inc.
625 Mount Auburn Street, Cambridge, MA, 02138-4555
AbstractABSTRACT: Although Partial Task Trainers (PTTs) have been shown to have a cost savings of 60 percent over training on actual systems, they routinely cost the Government in manpower, maintenance, and upgrades, and are limited by static content that does not address differently skilled trainees. Game-based training can provide a powerful, personalized approach to addressing individual training needs, but without accessible development tools, game updates can remain costly. To harness the full power of game-based training for maintenance proficiency, we propose to develop Maintenance Training based on an Adaptive Game-Based Environment using a Pedagogic Interpretation Engine (MAGPIE). Based on our successful Phase I, we propose a full-scope Phase II development effort focused on four elements: (1) a suite of intuitive authoring tools that enable course designers to construct scenarios, performance metrics, and game configurations for training; (2) instruction tools that cognitively merge observation, tracking, and training tasks for instructors to manage training exercises; (3) a realistic and extensible game engine that adapts COTS products to provide immersive gameplay for trainees with realistic aircraft models that address maintenance training objectives; and (4) an integration framework that seamlessly merges authored training content with both the game engine and the instruction tool. BENEFIT: We will transition the MAGPIE technology to courses at Sheppard AFB, providing instructors with a C-130H and C-130J trainer that can augment their current classroom-based training mechanisms. MAGPIE will also benefit Government agencies that train personnel using computer-controlled immersive scenarios (e.g., air traffic controllers, emergency responders, medical teams) by pursuing licensing arrangements with producers of similar or existing training systems for those domains. Finally, we will target the multi-billion dollar computer game industry, and augment our own commercial product, AgentWorks.
* information listed above is at the time of submission.