Developing Authoring Tools for Skills Models that Enable Adaptive Game-Based Maintenance Training
Presented at the Interservice/Industry Training, Simulation & Education Conferece (I/ITSEC), Las Vegas, NV (December 2015)
While game-based maintenance training provides a powerful, personalized approach to address individual training needs, it can be costly to update immersive game engines to address new training objectives. Challenges lie not only in the incorporation of new technology that must be trained, but also in the construction of surrounding training materials—curriculums, performance metrics, and optimal training methods—to address procedures for the new technology. In ongoing work with the Air Force Research Laboratories (AFRL), the authors are developing a modeling framework and editing tools for subject matter experts to translate new technology and Technical Orders (TOs) into training objectives, scenarios, and content for existing virtual game-based trainers. The Methodology for Annotated Skill Trees (MAST) provides a formalism that organizes training goals and associated performance metrics, skill decay models, scaffolding models, and effective training methods. This paper discusses the application of this modeling framework to maintenance training for the F-15E aircraft, and the associated development of editing tools to adapt content both in MAST and in the immersive game engine. This paper also describes an approach to improving training by adapting training objectives to support focused repetition of maintenance procedures and review with instructors. Finally, this paper summarizes initial feedback from active duty instructors, and next steps for improving these tools.
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