Flexible and Live Adaptive Training Tools (FLATT)

We propose to research and develop Flexible and Live Adaptive Training Tools (FLATT) as a flexible user interface capability within a generalized framework that can be applied to a wide variety of training instances. We plan to leverage our Generalized Intelligent Framework for Tutoring (GIFT) toolset because it is a flexible, expandable, service-oriented architecture (SOA)-based system that provides crucial capabilities to communicate with virtual training environments, gather data from sensors, and characterize learner models. FLATT will be designed so that it can run independent of GIFT, but we will integrate to leverage existing GIFT modules and capabilities, such as the ability to communicate real-time scenario adaptations to a virtual environment. Data in support of the trainee state will be provided to FLATT via sensors such as accelerometers, GPS, or bio-harness, as well as from the state of virtual training environment. FLATT will visualize the data that contributes to the trainee state, and enable the user to adapt the training environment, either automatically via a rule, or manually in real-time.