Personalized Learning Assistant for Training Optimization (PLATO)

Given the Air Force’s significantly reduced infrastructure and force footprint, future Airmen deployed to remote  air bases will need to be agile and able to respond to an extended scope of novel mission tasks, and to do so quickly. This requires Airmen who can take on cross-functional roles and provide on-demand response to novel tasks and situations. To enable these multicapable Airmen to perform effectively in austere environments requires providing training content to them regardless of what equipment is available. Therefore, Charles River Analytics is developing the Personalized Learning Assistant for Training Optimization (PLATO). PLATO is a context-aware system for multimission just-in-time training. PLATO intelligently adapts the selection, formatting, and interaction modalities of training content to address specific and changing training needs, situational contexts, and hardware available to Airmen in austere mission environments. PLATO’s contextual models map machine-readable training data to the interaction modalities of available hardware based on models of the environment, tools, interactions, and tasks, while adapting the interaction modalities to ensure training is available at the point of use. The success of our Phase I effort laid the foundations for us to develop and evaluate a full-scope Phase II prototype.