Data Science Driven Aircrew Performance Measurement and Proficiency System

The objective of this proposal is to design a software solution that consolidates performance data from multiple sources to ensure that data collection and assessment processes are accurate, efficient, and effective. The designed solution will leverage the work already conducted by NAVAIR’s Training Analysis Project (TAP) regarding F/A-18 air warfare. In doing so, the software will adhere to training best practices and align with the performance metrics that TAP has already identified as being critical to mission success in Component Commander plans. Since TAP’s processes were designed to be scalable, this software will provide a methodology for the NAE to duplicate the entire TAP process for other platforms and mission sets in a manner that is streamlined and efficient. Artificial intelligence will be applied to enable automated and semi-automated methods for collection of data, assessment of performance, and reporting of training deficiencies. This improves the speed and effectiveness of the feedback to the trainee and the NAE leadership. The software will be designed to reside on hardware that is already resident at Fleet training locations (to reduce the physical footprint) and will incorporate an intuitive user interface (to minimize the need for additional aircrew training).