Transforming Compliance Training for Drone Operators through an Extended Reality and Generative Artificial Intelligence-Driven System

This project aims to serve the national interest by developing personalized and immersive learning solutions for teaching Federal Aviation Administration (FAA) regulations (part 107) for operating Unmanned Aircraft Systems (UAS) in combination with basic UAS operation to support current and next-generation STEM students. The goal of this IUSE:EDU Level 1 Engaged Student Learning project includes developing an advanced Extended Reality (XR) training system that combines FAA Part 107 regulations and UAS operation, powered by Generative AI (GenAI) assistance. The system aims to improve regulatory compliance, safety, and operational proficiency in drone operations by leveraging GenAI's capabilities to generate multimodal content and real-time guidance. The project plans to integrate FAA Part 107 regulations into a GenAI-assisted XR-based UAS training system to enhance the realism and effectiveness of pilot education. The overarching goal of the project is to enhance interactivity, personalization, and support for trainees, creating a dynamic learning environment that continuously adapts to user needs. This project seeks to develop SKYGEN-XR (Smart Knowledge to Fly with GenAI and XR), an advanced training system which will integrate XR and GenAI to enhance drone operation education in the Architecture, Engineering, and Construction (AEC) industry. As unmanned aircraft systems (UAS) become vital tools in AEC, their use in complex environments brings safety risks and requires compliance with FAA Part 107 regulations. Traditional training methods often fall short of preparing operators for these challenges; SKYGEN-XR plans to address this gap by introducing an immersive, AI-assisted platform that combines regulatory instruction with realistic, scenario-based simulations. The project aims to improve safety, regulatory compliance, and operational proficiency by providing innovative interactive and personalized learning experiences. The project’s goal is to contribute to research in AI-driven compliance training, XR learning, and educational technology design. The project plans to explore new methodologies for regulation-focused instruction and promote active learning to increase student comprehension and retention. Once developed, the SKYGEN-XR will be implemented at the University of Texas at Arlington and K-12 partner institutions. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.