A Systems Engineering Decision-Making Matrix for Assessing XR Suitability in Task Execution

Extended Reality (XR) technologies, encompassing Virtual Reality (VR) Augmented Reality (AR), and Mixed Reality (MR), possess profound transformative potential across diverse domains such as education and aviation. Yet some tasks or training programs are ill-suited to XR integration, leading to problems ranging from lack of adoption to wasted capital and even harm. This paper introduces a robust decision-making framework to evaluate the suitability and efficacy of XR for a proposed system, addressing the critical need for well-defined criteria that determine when and how to deploy these technologies effectively.Through a comparative analysis of real-world applications, we identify crucial factors influencing XR adoption. Meta-studies of student education platforms reveal that over one-third of XR applications fail, juxtaposed with the aviation sector's extensive success in XR-integrated training programs. These contrasting scenarios underscore the necessity for a methodical approach to XR technology selection and integration, informed by analogous decision matrices from fields like robotics. We propose a metric-driven framework to evaluate XR's suitability for specific tasks or training objectives, drawing parallels with the "4 D’s" of robotic automation.Central to this framework is the introduction of the DIVE acronym: Danger, Immersion, Verification, and Expertise. This guide assesses the viability of XR systems based on the degree of inherent task danger or distraction, the necessity for immersive experiences, the ability to thoroughly verify user performance, and the benefits of delivering domain-specific expertise. Applying the DIVE framework to scenarios like history lectures and aviation training, we demonstrate how XR suitability varies with task demands, emphasizing visual immersion for education and danger simulation for aviation.This structured approach aims to better inform decision-makers, reducing the risk of overly ambitious XR projects that fail due to misalignment, inadequate user engagement, or insufficient technological fidelity. By aligning technological capabilities with project goals, the framework optimizes investments in the rapidly growing XR market, enhancing adoption and ensuring the effective integration of XR in serious applications across various fields.