Human in the Loop for XR Training: Theory, Practice and Recommendations for Effective and Safe Training Environments

The integration of Extended Reality (XR) technolo-gies and Artificial Intelligence (AI) has revolutionized training in various industries by providing a safe and supervised environ-ment for trainees to acquire practical experience. However, AI alone cannot substitute the expertise of experienced trainers, and the concept of Human in the Loop (HITL) is crucial in bridging this gap. HITL involves human supervision and decision-making in automated systems and has proven to be successful in various industries. This preliminary study focuses on the practical appli-cation of HITL in the context of XR training for medical first responders. The HITL system provides trainers with the ability to remotely monitor and control training sessions, personalize feedback based on trainee performance data, and customizable scenarios that simulate realistic environments and situations. The proposed approach offers practical guidance to developers and researchers in XR training systems regarding the integration of HITL methodology into virtual training environments. The synergy between XR and HITL technology has the potential to revolutionize training methodologies across a range of industries, creating a safer and more efficient training environment that en-hances learning outcomes and reduces training costs. To promote further research on the combination of XR and HITL, this work offers valuable insights for designing future XR systems. These insights are derived from the experience gained in XR training for medical first responders, facilitating the development of more effective and immersive XR training solutions.