Combining XR and AI for Integrating the Best Pedagogical Approach to Providing Feedback in Surgical Medical Distance Education

This position paper maintains that learners' involvement and accurate representation through cues and stimuli are essential aspects of an AI-guided XR app for learning surgery. It then shows how and why it is crucial to conduct expert interviews when designing/developing such an app. A multidisciplinary team of 22 experts was interviewed to provide insights into new visual technologies' intercommunication (i.e., Extended Reality-XR, Artificial Intelligence -AI or Machine Learning-ML, and 360 degrees videos) and the pedagogical aspects (i.e., educational theories, techniques, and practices) of designing an XR system supported by an ML-based subsystem. These insights are about instructional design elements to maximize the impact of simulation-based training (SBT). The paper guides educational games for medical surgery design and user experience theory and concepts. It shows howto capture the actual task's and environment's fundamental characteristics expressing realistic behaviors. It shows the significant issues (e.g., occlusion and the use of instruments) in capturing these tasks and possible options to overcome them (e.g., using video feeds from endoscopies and robotic surgery). It also provides practical opportunities for facilities in resource-constrained regions lacking internet access/reliability/speed. For qualifying impact, this paper provides the best way to measure learning experience return on investment for medical education.