Using Proactive Computing for Real-Time Feedback in High-Fidelity Medical Simulation

Using simulation for medical education improves clinical practice and creates a safe environment for students to develop skills. High-fidelity patient simulators, as one kind of simulation tool, use advanced life-like manikins. A high-fidelity simulation session includes pre-briefing, simulation scenarios, and debriefing. While pre-briefing and debriefing are widely recognized, the reflection-in-action during simulation is often overlooked despite its importance. Reflection-in-action is the ability to reflect on the student and adapt during the simulation. One major issue regarding reflection-in-action is the limited number of instructors at the university compared to the large number of students. In addition, the intensive time required for the simulations further constrains the capacity of the instructors. To address this critical gap, we propose using a proactive computing approach to provide real-time support for decisions in high-fidelity medical simulations. By implementing the proactive system and providing immediate adaptive feedback to students based on sensor data, we hope to assist teachers and improve learning outcomes.