This randomized controlled trial will explore how instructor type-human vs. machine-affects performance, immersion, and stress during VR-based Basic Life Support (BLS) training. Participants will receive VR based education wither with a machine instructor or a human instructor and complete a simulated emergency exam. Outcomes will include procedural accuracy, physiological stress (measured via electrodermal activity), and subjective evaluations of presence and instructor effectiveness.

In high-stakes medical emergencies, both technical proficiency and psychological resilience are critical. Traditional Basic Life Support (BLS) training methods-such as lectures, role-play, and manikin-based practice-help students build core skills but often fall short in replicating the stress and complexity of real-world crises. As medical education evolves, virtual reality (VR) is emerging as a promising tool, offering immersive, controlled environments that simulate emergency conditions while supporting both skill acquisition and psychological engagement. However, while VR's benefits for technical training are well-established, its impact on stress management and mental preparedness remains underexplored.

This study will examine how the type of instructor-human or machine-within a VR-based training environment influences students' performance, immersion, and stress responses during BLS training. Participants will undergo VR-based BLS instruction led by either a human educator or a software-based guide, followed by a simulated emergency exam. Outcomes will be assessed through procedural accuracy, physiological stress measured via electrodermal activity (EDA), and subjective evaluations of presence and instructor effectiveness.

The findings are expected to shed light on how different instructional approaches in VR affect not only learning outcomes but also students' capacity to manage stress in high-pressure situations. By identifying how instructor type influences both competence and psychological resilience, this research aims to optimize VR-based medical training for the demands of real-world clinical practice.

Inclusion Criteria:

• Being older than 18

Exclusion Criteria:

• prior completion of Basic Life Support (BLS) training
• history of virtual reality (VR)-induced motion sickness
• medical conditions such as vertigo or the use of medications known to cause vertigo-like symptoms