AI-Powered Virtual Human Simulation in Students

Critical care requires timely patient assessment, clinical judgment, and appropriate intervention, yet respiratory therapy students may have limited opportunities to experience complex clinical situations before entering clinical training. Traditional teaching methods are often based on lectures, case discussions, and demonstrations, and may be limited by available facilities, equipment, and clinical cases. AI-based virtual human simulation provides a safe and repeatable environment in which students can practice clinical decision-making and receive immediate feedback. This study will recruit eligible respiratory therapy students who voluntarily participate in AI-based critical care simulation training and will compare pre- and post-training assessments of learning outcomes, self-efficacy, and learning experience. The training is expected to improve students' critical care knowledge, clinical reasoning, confidence, and learning engagement, and the findings may provide a reference for future pre-clinical training and AI-assisted respiratory therapy education.

Inclusion criteria

• Respiratory therapy students participating in the pre-clinical training course, "Clinical Application of Critical Care Respiratory Therapy," at Fu Jen Catholic University Hospital between September 10 and October 10, 2026
• Able to communicate verbally in Mandarin and complete study-related questionnaires and interviews
• Considered suitable by the course instructor to participate in the AI-based virtual human simulation training
• Willing to participate

Exclusion criteria

• Students considered unsuitable by the course instructor to participate in the AI-based virtual human simulation training
• Individuals who are unable to communicate effectively in Mandarin, complete the study training, or complete study questionnaires due to language, cognitive, or other factors
• Individuals who are unwilling to participate in the study