FACTORS INFLUENCING THE DECISION TO USE GENERATIVE AI FOR STUDENT LEARNING: A CASE STUDY OF THE FACULTY OF MEDICINE SIRIRAJ HOSPITAL
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Introduction: The development of artificial intelligence technology, particularly Generative AI, is transforming learning approaches in medical education, which emphasizes high precision and ethics. Despite its potential to enhance learning efficiency, the application of this approach in medical education still raises numerous questions and concerns. Objective: This study examined factors influencing medical students' adoption of Generative AI for learning at the Faculty of Medicine Siriraj Hospital. The research applied the Unified Theory of Acceptance and Use of Technology (UTAUT) framework, extended with trust and anxiety constructs. Method: This quantitative research used a survey method via online questionnaires. The sample consisted of 412 Siriraj medical students with experience using Generative AI. Data was analyzed using Stepwise Multiple Regression. Results: Factors influencing the decision to use Generative AI, in order of importance, are perceived usefulness (strongest positive influence), followed by trust, environmental conditions (negative influence), performance expectancy, anxiety, and social influence (positive influences). All factors explained 65.7% of the variance in usage decisions. Gender significantly influenced adoption intention (p<0.05), with male students demonstrating higher acceptance rates. Age and academic year showed no significant effects. Conclusion: Medical students prioritize the benefits and reliability of technology. Educational institutions should focus on communicating clear benefits, building trust, and develop appropriate support mechanisms to maximize effective AI integration in medical education.
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