Đánh giá các yếu tố ảnh hưởng đến quan điểm của sinh viên Trường Đại học Y Dược Cần Thơ về việc ứng dụng trí tuệ nhân tạo trong học tập năm 2024–2025

In the context of the 4.0 industrial revolution and rapid technological advancements, artificial intelligence (AI) has brought profound changes across various sectors, including education. For the field of medicine and pharmacy, where theoretical knowledge and practical skills are paramount, the application of AI in training is emerging as an inevitable trend. AI offers significant opportunities for students to access modern knowledge, enhance self-study, facilitate clinical simulations, and develop critical thinking skills. While international research has highlighted the positive impacts of AI and the need for ethical guidelines in medical education, domestic studies focusing on student perspectives and factors influencing AI adoption remain limited. This study addresses this gap by assessing the determinants of students' general perception of applying artificial intelligence in learning at Can Tho University of Medicine and Pharmacy for the academic year 2024-2025, providing empirical evidence to guide strategic interventions.

Academics, educators, and policymakers in medical education, university administrators, and researchers interested in artificial intelligence adoption and student perceptions within higher education.

This research investigates the critical factors influencing student perception regarding the application of artificial intelligence (AI) in learning within a medical education context. Employing a cross-sectional online survey via Google Forms, data was collected from 1,676 students at Can Tho University of Medicine and Pharmacy during the 2024-2025 academic year. The methodology involved validating measurement scales through exploratory and confirmatory factor analyses, subsequently testing model relationships using Partial Least Squares Structural Equation Modeling (PLS-SEM). Key findings reveal that the majority of respondents were female (60%) and pharmacy majors (78.2%), and that three significant factors positively predicted students' general perception of AI: trust (β = 0.409), social influence (β = 0.279), and media influence (β = 0.274). These factors collectively accounted for 74.2% of the variance in student perspectives, with trust emerging as the strongest predictor. The study underscores the necessity of prioritizing initiatives that build trust in AI through structured training, clear safety and ethics guidance, and demonstrable educational benefits. Furthermore, leveraging social and media influences can be instrumental in cultivating positive norms for artificial intelligence adoption within medical education. These insights offer valuable guidance for developing effective strategies to integrate AI successfully into healthcare professional training programs.