Student Usability of an AI-Based Process-Oriented Approach for EBM Education in Korean Medicine
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Objectives: Evidence-based medicine (EBM) education often emphasizes the critical evaluation of published research as a final product, neglecting the dynamic and ongoing nature of scientific inquiry. Our recent proof-of-concept study highlighted the educational potential of an AI-based research note generation system from the perspective of faculty educators. However, the actual learning experience and effectiveness from the students’ viewpoint remain unexamined. Methods: This study assessed the usability and perceived educational value of an AI-based research note generation system for Korean medicine (KM) students. A cross-sectional study involved 36 fourthyear students who used the system for an assignment. The assignment required students to upload clinical research papers, review 10 AI-generated research notes, answer three AI-generated questions, and receive AI feedback. Evaluation methods included a mixed-use questionnaire and the EBM interest rating scale, which was scored on a 0∼10 scale before and after the task. Results: Participants reported high overall satisfaction, with the highest scores in “Usefulness and Convenience” (4.53±0.43) and “System Usability” (4.51±0.51). After completing the assignment, students’ interest in EBM increased significantly (from 5.25 to 7.19, p< 0.001). Qualitatively, students valued the “proxy experience” of engaging in the research process, appreciated the time efficiency of the system, and critically noted issues with AI content accuracy. Conclusions: This study indicates that an AI-based, process-centered learning approach is a feasible and promising strategy for EBM education, significantly enhancing student motivation and interest. While students recognized the advantages of using this system, they also critically acknowledged the limitations of AI, particularly concerning content accuracy.
Abstract
Objectives: Evidence-based medicine (EBM) education often emphasizes the critical evaluation of published research as a final product, neglecting the dynamic and ongoing nature of scientific inquiry. Our recent proof-of-concept study highlighted the educational potential of an AI-based research note generation system from the perspective of faculty educators. However, the actual learning experience and effectiveness from the students’ viewpoint remain unexamined. Methods: This study assessed the usability and perceived educational value of an AI-based research note generation system for Korean medicine (KM) students. A cross-sectional study involved 36 fourthyear students who used the system for an assignment. The assignment required students to upload clinical research papers, review 10 AI-generated research notes, answer three AI-generated questions, and receive AI feedback. Evaluation methods included a mixed-use questionnaire and the EBM interest rating scale, which was scored on a 0∼10 scale before and after the task. Results: Participants reported high overall satisfaction, with the highest scores in “Usefulness and Convenience” (4.53±0.43) and “System Usability” (4.51±0.51). After completing the assignment, students’ interest in EBM increased significantly (from 5.25 to 7.19, p< 0.001). Qualitatively, students valued the “proxy experience” of engaging in the research process, appreciated the time efficiency of the system, and critically noted issues with AI content accuracy. Conclusions: This study indicates that an AI-based, process-centered learning approach is a feasible and promising strategy for EBM education, significantly enhancing student motivation and interest. While students recognized the advantages of using this system, they also critically acknowledged the limitations of AI, particularly concerning content accuracy.