Use and perception of generative artificial intelligence in traditional Korean medicine education: A cross-sectional survey of undergraduate students in Korea

Abstract

Background

This study aimed to examine the usage, awareness, and satisfaction related to generative AI (GenAI) among undergraduate students at a Traditional Korean Medicine (TKM) college in Korea and to identify factors associated with GenAI use and satisfaction.

Methods

A structured questionnaire consisting of 56 items across six domains was administered, covering demographics, general and TKM-specific GenAI use, satisfaction, educational experiences, and future expectations. Descriptive statistics, univariable analysis, multivariable logistic regression, and correlation analysis were performed.

Results

A total of 234 students across six academic years participated in the survey. Most respondents were aware of GenAI (88.5 %) and used it for general purposes (79.9 %). However, only 16.2 % actively used it for TKM learning. While 70.4 % were satisfied with using GenAI in general, only 45.8 % felt satisfied with its use for TKM education. Factors significantly associated with GenAI use or satisfaction included enrollment in the TKM curriculum, older age, prior major, scholarship receipt, and self-directed GenAI learning. Although only 18.8 % had experienced GenAI in formal TKM courses, 96.2 % viewed GenAI as necessary in TKM education.

Conclusion

A notable gap exists between students’ interest and the limited integration of GenAI in TKM curricula. To close this gap, GenAI should be systematically incorporated into educational programs, accompanied by faculty training and institutional support to enhance students’ digital readiness and learning outcomes.