AI in medical education: the moderating role of the chilling effect and STARA awareness

Abstract

Abstract Background The rapid growth of artificial intelligence (AI) technologies has been driven by the latest advances in computing power. Although, there exists a dearth of research on the application of AI in medical education. Methods this study is based on the TAM-ISSM-UTAUT model and introduces STARA awareness and chilling effect as moderating variables. A total of 657 valid questionnaires were collected from students of a medical university in Dalian, China, and data were statistically described using SPSS version 26, Amos 3.0 software was used to validate the research model, as well as moderated effects analysis using Process (3.3.1) software, and Origin (2021) software. Results The findings reveal that both information quality and perceived usefulness are pivotal factors that positively influence the willingness to use AI products. It also uncovers the moderating influence of the chilling effect and STARA awareness. Conclusions This suggests that enhancing information quality can be a key strategy to encourage the widespread use of AI products. Furthermore, this investigation offers valuable insights into the intersection of medical education and AI use from the standpoint of medical students. This research may prove to be pertinent in shaping the promotion of Medical Education Intelligence in the future.