Design strategies for artificial intelligence based future learning centers in medical universities.

ABSTRACT:

Background

This study explores the acceptance of artificial intelligence(AI) tools in medical students and its influencing factors, thus providing theoretical basis and practical guidance for the construction of future learning centers in medical universities.

Methods

This study comprehensively applied the unified theory of acceptance and use of technology(UTAUT), expectancy confirmation theory (ECT), and innovation diffusion theory (IDT) to analyze the data through structural equation modeling.

Results

Effort expectancy (EE), facilitating condition (FC), social influence (SI), and satisfaction (SA) significantly influence medical students' continuance intention (CI) to use artificial intelligence tools. Relative advantage (RA) has a significant impact on medical stud

SUBMITTER: Xiaowen Y 

PROVIDER: S-EPMC11786482 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature