Generative artificial intelligence adoption and use in teaching and training healthcare professionals in higher education in the United States: a cross-sectional study

Abstract

The use of generative artificial intelligence (GenAI) is rapidly expanding across medical and allied health education. However, structured and curriculum-integrated training to prepare future healthcare professionals remains limited. This study examined the adoption, self-reported knowledge, and perceptions of GenAI among faculty and students in a U.S. higher education institution. We conducted a cross-sectional study using a self-administered online questionnaire to assess GenAI knowledge, adoption, use, benefits, and challenges among faculty and students in a public Minority Serving Institution in California. Using a convenience sampling technique, data were collected with Qualtrics from January – March 2025 and analysed with IBM SPSS Statistics version 31. A total of 559 complete responses were analysed (faculty: 19.3%; students: 78.5%). Overall, 83.2% of respondents reported having used GenAI, including 91.1% of faculty and 81.4% of students, with no statistically significant difference by role (p = .12). Only 7.9% had received formal training in GenAI, while 29.1% reported having conducted substantial independent research on GenAI (faculty: 48.5%; students: 24.3%). Nearly half of participants (48.7%) perceived GenAI as beneficial for learning, teaching, and research (p = .002). Additionally, 47.4% believed GenAI is currently essential, and 70.8% anticipated it will become essential in the future, with significant more faculty respondents asserting the importance of AI (p < .001 and p = .009, respectively). Most respondents relied on free GenAI tools (90.6%), and among users of paid tools, 66.3% paid out of pocket. Participants primarily sourced GenAI information from the internet (77.3%), reported substantial concerns (70.3%), and experienced multiple challenges in GenAI use (84.7%). GenAI use among faculty and students is widespread, but formal training and institutional support remain limited. These findings underscore the need for coordinated, campus-wide GenAI training, governance, and policy frameworks to promote ethical, effective, and equitable integration of GenAI into healthcare education and workforce preparation.

Ähnliche Arbeiten