Exploring medical students' intention to use of ChatGPT from a programming course: a grounded theory study in China.

Abstract

Background: In interdisciplinary general education courses, medical students face the daunting challenge of learning programming due to academic pressure, cognitive biases, and differences in thinking patterns. ChatGPT provides an effective way for people to acquire knowledge, improve learning efficiency, and quality.

Objective: To explore whether medical students can be assisted in learning programming with the help of ChatGPT, it is necessary to investigate their experience and perception of using ChatGPT, and to study which factors influence their willingness to use ChatGPT.

Methods: Drawing on the grounded theory research paradigm, this paper constructs a research model of the influencing factors of ChatGPT usage willingness for medical students in programming courses through the analysis of interview data from 30 undergraduate medical students. It analyzes and discusses the cognition and influencing factors of medical students' willingness to use ChatGPT in programming learning.

Results: The willingness to use ChatGPT in programming learning is divided into three types based on the students' subjective degree of use: active use, neutral use, and negative use. It is also found that individual factors, technical factors, information factors, and environmental factors are four important dimensions affecting the willingness to use ChatGPT.

Conclusions: Based on the analysis of influencing factors, strategies and suggestions such as preventing risks and focusing on ethical education, cultivating critical thinking and establishing a case library, and personalized teaching to enhance core literacy in programming are proposed.