Background: The advent of pre-trained generative transformers, exemplified by ChatGPT, has significantly impacted medical education, catalysing a wealth of research focused on enhancing educational methodologies. Despite this, the application of ChatGPT in the specific area of career planning for medical students remains relatively unexplored. This study seeks to rigorously evaluate the potential of ChatGPT-4o in facilitating the career planning of medical students, comparing its effectiveness with that of traditional human educators. It also aims to identify optimal strategies for integrating ChatGPT-4o with human educators to maximise support in career planning for medical students.

Methods: Adopting a mixed-methods approach, this research combines qualitative insights from interviews with quantitative data from questionnaires. The research is bifurcated into two primary segments: first, evaluating the proficiency of ChatGPT-4o in aiding medical students' career planning, and second, identifying effective collaborative practices between ChatGPT-4o and human educators.

Discussion: The study focuses on assessing ChatGPT-4o's utility in career planning for medical students and determining how it can be best used within medical education by both educators and students. The aim is to augment the career planning consultation process, thereby enhancing the efficiency and quality of human educators' contributions. This includes exploring how ChatGPT-4o can supplement traditional teaching methods, providing a more robust and comprehensive support system for career planning in medical education.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11605808PMC
http://dx.doi.org/10.1136/bmjopen-2023-083697DOI Listing

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