Artificial intelligence, ChatGPT, and dental education: Implications for reflective assignments and qualitative research

作者：Mario Brondani, Cláudia Maria Coêlho Alves, Cecília Cláudia Costa Ribeiro, Mariana Minatel Braga, Renata Cunha Matheus Rodrigues Garcia, Thiago Machado Ardenghi, Komkham Pattanaporn · 发表于：Journal of Dental Education · 年份：2024 · DOI：10.1002/jdd.13663 · 被引用次数：27 · 研究领域：Artificial Intelligence in Healthcare and Education、Explainable Artificial Intelligence (XAI)、Clinical Reasoning and Diagnostic Skills

INTRODUCTION: Reflections enable students to gain additional value from a given experience. The use of Chat Generative Pre-training Transformer (ChatGPT, OpenAI Incorporated) has gained momentum, but its impact on dental education is understudied. OBJECTIVES: To assess whether or not university instructors can differentiate reflections generated by ChatGPT from those generated by students, and to assess whether or not the content of a thematic analysis generated by ChatGPT differs from that generated by qualitative researchers on the same reflections. METHODS: Hardcopies of 20 reflections (10 generated by undergraduate dental students and 10 generated by ChatGPT) were distributed to three instructors who had at least 5 years of teaching experience. Instructors were asked to assign either 'ChatGPT' or 'student' to each reflection. Ten of these reflections (five generated by undergraduate dental students and five generated by ChatGPT) were randomly selected and distributed to two qualitative researchers who were asked to perform a brief thematic analysis with codes and themes. The same ten reflections were also thematically analyzed by ChatGPT. RESULTS: The three instructors correctly determined whether the reflections were student or ChatGPT generated 85% of the time. Most disagreements (40%) happened with the reflections generated by ChatGPT, as the instructors thought to be generated by students. The thematic analyses did not differ substantially when comparing the codes and...