Research Article: Application effect and teaching evaluation of case-based learning combined with ChatGPT in ophthalmology clinical teaching
Abstract:
To investigate the effectiveness of a case-based learning (CBL) model integrated with ChatGPT in ophthalmology clinical teaching and to compare its educational outcomes with those of the traditional multimedia lecture-based approach.
A total of 98 fifth-year clinical medicine students from Shanghai Jiao Tong University School of Medicine (Class of 2021) were randomly assigned to an experimental group (CBL + ChatGPT, n = 49) or a control group (traditional lecture-based teaching, n = 49). The teaching intervention lasted for 8 weeks, with one 90-min session per week. The experimental group adopted a standardized human-AI interaction protocol, including a structured questioning framework, no fewer than three rounds of dialog, and real-time teacher supervision and correction. The control group received conventional multimedia lectures. Outcomes included theoretical knowledge examination scores, case analysis scores, recognition rates of the teaching model across seven dimensions, and overall teaching satisfaction. Subgroup analyses were further conducted according to students’ baseline academic performance (high-, medium-, and low-foundation groups).
The experimental group achieved significantly higher theoretical examination scores than the control group (86.4 ± 5.2 vs. 78.9 ± 6.1, P < 0.01), as well as higher case analysis scores (84.7 ± 6.3 vs. 74.2 ± 7.5, P < 0.01). Recognition rates across all seven evaluation dimensions, including interactivity, immediate feedback, and clinical relevance, were significantly higher in the experimental group (all P < 0.05). The overall satisfaction rate was 89.8% in the experimental group and 63.3% in the control group ( P < 0.01). Subgroup analysis demonstrated that students with weaker academic foundations benefited most from the intervention, showing the greatest improvement in scores (+12.3 points, P < 0.01). These students also reported significantly higher recognition of personalized learning experiences than students with stronger academic backgrounds (95.2% vs. 81.2%, P < 0.05).
The CBL teaching model integrated with ChatGPT significantly improves both objective learning outcomes and subjective satisfaction in ophthalmology clinical education, particularly among students with weaker academic foundations. This teaching approach demonstrates substantial potential for broader implementation in medical education.
Introduction:
Artificial intelligence (AI) technologies are increasingly transforming medical education by enabling adaptive, interactive, and learner-centered learning environments ( 1 – 4 ). Large language models represented by ChatGPT have demonstrated promising performance in medical knowledge assessment ( 5 – 7 ), clinical reasoning support ( 8 , 9 ), improvement in clinical consultation and patient interviewing skills ( 10 , 11 ), and personalized educational assistance ( 12 , 13 ), thereby attracting growing attention in…
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