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.
Approach:
Study Design: A randomized controlled trial involving 98 fifth-year clinical medicine students assigned to either an experimental group (CBL + ChatGPT) or a control group (traditional lectures).
Intervention: The experimental group engaged in an 8-week program with structured human-AI interactions, while the control group received conventional multimedia lectures.
Outcome Measures: Outcomes included theoretical knowledge examination scores, case analysis scores, recognition rates across seven dimensions, and overall teaching satisfaction.
Key Findings:
The experimental group had significantly higher theoretical examination scores (86.4 ± 5.2 vs. 78.9 ± 6.1, P < 0.01).
Case analysis scores were also higher in the experimental group (84.7 ± 6.3 vs. 74.2 ± 7.5, P < 0.01).
Recognition rates across all seven evaluation dimensions were significantly higher in the experimental group (all P < 0.05).
Overall satisfaction was 89.8% in the experimental group compared to 63.3% in the control group (P < 0.01).
Students with weaker academic foundations showed the greatest improvement in scores (+12.3 points, P < 0.01).
Interpretation:
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.
Limitations:
The study's sample size was limited to a single institution.
The long-term retention of knowledge was not assessed.
Conclusion:
The integration of ChatGPT in CBL shows substantial potential for broader implementation in medical education.
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