基于生成式人工智能的"医学大数据分析"课程创新教学模式研究与实践探索OA

Objective To explore the application effect of generative artificial intelligence(GAI)in Medical Big Data Analysis courses,aiming to enhance medical students'data processing and analysis capabilities,address their weak programming foundation,and explore innovative teaching paths supported by intelligent technology.Methods Medical master and doctoral students enrolled in the course in 2023(the control group,n=57)and 2024(the experimental group,n=58)were selected as the research subjects.The control group received traditional teaching methods,while the experi-mental group was integrated with the intelligent programming assistant"Tongyi Lingma",implement-ing personalized task generation,instant feedback,and intervention strategies to prevent thinking deg-radation.Teaching effectiveness was evaluated based on homework on-time submission rate,usual performance,and final comprehensive exam scores.Results The experimental group significantly out-performed the control group in homework on-time submission rate(95.70%vs.84.70%),usual per-formance[(97.53±0.80)vs.(95.88±2.78)],and final comprehensive exam scores[(91.09±5.99)vs.(85.88±7.09)](all P<0.05).After the intervention,students'code correctness rate increased by 26%,core syntax errors decreased by 57%,and code interpretation ability was significantly en-hanced.Conclusion The GAI-based teaching mode for Medical Big Data Analysis courses can effec-tively improve students'learning engagement,knowledge mastery,and programming practice abil-ity,providing a feasible path and practical evidence for the digital transformation of medical education.