TITLE:
Effects of a Digital Intelligence-Empowered Blended Teaching Model in a Medical Reproductive System Course
AUTHORS:
Xiaoling He, Chao Tong, Huijia Fu, Jing Zhang
KEYWORDS:
Digital Intelligence Technology, Mixed Teaching, Reproductive System Course, Medical Education, Teaching Reform
JOURNAL NAME:
Open Journal of Social Sciences,
Vol.13 No.10,
October
11,
2025
ABSTRACT: Objective: To investigate the efficacy of an integrated online and offline teaching model empowered by digital intelligence in the course on reproductive system diseases. Methods: A total of 192 first-semester clinical medicine students from September 2023 to July 2024 were assigned to the control group, receiving traditional instruction. Meanwhile, 172 second-semester students formed the observation group, where a blended teaching approach incorporating digital medicine was implemented. Post-semester evaluations compared the teaching quality and learning outcomes between the two groups. Results: The observation group exhibited lower usual scores but significantly higher final exam and overall scores compared to the control group (P P P > 0.05). Overall satisfaction was notably higher in the observation group (P Conclusion: The implementation of a digital intelligence-enabled blended teaching model in reproductive system disease courses significantly improves academic performance and practical skills, with high student satisfaction. This approach holds potential for enhancing teaching quality and fostering comprehensive student development.