Practical research on the online and offline hybrid teaching model of medical imaging with artificial intelligence empowerment
Year: 2025
Type: article
Abstract: Objective To explore the innovative practice of artificial intelligence (AI) .empowered online and offline hybrid teaching model in medical imaging education. Methods In the teaching of eight.year students of Chinese medicine (including standardized training for residents) in Nanjing University of Chinese Medicine, relying on the national online education platform, the innovation of teaching mode was implemented: an online teaching platform was created to integrate curriculum resources, personalized teaching design and independent learning paths were provided, and AI technology was used by teacher to analyze students.. online tests and learning activities, and adjusted classroom teaching content and course progress in a timely manner. In the offline classroom, classroom teaching was integrated with AI andvirtual simulation technology to create a flipped classroom with real clinical scenes, to form a synchronous outside class and in.class, online and offline collaboration. Results A digital and intelligent online teaching platform and a teachingresource library of medical imaging real cases were created successfully, and medical imaging has been rated as a first. class undergraduate online and offline hybrid course in Jiangsu Province. The new teaching model ranked second in the evaluation of clinical courses at the same level in the whole school, and was well received by experts from other universities. After the new model implementation, the students′ average course was more than 85 points, and the passing rate of the medical practitioner examination reading skills test was more than 90%. The new teaching model won the second prize of the National Challenge Cup and the second prize of the 3rd Jiangsu Teaching Innovation Competition. Conclusion AI-empowered medical imaging teaching mode of “online self-learning plus offline flipped classroom with real clinical scenes” broadens the scope of “visual diagnosis” of Chinese medicine diagnostic methods, provides an accurate visual basis for Chinese medicine clinical syndrome differentiation and treatment, and is conducive to cultivating students’accurate diagnostic thinking and innovative practice ability, and mastering rich and diverse interdisciplinary knowledge that combined Chinese and Western culture.
Authors: ZHENG Liang, HE Xiaojin, WANG Quanquan, YUAN Yongfeng, LAN Xing, ZHU Li
Institution: Nanjing University of Chinese Medicine
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W6904115776
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