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Exploration of the Intelligent Medical Education Model to Support the Reform of Diagnosis Practice Teaching

In: Proceedings of the 2024 6th Management Science Informatization and Economic Innovation Development Conference (MSIEID 2024)

Author

Listed:
  • Yu Fang

    (Shaanxi University of Chinese Medicine, Department of Basic Medicine)

  • Yina Jiang

    (Shaanxi University of Chinese Medicine, Department of Basic Medicine)

  • Yujuan Huang

    (Shaanxi University of Chinese Medicine, Department of Basic Medicine)

Abstract

This paper takes the reform of practical teaching in diagnostics at traditional Chinese medicine (TCM) colleges and universities as its background, focusing on the application and effectiveness of the smart medical education model in the reform of practical teaching in diagnostics. The article discusses the multi-system reform of the “Diagnostics” practical training course, including the digital and intelligent transformation of teaching resources, the innovation of teaching content and methods, and the reform of evaluation methods. Finally, through empirical research, the diagnostic skills assessment results of the five-year undergraduate students majoring in Traditional Chinese Medicine Orthopedics at Shaanxi University of Traditional Chinese Medicine in 2020 and 2021 were analyzed. It was found that there was a significant difference in the skills assessment results between the reform group and the control group, indicating that the reform has achieved positive results. It provides new ideas and methods for the reform of diagnostic teaching at TCM colleges and universities.

Suggested Citation

  • Yu Fang & Yina Jiang & Yujuan Huang, 2025. "Exploration of the Intelligent Medical Education Model to Support the Reform of Diagnosis Practice Teaching," Advances in Economics, Business and Management Research, in: Manhui Huang & Vilas B. Gaikar & Md Rabiul Islam & Ivan Krumov Todorov (ed.), Proceedings of the 2024 6th Management Science Informatization and Economic Innovation Development Conference (MSIEID 2024), pages 338-345, Springer.
    • Handle: RePEc:spr:advbcp:978-94-6463-676-5_32
    DOI: 10.2991/978-94-6463-676-5_32
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