Endless possibilities in academia
Endless possibilities in academia
Yunyang Wu1, Yuanyuan Meng2, Tingru Chen2, Qinwufeng Gu2, Ling Tang2, Yanlong Yang1
1School of Traditional Chinese Medicine, Naval Medical University, Shanghai 200433, China. 2Department of Traditional Chinese Medicine, The First Affiliated Hospital of Naval Medical University, Shanghai 200433, China.
Address correspondence to: Yanlong Yang, School of Traditional Chinese Medicine, Naval Medical University, 800 Xiangyin Road, Shanghai 200433, China. E-mail: yangyanlong@smmu.edu.cn. Ling Tang, Department of Traditional Chinese medicine, The First Affiliated Hospital of Naval Medical University, 168 Changhai Road, Shanghai 200433, China. E-mail: tanglingyu@126.com.
DOI: https://doi.org/10.61189/728207gnvvpc
Received June 5, 2025; Accepted July 28, 2025; Published September 30, 2025
Highlights
● The integration of the BOPPPS comprehensive teaching approach with problem-based learning in Traditional Chinese Medicine surgery education is proposed.
● Using eczema as a case study, the focus is on implementing a student-centered, problem-oriented teaching model.
● Enhancing the faculty team and implementing a robust feedback mechanism can improve students' learning outcomes.
Research Article |Published on: 30 September 2025
[Progress in Medical Education] 2025; 1 (2): 63-68.
Linlin Chen*, Shuo Yang*, Zhanheng Chen, Zixin Li, Mi Li, Zui Zou, Zhibin Wang
School of Anesthesiology, Naval Medical University, Shanghai 200433, China
*The authors contribute equally.
Address correspondence to: Zhibin Wang, Department of Critical Care Medicine, School of Anesthesiology, Naval Medical University, 168 Changhai Road, Shanghai 200433, China. E-mail: methyl@smmu.edu.cn. Zui Zou, School of Anesthesiology, Naval Medical University, 168 Changhai Road, Shanghai 200433, China. E-mail: zouzui1980@163.com.
Acknowledgement: This work was supported by the Anesthesiology Department Teaching Development Foundation of Naval Medical University under grant (2024MZQN02 and 2024MZQN03).
DOI: https://doi.org/10.61189/680530ermmyu
Received June 12, 2025; Accepted July 29, 2025; Published September 30, 2025
Highlights
● A comprehensive disaster medicine assessment system is established based on the "cognitive-skill-attitude" triad, incorporating six evaluation components: pre-class preparation, pre-class tests, case discussions, skills assessment, post-class tests, and post-class feedback.
● The system features multiple simulated disaster scenarios and integrates high-fidelity mannequins to achieve a "teaching-training-assessment" integration, with 91% of students reporting that it enhanced their disaster response capabilities.
● An innovative multi-subject evaluation framework ("self-peer-teacher", 40% weighting) is introduced, shifting learners into active evaluator roles to foster teamwork and reflective practice.
Research Article |Published on: 30 September 2025
[Progress in Medical Education] 2025; 1(2): 69-76.
Linlin Chen1*, Zhibin Wang1*, Xiaojing Guo1 , Zhanheng Chen1 , Zixin Li1 , Mi Li1 , Weiheng Xu2 , Zui Zou1 , Shuo Yang1
1School of Anesthesiology, Naval Medical University, Shanghai 200433, China. 2School of Pharmacy, Naval Medical University, Shanghai 200433, China.
*The authors contribute equally.
Address correspondence to: Shuo Yang, Department of Critical Care Medicine, School of Anesthesiology, Naval Medical University, 168 Changhai Road, Shanghai 200433, China. E-mail: charlotteyang@smmu.edu.cn; Zui Zou, School of Anesthesiology, Naval Medical University, 168 Changhai Road, Shanghai 200433, China. E-mail: zouzui1980@163.com.
Acknowledgement: This work was supported by the Anesthesiology Department Teaching Development Foundation of Naval Medical University (2024MZQN03) and the Teaching Research and Reform Project of Naval Medical University (JYG2024B24).
DOI: https://doi.org/10.61189/793750gpxnge
Received June 23, 2025; Accepted August 28, 2025; Published September 30, 2025
Highlights
● This study introduces an AI-empowered blended teaching model for disaster medicine, integrating generative AI, virtual simulations, and intelligent assessment systems to improve teaching efficiency and student engagement.
● The model employs a “dual-teacher collaboration” approach, combining AI-driven tools with human instructors to foster critical thinking and ethical awareness in disaster response training.
● A multidimensional evaluation system was developed, combining dynamic AI-based assessments, scenario- driven simulations, and long-term tracking to provide personalized feedback and support continuous learning.
● The course emphasizes interdisciplinary integration across engineering, information technology, and psychology, aiming to cultivate comprehensive disaster management competence and strengthen professional responsibility.
Research Article |Published on: 30 September 2025
[Progress in Medical Education] 2025; 1 (2): 77-84.
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