Study on curriculum reconstruction of oral and maxillofacial surgery driven by a voice-interactive artificial intelligence agent_West China Medical Journal

Authors：

LI Zhixuan , ZHU Guiquan , LI Chunjie ,  GUO Zhiyong

State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Department of Head and Neck Oncology, West China Hospital of Stomatology, Sichuan University, Chengdu, Sichuan 610041, P. R. China;

Corresponding author：

GUO Zhiyong, Email: zhiyongguo@scu.edu.cn

Keywords：

Oral and maxillofacial surgery; artificial intelligence agent; teaching reform; medical education

DOI：

10.7507/1002-0179.202512078

Video：

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Objective To investigate the effectiveness of applying a voice-interactive artificial intelligence (AI) agent in the teaching of oral and maxillofacial surgery. Methods Fourth-year undergraduate students enrolled at West China School of Stomatology, Sichuan University, from September 2024 to June 2025 were included. Students were randomly assigned by class into two groups: an AI-assisted teaching group (experimental group) that utilized a voice-interactive AI agent, and a traditional face-to-face teaching group (control group). Results A total of 227 students were enrolled, with 122 in the experimental group and 105 in the control group. The average final exam score of the experimental group was higher than that of the control group [(88.34±5.75) vs. (84.30±8.10) points, P<0.001]. The course attendance rate was similar between the experimental and control groups [97.30% (2849/2928) vs. 97.34% (2453/2520)]. However, participation in thought-provoking questions was higher in the experimental group than in the control group [92.08% (2696/2928) vs. 83.17% (2096/2520)]. All evaluations of course satisfaction in the experimental group were significantly higher than those in the control group (P<0.05). Conclusion Teaching of oral and maxillofacial surgery driven by a voice-interactive AI agent demonstrated markedly better outcomes compared with the traditional instructional model.

Citation： LI Zhixuan, ZHU Guiquan, LI Chunjie, GUO Zhiyong. Study on curriculum reconstruction of oral and maxillofacial surgery driven by a voice-interactive artificial intelligence agent. West China Medical Journal, 2026, 41(1): 108-112. doi: 10.7507/1002-0179.202512078 Copy

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14.	韦毅, 黄仁杰. 基于 AI 思政智能体的外语类高校思政课教学育人传播路径探索. 传播与版权, 2025(18): 98-101.
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18.	杨鸿, 周霞. 生成式人工智能在呼吸内科的应用进展. 数理医药学杂志, 2025, 38(1): 60-66.

1. Khakpaki A. Advancements in artificial intelligence transforming medical education: a comprehensive overview. Med Educ Online, 2025, 30(1): 2542807.
2. 梁竹梅, 李鲍, 赵冬梅. 以 AI 智能体重构学习过程——教学智能体创建案例分析与思考. 中国大学教学, 2025(9): 80-86.
3. Ahsan Z. Integrating artificial intelligence into medical education: a narrative systematic review of current applications, challenges, and future directions. BMC Med Educ, 2025, 25(1): 1187.
4. 田建林, 段磊, 韩雪凉. 知识图谱驱动的人工智能教学赋能一流人才培养实践. 中国信息技术教育, 2025(19): 109-112.
5. 蒋友涵, 徐瑾劼. 意大利智能体赋能教师 AI 协同教学素养的多元建构与实践探索. 上海教育科研, 2025(11): 28-33.
6. 陈金龙, 汤炜, 田卫东. 国内外口腔颌面外科教育培训体系对比. 中国实用口腔科杂志, 2022, 15(1): 33-35, 40.
7. Tozsin A, Ucmak H, Soyturk S, et al. The role of artificial intelligence in medical education: a systematic review. Surg Innov, 2024, 31(4): 415-423.
8. Shaw K, Henning MA, Webster CS. Artificial intelligence in medical education: a scoping review of the evidence for efficacy and future directions. Med Sci Educ, 2025, 35(3): 1803-1816.
9. Szatkowski JP, Druten E, Soni C, et al. Artificial intelligence in orthopaedic education: a narrative review. Ann Jt, 2025, 10: 34.
10. 王影, 周瑜, 李春洁, 等. 基于 AI 赋能宏环境下口腔医学生在线课程应用模式的问卷调查研究. 遵义医科大学学报, 2025, 48(9): 945-952.
11. 罗淼, 蔡维霞. 教学智能体的发展脉络、教育纾困与潜在风险. 武汉商学院学报, 2025, 39(5): 93-96.
12. Shah SV. Accuracy, consistency, and hallucination of large language models when analyzing unstructured clinical notes in electronic medical records. JAMA Netw Open, 2024, 7(8): e2425953.
13. 张澍, 孟列素, 刘进军, 等. DeepSeek 进课堂——AI 智能体在器官系统整合课程教学中的应用探索与思考. 中国医学教育技术, 2025, 39(4): 432-436.
14. 韦毅, 黄仁杰. 基于 AI 思政智能体的外语类高校思政课教学育人传播路径探索. 传播与版权, 2025(18): 98-101.
15. Knopp MI, Warm EJ, Weber D, et al. AI-enabled medical education: threads of change, promising futures, and risky realities across four potential future worlds. JMIR Med Educ, 2023, 9: e50373.
16. Abd-Alrazaq A, AlSaad R, Alhuwail D, et al. Large language models in medical education: opportunities, challenges, and future directions. JMIR Med Educ, 2023, 9: e48291.
17. 殷宝媛, 唐瑀晗, 吴恋, 等. 教育智能体支持人机协同教学: 数智时代教学的新形态. 吉林师范大学学报(人文社会科学版), 2025, 53(3): 67-75.
18. 杨鸿, 周霞. 生成式人工智能在呼吸内科的应用进展. 数理医药学杂志, 2025, 38(1): 60-66.

West China Medical Journal

Study on curriculum reconstruction of oral and maxillofacial surgery driven by a voice-interactive artificial intelligence agent

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