中国实用口腔科杂志

中国实用口腔科杂志 ›› 2026, Vol. 19 ›› Issue (2): 218-223.DOI: 10.19538/j.kq.2026.02.014

• 口腔医学教育研究专栏 • 上一篇    下一篇

生成式人工智能赋能转化医学导向的口腔颌面外科教学价值、挑战与策略初探

夏    亮a，于雯雯a，邹多宏b，杨    驰b，张志愿b   

  1. 上海交通大学医学院附属第九人民医院a口腔颅颌面科，b口腔外科；上海交通大学口腔医学院；国家口腔医学中心；国家口腔疾病临床医学研究中心；上海市口腔医学重点实验室；上海市口腔医学研究所，上海 200011
  • 出版日期:2026-03-30 发布日期:2026-03-30
  • 通讯作者: 邹多宏
  • 基金资助:
    国家自然科学基金（92368111）；国家重点研发计划项目（2024YFC2418600）；中央高校基本科研业务费专项（YG2024LC05）；上海交通大学医学院附属第九人民医院原创探索项目（JYYC007）；上海交通大学医学院附属第九人民医院交叉基金（JYJC202012）；上海市科技计划项目（24SF1905400）

  • Online:2026-03-30 Published:2026-03-30

摘要： 目的    调查并分析生成式人工智能（artificial intelligence generated content，AIGC）赋能转化医学导向的口腔颌面外科教学价值与挑战，初探相应的教学改革策略。方法    选取2025年上海交通大学口腔医学院全日制在读本科生（350名）、研究生（100名）及从事相关教学任务的教师（50名）共500名。采用匿名自填式问卷方式对AIGC赋能转化医学导向的口腔颌面外科教学认知维度进行调查，包括对AIGC的认知与使用评价、教学态度评价、教学需求与预期评价、教学建议与意见。其中，采用五级Likert量表方法对AIGC赋能教学态度及教学需求进行评分。结果    共发放问卷500份，回收有效问卷481份，问卷回收率为96.2%；其中，学生群体占90.0%（433/481），教师群体占10.0%（48/481）。95.8%（461/481）研究对象对AIGC有一定程度了解。学生群体对AIGC提升教学质量的态度评价为3.83 ~ 4.09分，教师群体为4.21分。学生群体在AIGC课程选修意愿方面评分较高（> 3.80分），所有研究对象在教学平台建设需求方面评分较高（3.75 ~ 4.24分）。对于是否担心AIGC影响教师教学地位方面，教师群体评分（2.60分）高于学生群体（1.62 ~ 2.05分）。在教学建议与意见评价中，存在AIGC技术成熟度有限、教师教学主导权边界模糊及伦理规范与数据安全等方面顾虑，需在规范与引导下审慎推进。针对AIGC辅助教学手段及教学平台建设功能方面，手术模拟（68.4%，329/481）、病例分析（65.3%，314/481）及智能考核反馈（60.1%，289/481）为主要需求，教师更关注临床决策支持（66.7%，32/48）与科研设计（72.9%，35/48），学生偏向个性化推荐（64.4%，279/433）与模拟训练（68.1%，295/433）；多数研究对象期望平台具备虚拟病例库（70.5%，339/481）、自动化评分系统（65.3%，314/481）及学习路径推荐功能（60.7%，292/481），教师对模拟操作记录分析功能（75.0%，36/48）需求较高，学生青睐语音交互问答功能（61.7%，267/433）。结论    AIGC赋能转化医学在口腔颌面外科教学中展现出较高的应用潜力与师生接受度，但在技术能力、教育主导性及伦理规范等方面仍面临挑战，需在完善规范体系与加强引导的基础上稳步推进。AIGC在口腔颌面外科教学中的应用需求明确且呈现群体差异，推动AIGC在口腔医学教育中的系统化与规范化应用，可为教学模式创新与优化提供有效路径。

关键词: 人工智能, 生成式人工智能, 口腔医学, 颌面外科, 转化医学, 教学改革

Abstract: Objective    To investigate and analyze the value and challenges of artificial intelligence generated content（AIGC）in empowering translational medicine-oriented oral and maxillofacial surgery education，and to preliminarily explore corresponding teaching reform strategies. Methods    A total of 500 participants were recruited in 2025 from the College of Stomatology，Shanghai Jiao Tong University，including full-time undergraduate students（n = 350），postgraduate students（n = 100），and faculty members engaged in related teaching tasks（n = 50）. An anonymous self-administered questionnaire was used to assess cognitive dimensions of AIGC-enabled translational medicine-oriented oral and maxillofacial surgery education，including cognition and usage of AIGC，attitudes toward AIGC-enabled teaching，teaching needs and expectations，and suggestions and concerns. A five-point Likert scale was applied to evaluate attitudes toward AIGC-enabled teaching and teaching needs. Results    Of the 500 questionnaires distributed，481 valid responses were collected with response rate of 96.2%，including 433 students（90.0%）and 48 teachers（10.0%）. Overall，95.8%（461/481）of respondents reported some understanding of AIGC. Students′ ratings for the role of AIGC in improving teaching quality ranged from 3.83 to 4.09，while teachers rated it 4.21. Students showed high willingness to enroll in AIGC-related courses（all > 3.80），and all respondents expressed strong demand for teaching platform development（3.75 - 4.24）. Teachers reported greater concern that AIGC might affect their teaching role （score：2.60） compared with students （1.62 - 2.05）. Respondents also expressed concerns regarding limited technological maturity，unclear boundaries of teaching leadership，and ethical and data security issues，which should be promoted with caution under standardization and guidance. Regarding AIGC-assisted teaching methods，the most demanded applications were surgical simulation （68.4%，329/481），case analysis（65.3%，314/481），and intelligent assessment and feedback （60.1%，289/481）. Teachers showed greater interest in clinical decision support（66.7%，32/48）and research design（72.9%，35/48），whereas students preferred personalized learning recommendations（64.4%，279/433）and simulation training（68.1%，295/433）. Concerning teaching platform functions，most respondents expected virtual case libraries（70.5%，339/481），automated scoring systems（65.3%，314/481），and learning pathway recommendation functions（60.7%，292/481）. Teachers demonstrated higher demand for simulation operation record analysis（75.0%，36/48），while students favored voice-interactive question-and-answer functions （61.7%，267/433）. Conclusion    AIGC demonstrates substantial potential and high acceptance among teachers and students in translational medicine-oriented oral and maxillofacial surgery education. However，challenges remain regarding technological capability，teaching leadership，and ethical governance，and its implementation should be advanced steadily through improved regulatory frameworks and enhanced guidance. The application needs of AIGC in oral and maxillofacial surgery education are clear and exhibit group-specific differences，suggesting that systematic and standardized application of AIGC in oral medical education may provide an effective pathway for optimizing and innovating teaching models.

Key words: artificial intelligence, artificial intelligence generated content, oral medicine, oral and maxillofacial surgery, translational medicine, teaching reform