AI赋能研究生病理学课程思政实践探索

Exploring the Integration of AI in Graduate Pathology Courses for Ideological and Political Education

摘要: 在新医科建设与研究生教育立德树人根本任务的双重驱动下，病理学作为连接基础医学与临床医学的桥梁学科，其课程思政建设是培养高层次医学人才的重要抓手。当前，研究生病理学课程普遍存在思政内容与科研临床实践衔接不紧、教学场景单一、育人成效难量化、个性化引导不足等现实问题。本文结合研究生培养的高阶性与个性化特点，探索以人工智能(Artificial Intelligence, AI)技术为支撑的病理学课程思政实践路径，通过搭建思政知识图谱与分层案例资源、拓展虚实结合的教学情境，将思政元素融入教学全过程，并建立全过程评价反馈机制，实现专业知识与思政育人的深度融合。实践表明，该模式有效增强了研究生的职业使命感、科研诚信意识和人文关怀能力，同时促进了教师育人能力的持续提升，为研究生病理学课程思政改革提供了可推广的实践参考。

Abstract: Driven by the dual imperatives of advancing the new medical education system and fulfilling the fundamental mission of fostering virtue through graduate education, pathology-bridging basic and clinical medicine-serves as a critical discipline for cultivating high-level medical talent. Current pathology courses for graduate students commonly face challenges such as disjointed integration of ideological-political content with research and clinical practice, relatively monotonous teaching scenarios, quantifiable difficulties in educational outcomes, and insufficient personalized guidance. This study explores an AI-supported pedagogical approach for ideological-political education in pathology, leveraging knowledge graphs and tiered case resources, expanding virtual-physical teaching scenarios, embedding ideological-political elements throughout the instructional process, and establishing a formative evaluation feedback mechanism to achieve deep integration of professional knowledge and ideological-political education. Practical results demonstrate enhanced sense of professional mission, research integrity awareness, and humanistic care capabilities among graduate students, alongside sustained improvement in faculty mentoring skills, providing a replicable model for pathology curriculum reform in graduate education.