生成式人工智能时代高校思政课教学的挑战与创新

Challenges and Innovations in the Teaching of Ideological and Political Theory Courses in Colleges and Universities in the Era of Generative Artificial Intelligence

摘要: 生成式人工智能正在改变高校思政课教学的内容供给、互动方式与评价模式，同时也带来新的教学挑战，表现为教师主导地位弱化、教学内容质量失范、育人效能弥散以及伦理规范缺位。在此基础上，本文提出技术应用应坚持四项基本前提：教育性前提，即育人目标与技术应用的统一；主体性前提，即教师主导与学生能动的统一；发展性前提，即全面发展与素养提升的统一；规范性前提，即伦理约束与制度保障的统一。进而从创新路径角度提出，应以教师主导为核心构建人机协作教学新形态，以内容审核为重点建立技术过滤与教师把关机制，以三维融合为路径优化认知诊断与沉浸体验模式，以伦理制度为保障完善数据保护与算法透明体系。四者相互衔接，共同确保生成式人工智能在服务育人目标的前提下合理应用，为高校思政课教学创新提供参考。

Abstract: Generative artificial intelligence is transforming the content supply, interaction methods, and evaluation models of the teaching of ideological and political theory courses in colleges and universities, while also bringing new teaching challenges, manifested as the weakening of teachers’ leading role, anomie in the quality of teaching content, dissipation of educational effectiveness, and absence of ethical norms. On this basis, this paper proposes that the application of technology should adhere to four basic premises: the educational premise, namely the unity of educational goals and technological application; the subjectivity premise, namely the unity of teacher leadership and student agency; the developmental premise, namely the unity of comprehensive development and competency enhancement; and the normative premise, namely the unity of ethical constraints and institutional safeguards. Furthermore, from the perspective of innovation paths, it proposes that a new form of human–machine collaborative teaching should be built with teacher leadership at its core; a mechanism of technological filtering and teacher gatekeeping should be established with content review as the focus; cognitive diagnosis and immersive experience models should be optimized through three-dimensional integration; and systems for data protection and algorithmic transparency should be improved with ethical regulations as safeguards. These four aspects are interconnected, jointly ensuring the reasonable application of generative artificial intelligence on the premise of serving educational goals, and providing a reference for innovation in the teaching of ideological and political theory courses in colleges and universities.