人工智能技术赋能高校课程思政建设的路径探析

Path Analysis of Empowering Curriculum-Based Ideological and Political Education in University Courses with Artificial Intelligence Technology

摘要: 在人工智能技术深度变革教育生态的背景下，本文针对高校课程思政建设中普遍存在的内容同质化、资源更新滞后、教学互动缺失等问题，提出以人工智能技术赋能课程思政数智化转型的实践路径。通过自然语言处理技术实现思政元素的精准提取，依托知识图谱构建动态化、结构化的课程思政案例库，利用机器学习技术优化课堂互动与学情分析，推动课程思政教学向个性化、精准化转型。研究同时指出需警惕技术应用中的价值导向风险、数据安全隐患及教师数智素养不足等挑战，强调通过深化“技术逻辑”与“育人逻辑”的融合，构建智能技术、教学内容、育人目标三位一体的创新范式，为提升高校课程思政育人实效提供理论支持与实践参考。

Abstract: Against the backdrop of Artificial Intelligence technology profoundly transforming the educational ecosystem, this paper addresses common issues in the development of curriculum-based ideological and political education, such as content homogenization, outdated resources, and lack of teaching interaction. It proposes practical pathways for empowering the digital and intelligent transformation of curriculum-based ideological and political education using AI technology. Specifically, Natural Language Processing technology is leveraged to achieve precise extraction of ideological and political elements. Knowledge graphs are employed to construct dynamic and structured repositories of case studies. Machine learning techniques are utilized to optimize classroom interaction and learning analytics, thereby driving the transformation of curriculum-based ideological and political teaching towards personalization and precision. The study also highlights challenges requiring vigilance, including risks to value orientation in technology application, data security concerns, and insufficient digital literacy among educators. It emphasizes the need to deepen the integration of “technological logic” and “educational logic”, advocating for the construction of an innovative paradigm that unites intelligent technology, teaching content, and educational objectives. This approach aims to provide theoretical support and practical references for enhancing the educational effectiveness of curriculum-based ideological and political education in university courses.