Integrating Generative Artificial Intelligence into Practical Teaching of Ideological and Political Education in Chinese Universities: Pathways, Challenges, and Pedagogical Strategies

Abstract

With the iterative upgrading and widespread application of Generative Artificial Intelligence (GenAI), the educational ecosystem is undergoing a profound digital transformation. Leveraging advanced technologies such as deep learning, natural language processing, and computer vision, GenAI can not only construct highly simulated teaching scenarios but also plan personalised learning pathways through precise data analysis. In the practical teaching of Ideological and Political Education (IPE) in Chinese universities, this technological empowerment serves as a key variable for optimising teaching supply and innovating pedagogical models, as well as a digital carrier for guiding students to establish correct worldviews, life values, and political beliefs. It plays an important role in enhancing students' comprehensive quality and moral cultivation. In the new era, facing long-standing problems in traditional IPE practical teaching—such as limited time and space, single resources, and insufficient interaction—only by deeply exploring learning pathways and teaching strategies adapted to the intelligent era can we truly achieve a shift from "passive acceptance" to "active construction", allowing university IPE to gain new vitality and vigour through adhering to principles while innovating, and providing solid support for cultivating new generations capable of undertaking the great task of national rejuvenation.