Affordances and Constraints of Generative AI in Reforming University Ideological and Political Education

Generative Artificial Intelligence (GAI) represents a cutting-edge achievement of the digital intelligence technology revolution. Its disruptive impact is prompting a growing recognition of the necessity to rethink the methods of ideological and political education and learning in higher education institutions. However, there is still a lack of in-depth exploration into fundamental theoretical issues, such as the internal mechanisms through which GAI empowers teaching in ideological and political courses. Therefore, from the perspective of affordance theory, this paper critically analyzes the technological affordances and constraints of integrating artificial intelligence with ideological and political courses in higher education. It examines the internal mechanisms by which information technologies, such as generative artificial intelligence, drive transformation, and seeks practical pathways for integrating GAI technology into the teaching of ideological and political theory courses in schools. In summary, the empowerment of ideological and political course teaching reform by GAI presents both opportunities and challenges. It is essential to fully assess the dual nature of this new technology, enhance its empowering affordances, and prevent or mitigate the risks and challenges posed by its constraints.