Research on the Reconstruction of the Teaching Model for University Ideological and Political Theory Courses from the Perspective of Human-Computer Collaboration

Wenyan Tang

doi:10.30560/ier.v8n4p61

Wenyan Tang Nanning University, China

DOI: https://doi.org/10.30560/ier.v8n4p61

Keywords: Human-Computer Collaboration, Ideological and Political Theory Course, Teaching Model Reconstruction, Generative Artificial Intelligence, Digital Human Lecturing

Abstract

With the rapid development of generative artificial intelligence technology, the traditional teaching model for university ideological and political theory courses is facing a profound transformation. This study, based on human-computer collaboration theory and constructivist learning theory, and through in-depth investigation of teaching practices in universities such as Zhejiang University, constructs a teaching model for ideological and political courses that integrates digital human lecturing, AI-assisted learning, human-computer co-creation, and intelligent assessment. The study adopts a mixed-methods research approach to analyze the teaching experiment data of more than 5,000 students. The results show that this model can significantly increase student classroom participation by 30-50%, and 85% of students indicated that their learning interest was significantly enhanced. The study finds that the human-computer collaborative teaching model, through a deep integration of technological empowerment and value inheritance, effectively solves the problems existing in traditional ideological and political course teaching, such as theoretical abstraction, low participation, and insufficient personalization. However, the promotion and application of the model still face challenges such as technological maturity, faculty competence, and ethical risks, which need to be addressed through systematic policy support, capacity building, and collaborative innovation.

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