Technological Embodiment and Value Return: The Logical Path of Generative AI Empowering Scenario-based Teaching in University Ideological and Political Courses

Abstract

In the deep water zone of digital transformation in education, Generative Artificial Intelligence (Generative AI), with its powerful content generation capabilities, multimodal interaction characteristics, and human-like logical reasoning abilities, provides a new technological embodiment field for the reform of scenario-based teaching in university ideological and political theory courses (Civics Courses). Traditional teaching in these courses often faces a rupture between abstract theory and concrete experience. Generative AI, by constructing immersive, interactive, and generative teaching scenarios, realizes a cognitive shift from "disembodied" knowledge to "embodied" knowledge. However, the deep embedding of technology also triggers ethical risks such as algorithmic bias, information cocoons, and the alienation of subjectivity, posing severe challenges to the value-leading function of ideological and political education. Based on the perspectives of technological phenomenology and Marxist humanism, this paper deeply analyzes the internal mechanism of Generative AI empowering scenario-based teaching in Civics Courses, dialectically examines the dilemma of "technological overreach" it may encounter, and explores practical paths for unifying technological empowerment with the essence of education from three dimensions: the reshaping of subjects through human-machine synergy, the ethical regulation of algorithmic governance, and the return of value rationality. This aims to provide theoretical support and action reference for the high-quality development of university ideological and political courses in the new era.