Research on the Construction and Application Effectiveness of an AI-Empowered Smart Teaching Model for Ideological and Political Theory Courses in Universities

Abstract

: The deep integration of artificial intelligence technology with ideological and political theory courses in universities has created new technological conditions for addressing such problems in traditional classrooms as imprecise identification of students’ learning conditions, insufficient matching of teaching resources, limited depth of student participation, and delayed evaluation and feedback. Based on the fundamental task of fostering virtue through education in university ideological and political theory courses, this study focuses on five key elements: teaching objectives, intelligent resources, classroom activities, learning data, and evaluation feedback. It constructs a smart teaching model consisting of six interconnected stages: “precise diagnosis—intelligent learning guidance—contextual inquiry—collaborative analysis—data-based evaluation—feedback and improvement.” The responsibilities and functional boundaries of teachers, students, and intelligent platforms are further clarified across the pre-class, in-class, and post-class stages. Practical application shows that artificial intelligence can improve the precision of resource allocation, the quality of classroom interaction, and the continuity of learning evaluation in ideological and political theory courses. However, its effective application still requires adherence to the principles of teacher leadership, value guidance, data security, and appropriate use of technology, so as to establish a smart teaching mechanism that coordinates technological empowerment with the principles of education.