The Logical Reconstruction and Path Exploration of the Vitality of Ideological and Political Theory Courses in the Era of Artificial Intelligence

Abstract

Artificial intelligence (AI), exemplified by large-scale models, is reshaping the educational landscape and accelerating the transition from digitalization to intelligent transformation. Ideological and Political (IP) courses face both new opportunities and emerging risks. Anchored in value orientation and educational principles, this paper traces the historical logic of change and identifies key structural challenges: attention dispersion, algorithmic enclosure, and capacity mismatch. We propose a three-dimensional framework of influence. First, a cognitive shift from indoctrination and rote memorization to problem-driven, evidence-based, and reflective learning. Second, a discursive shift from one-way transmission to multi-source co-construction with explicit value interpretation. Third, a relational shift from knowledge mediation to value leadership, instructional design, and data stewardship. Building on this framework, we outline practical pathways for intelligent content iteration, immersive experiences combined with rational debriefing, personalized support grounded in integrity safeguards, and renewed teacher professionalism for human–machine collaboration. Finally, we propose an institutional architecture emphasizing value guidance, collaborative mechanisms, shared resource ecosystems, digital–ethical literacy for teachers, and proportionate data governance. We argue that only through coupling value rationality with technical rationality, under transparent and auditable safeguards, can IP courses enhance their ideological depth, emotional resonance, and practical effectiveness.