GAI-Enabled Primary School Ideological and Political Education: Prospects, Risks, and Pathways

Abstract

Generative Artificial Intelligence (GAI) is reshaping ideological and political education in primary schools by enabling dialogic inquiry, multimodal interaction, immersive simulation, and narrative assessment. While these capabilities support the construction of technology-enhanced moral learning models, they also introduce risks such as algorithmic bias, teacher role marginalization, experiential simplification, and emotional reductionism in evaluation. Grounded in theories of cognitive development and moral education, this study proposes a four-dimensional framework to mitigate these risks: (1) developing value-aligned adaptive models, (2) fostering human-machine teaching symbiosis, (3) designing integrated virtual-real learning contexts, and (4) implementing evidence-based growth narratives. The research offers both theoretical and practical pathways for leveraging GAI to enhance the quality and integrity of moral education in the digital age.