AI literacy and subject specialization in pre-service teacher education: a mixed-methods study of dimensional profiles and perceived pedagogical challenges

Abstract

Artificial intelligence (AI) literacy has become an important component of teacher preparation, yet limited evidence is available on pre-service teachers’ self-reported AI literacy profiles and the challenges they perceive in connecting AI-related awareness with pedagogical practice. This study examined self-reported AI literacy and perceived pedagogical challenges among pre-service primary teachers using an explanatory sequential mixed-methods design. Survey data were collected from 161 third-year students in a university-based primary teacher education program in Central China, followed by semi-structured interviews with nine purposively selected participants. The study used a theoretically informed four-dimensional framework comprising AI Perception, AI Knowledge and Skills, AI Application and Innovation, and AI Ethics. Quantitative results showed a moderately high overall level of self-reported AI literacy, with AI Perception and AI Ethics slightly higher than AI Knowledge and Skills and AI Application and Innovation. Mathematics students reported higher self-rated scores than Chinese and English students across all four dimensions in this sample. The qualitative findings provided possible contextual interpretations of these survey patterns by highlighting participants’ perceptions of disciplinary alignment, unequal AI-related learning opportunities, limited subject-specific pedagogical support, and insufficient practicum-based experience. Participants recognized general ethical concerns but reported uncertainty about applying ethical principles to specific classroom situations.