PREPARING FUTURE ELEMENTARY SCHOOL TEACHERS FOR THE AI ERA: THE ROLE OF ARTIFICIAL INTELLIGENCE LITERACY, DIGITAL PEDAGOGICAL COMPETENCE, AND SELF-EFFICACY IN TEACHING READINESS

Abstract

The rapid diffusion of artificial intelligence (AI) into everyday classroom practice has repositioned the competencies that elementary teacher education must cultivate in pre-service teachers. This narrative review synthesizes recent empirical and conceptual literature (2017–2026) on three interrelated constructs that shape prospective elementary teachers' readiness to teach in AI-mediated classrooms: artificial intelligence literacy, digital pedagogical competence, and self-efficacy. Sources were retrieved from Scopus-indexed and Web of Science-indexed journals, Frontiers, ScienceDirect, Taylor & Francis, Springer, and official policy documents from UNESCO and the European Commission, then organized thematically rather than through a systematic protocol. The review shows that AI literacy is increasingly conceptualized as a multidimensional construct spanning technical understanding, ethical judgment, and pedagogical application, yet most instruments and interventions still target secondary or general higher-education populations rather than elementary-specific contexts. Digital pedagogical competence, framed through the Technological Pedagogical Content Knowledge (TPACK) and DigCompEdu models, correlates strongly with technology-related self-efficacy among pre-service teachers, and self-efficacy itself functions as a recurring mediator between AI exposure and teaching readiness. The synthesis proposes an integrated conceptual pathway in which AI literacy and digital pedagogical competence jointly feed self-efficacy beliefs, which in turn determine willingness to enact AI-supported instruction in elementary classrooms. The review concludes with implications for teacher-education curricula and identifies the scarcity of elementary-specific, longitudinal, and non-Western evidence as priorities for future research.