Mapping Teacher Competencies for Artificial Intelligence Integration in Elementary Literacy Learning

Abstract

The rapid emergence of generative Artificial Intelligence (AI) has opened considerable opportunities for transforming literacy instruction in elementary schools, yet its successful adoption is contingent upon teachers' competence in using it pedagogically, critically, and ethically. This study aims to map the dimensions of elementary school teachers' competence in utilizing AI for literacy learning, identify the forms of AI utilization and implementation challenges encountered, and propose an integrative conceptual model as the novelty contribution of this review. A Systematic Literature Review (SLR) was conducted following the PRISMA procedure across six databases (Scopus, ScienceDirect, Taylor & Francis, Google Scholar, DOAJ, and Garuda/SINTA), yielding 28 eligible articles published between 2020 and 2026, supplemented by relevant comparative studies from Jurnal Elementaria Edukasia. The findings indicate that teacher competence comprises four interrelated dimensions: conceptual knowledge of AI, technical pedagogical skills for integrating AI into reading and writing activities, critical evaluation of AI generated outputs, and ethical awareness in AI use. This study proposes a new conceptual model that integrates the Technological Pedagogical Content Knowledge (TPACK) framework with the AI literacy framework, positioning the four dimensions as reinforcing layers surrounding the conventional TPACK core. Key challenges include limited continuous training, digital infrastructure gaps, risks of student over reliance on AI, and insufficient supportive policies at the school level. This study recommends strengthening teacher professional development programs that are reflective, contextual, and grounded in the proposed TPACK AI literacy model, rather than focusing merely on technical tool mastery.