Integrating AI Literacy into Pre-Service Science Teacher Education in Colleges of Education in Plateau State, Nigeria: A Framework for Preparing Educators for AI-Mediated Classrooms

The rapid integration of artificial intelligence (AI) in global education necessitates a purposeful re-orientation of pre-service science teacher preparation. Despite growing policy momentum in Nigeria, Colleges of Education (COEs) in Plateau State remain ill-equipped to embed AI literacy into science teacher education curricula. This study aimed to (i) assess the current level of AI literacy integration in pre-service science teacher education in Plateau State COEs; (ii) identify institutional factors enabling or constraining AI literacy integration; and (iii) develop a contextualised framework for preparing pre-service science teachers for AI-mediated classrooms. Adopting a sequential explanatory mixed-methods design, the study surveyed 112 pre-service science teachers and 15 science education lecturers drawn from two accredited colleges of education in Plateau State using stratified random and purposive sampling. Data were collected through a validated AI Literacy Readiness Questionnaire (ALRQ; Cronbach's α = .87) and semi-structured interviews. Quantitative data were analysed using descriptive statistics and independent samples t-tests; qualitative data were analysed thematically. Findings reveal a critically low level of AI literacy readiness (M = 1.94, SD = 0.61) across all four domains examined. Four qualitative themes characterise institutional barriers: infrastructural inadequacy, lecturer unpreparedness, absence of policy directives, and curriculum rigidity. Prior digital training significantly predicted higher AI literacy among lecturers (d = 1.39). The proposed SAIL (Science-AI Literacy Integration) framework offers a structured, theoretically grounded, context-sensitive approach for embedding AI literacy across science education curricula in Nigerian colleges of education