Artificial Intelligence Integration in Teacher Education: Institutional Readiness and Curriculum Pathways in a Fourth Industrial Revolution Context
TL;DR
The findings indicate that AI integration extends beyond technological adoption and requires coordinated curriculum transformation, institutional preparedness, and pedagogical redesign, and that institutional readiness, particularly in terms of infrastructure, faculty capacity, and curriculum alignment, is a critical determinant of implementation.
Abstract
Despite growing global interest in Artificial Intelligence (AI) in education, limited empirical research has examined how teacher education institutions in developing-country and resource-constrained contexts can sustainably integrate AI into their curricula. This gap is particularly significant because many existing AI integration frameworks assume levels of technological infrastructure, institutional capacity, and digital readiness that may not reflect the realities of higher education institutions in the Global South. Against this backdrop, this study explored institutional readiness, curriculum integration pathways, and implementation strategies for Artificial Intelligence within teacher education programmes in Namibia. Guided by an interpretivist paradigm, a qualitative exploratory design was employed, using semi-structured interviews with 25 teacher educators across six university campuses. Data were analysed thematically using Braun and Clarke’s framework. The findings indicate that AI integration extends beyond technological adoption and requires coordinated curriculum transformation, institutional preparedness, and pedagogical redesign. Key integration pathways include embedding AI within faculty courses, curriculum-wide integration of AI competencies, simulation-based learning, and support for online teaching environments. Institutional readiness, particularly in terms of infrastructure, faculty capacity, and curriculum alignment, emerged as a critical determinant of implementation. While participants highlighted benefits such as improved instructional efficiency, enhanced teacher capacity, and increased learner autonomy, they also expressed concerns regarding overreliance on technology. By integrating Diffusion of Innovation (DOI) and the Technology Acceptance Model (TAM), this study advances a multi-level framework linking institutional and individual dimensions of AI adoption in teacher education. This study contributes context-specific insights to AI curriculum transformation in the Global South and provides practical implications for curriculum design, institutional strategy, and policy development.