Reimagining Under-Resourced African Schools through AI: Pedagogical Transformation and Teacher Adaptability

Abstract

The introduction of Artificial Intelligence (AI) in the education sector is changing the teaching and learning process, although the effects on schools with limited resources, especially those in Africa, are under-researched. The paper is a review of the literature regarding AI-driven tools, including adaptive learning systems, intelligent tutoring, and automated assessment tools, and how they can support teaching and learning practices in socio-economically disadvantaged educational contexts. The structural barriers, such as digital inequity, inadequate infrastructure, and inadequate training of teachers, are discussed. Research indicates that AI may be used to personalize education, decrease the workload on administration, and differentiate instruction, but the feasibility of implementation depends on the digital skills of the teacher and their professional growth, as well as the support of the institution. The strategic suggestions include context-specific AI implementation, teacher education investment, and inclusive digital infrastructure development. This paper demonstrates that the proper implementation of AI in under-resourced educational environments is necessary and should be equitable and sustainable.