Bridging Educational Gaps in Low-Resource Classrooms: AI-Enhanced Project-Based Learning for STEM Educators in Africa

Purpose This research examines the potential of Artificial Intelligence (AI)-Project-Based Learning (PBL) to enable science, technology, engineering, and mathematics (STEM) educators in resource-limited African classrooms to shift from content-centric teaching to competency-based learning (CBL). It seeks to ascertain how cost-effective AI tools can address deficiencies in teacher capacity, inclusivity, and digital accessibility. Design/Approach/Method Using a qualitative research design, data were collected from ten STEM educators across Nigeria, Botswana, Ghana, Namibia, and Sierra Leone through open-ended interviews, document analysis, observations, and analysis of participants’ project artefacts. The intervention involved hands-on engagement with speech-to-text-to-image generation, smartphone-based block coding using the Magnetcode application, circuit simulation, and microcontroller-based prototyping. Findings Thematic analysis revealed five outcomes: AI speech-to-text tools enhanced visualization of science concepts; smartphone-based coding increased inclusion; simulations provided cost-effective scaffolding for hardware use; educators gained transition skills in computational thinking; and participants developed concrete strategies for classroom integration. Originality/Value This study contributes novel empirical evidence from Sub-Saharan Africa, demonstrating that low-cost, AI-supported PBL can facilitate learner-entered pedagogy and equitable STEM innovation. It highlights AI as a transformative enabler for CBL, offering scalable models for sustainable, inclusive education in resource-constrained environments.