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Abstract
The integration of artificial intelligence (AI) into science, technology, engineering, and mathematics (STEM) education is transforming teaching methods worldwide. In Africa, this change presents major opportunities along with notable challenges. This conceptual paper critically explores the philosophical and critical perspectives of how AI can be incorporated into STEM curriculum design within African education systems to enhance teaching and learning outcomes. The paper adopts a dual-theory approach using the artificial intelligence technological pedagogical content knowledge (AI-TPACK) framework and Paulo Freire’s critical pedagogy theory. These frameworks guide the analysis of how AI can be aligned with curriculum goals, teaching strategies, and student needs, while ensuring ethical and culturally responsive integration. A conceptual and interpretive research design is foregrounded, supported by a narrative literature review, and is employed to generate theoretical insights rather than empirical findings. AI tools, including intelligent tutoring systems, adaptive learning platforms, automated assessment tools, and generative content applications, can personalize instruction, encourage problem-solving and critical thinking, and provide real-time feedback to both students and teachers. In environments characterized by overcrowded classrooms, limited educational resources, and unequal access to quality learning, AI offers scalable, data-driven approaches to improve STEM education. By integrating AI, education systems can work toward reducing learning gaps and promoting the development of future-ready skills aligned with the needs of the 4th Industrial Revolution. The paper recommends the development of culturally relevant, inclusive, and ethically grounded strategies to guide AI integration in STEM education across Africa. These approaches should address infrastructural gaps, teacher capacity, and contextual diversity to prevent the reinforcement of educational inequities.
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Article Type: Research Article
EURASIA J Math Sci Tech Ed, Volume 22, Issue 5, May 2026, Article No: em2826
https://doi.org/10.29333/ejmste/18503
Publication date: 04 May 2026
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