AI literacy and STEM education: emerging frontiers and research priorities

Abstract

Abstract This article examines the state of the art in AI literacy and STEM education and identifies emerging frontiers and research priorities to inspire cutting-edge empirical and theoretical research. The reviewed research is grounded in established AI literacy frameworks and shows that there is potential for students’ development of a critical and technologically informed AI literacy. However, the research is unevenly spread across the STEM disciplines and the potential for AI to transform STEM learning remains unclear. Thus, while the field has expanded rapidly, particularly with the emergence of generative AI (GenAI), fundamental challenges remain. The conceptual ambiguity surrounding AI literacy, combined with the rapid evolution of AI technologies, demands continued theoretical refinement and empirical investigation. Critical questions remain regarding how AI literacy intersects with disciplinary STEM literacies, how GenAI tools both support and reshape teaching and learning processes, and what opportunities and trade-offs arise when students engage with AI as learning partner. The ethical dilemmas of AI integration, including bias, data privacy, and environmental sustainability, also warrant urgent attention. As STEM education increasingly engages with AI as both a subject of learning and a learning tool, future research must move beyond one-size-fits-all frameworks toward context-sensitive approaches that empower educators and learners to critically and responsibly engage with AI while preserving core STEM learning goals. This article highlights key research frontiers and priorities for advancing scholarship at the intersection of AI literacy and STEM education.