Nurun Nahar

This study addresses the impact of Artificial Intelligence (AI) in Higher Education Institutions (HEIs) and the whole institutional approach undertaken to develop an AI literacy framework for students in a UK HEI. Drawing upon established models of AI literacy developed for higher education, informed by Leavitt’s People, Process, and Technology model (1965), and grounded in pedagogic theories, the study synthesises principles that address the interplay between emerging technologies, institutional resources, and learner needs. An analysis of existing AI literacy frameworks revealed a gap in terms of aligning institutional readiness, AI literacy and learner needs. To bridge this gap, this study proposes a conceptual AI literacy framework that is learner centred. It integrates practical knowledge and competencies to enable students to
confidently collaborate with AI systems for academic and professional development. Using a mixed-methods study approach and a convergent parallel design, primary data was collected using a survey (n = 110) and two focus groups (combined n = 63) involving multi-ethnic students to capture their perspectives on AI usage. A thematic analysis of secondary literature on AI literacy frameworks was undertaken along with a survey of academic staff (n = 66) to understand the relevance of incorporating AI literacy within curriculum. The resulting framework takes a four-step approach to cultivating AI literacy in higher education students: (i) prepare (ii) understand (iii) apply and (iv) responsible use. This conceptual framework is anticipated to offer a scalable, robust model that will help guide any HEI to cultivate adaptive learners prepared to responsibly navigate and innovate in an AI-driven world.