Keywords
AI literacy
Education
Ethical AI
Digital transformation
How to Cite
Abstract
Purpose: This study explores how Artificial Intelligence (AI) is transforming education and proposes a multidimensional framework for AI literacy as a foundation for equitable and ethical integration of AI-driven learning models. It examines how AI can enhance personalization, inclusivity, and creativity while addressing the challenges of ethics, transparency, and bias in educational contexts.
Design/Methodology/Approach: The research employs a conceptual and exploratory design grounded in a systematic literature review, case study analysis, and examination of international policy frameworks such as UNESCO’s AI and Education: Guidance for Policymakers (2023). It synthesizes insights from educational technology, ethics, and digital literacy traditions to construct a three-dimensional model of AI literacy—functional, critical, and creative.
Findings: The study finds that AI literacy is essential to ensure responsible engagement with intelligent systems. Functional literacy enables effective use of AI tools; critical literacy fosters awareness of biases, limitations, and ethical implications; and creative literacy promotes collaboration with AI in innovation and problem-solving. Together, these dimensions empower learners and educators to act as reflective and active participants in the co-construction of knowledge.
Research Limitations/Implications: As a conceptual study, the framework requires empirical validation through classroom implementation and longitudinal evaluation. Future research should examine how AI literacy affects learning outcomes and democratic engagement.
Originality/Value: By integrating functional, critical, and creative dimensions, this paper positions AI literacy as a key competency for 21st-century education—bridging technological innovation with humanistic and ethical values.
References
Allington, D., Duffy, B., Wessely, S., Dhavan, N., & Rubin, J. (2020). Health-protective behaviour, social media, and misinformation during the COVID-19 pandemic. Psychological Medicine, 51(10), 1763–1769.
Buckingham, D. (2020). The Media Education Manifesto. Polity Press.
Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. IEEE Access, 8, 75264–75278.
European Commission. (2021). Coordinated Plan on Artificial Intelligence 2021 Review.
Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., ... & Vayena, E. (2018). AI4People—An ethical framework for a good AI society. Minds and Machines, 28(4), 689–707.
Gebru, T., Morgenstern, J., Vecchione, B., Vaughan, J. W., Wallach, H., Daumé, H., & Crawford, K. (2021). Datasheets for datasets. Communications of the ACM, 64(12), 86–92.
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. Center for Curriculum Redesign.
Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., Shum, S. B., & Santos, O. C. (2022). Ethics of AI in education: Towards a community-wide framework. International Journal of Artificial Intelligence in Education, 32(3), 525–560.
Lewandowsky, S., Ecker, U. K. H., & Cook, J. (2017). Beyond misinformation: Understanding and coping with the “post-truth” era. Journal of Applied Research in Memory and Cognition, 6(4), 353–369.
Long, D., & Magerko, B. (2020). What is AI literacy? Competencies and design considerations. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 1–16.
Luckin, R. (2017). Towards Artificial Intelligence-based Assessment Systems. Nature Human Behaviour, 1, 0028.
Ng, D. T. K. (2021). Artificial intelligence literacy: A multidimensional construct. Journal of Computer Assisted Learning, 37(4), 846–857.
OECD. (2021). AI in Education: Implementing Policy and Practice. Organisation for Economic Co-operation and Development.
O’Neil, C. (2016). Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Crown Publishing.
UNESCO. (2023). AI and Education: Guidance for Policymakers. Paris: UNESCO.
Voigt, P., & Von dem Bussche, A. (2017). The EU General Data Protection Regulation (GDPR): A Practical Guide. Springer.
Williamson, B., & Eynon, R. (2020). Historical threads, missing strands, and future patterns: Artificial intelligence in education lab. Learning, Media and Technology, 45(3), 223–235.
Zarocostas, J. (2020). How to fight an infodemic. The Lancet, 395(10225), 676.
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – where are the educators? International Journal of Educational Technology in Higher Education, 16, 39.
Zhang, K., Song, Y., Tan, W., & Zhu, Q. (2020). Smart education: AI applications in higher education. Journal of Educational Technology Development and Exchange, 13(2), 1–15.
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