AI literacy has become a core skill for both teachers and students. Knowing how to use AI tools is no longer enough. What truly matters is understanding how these systems work, how they shape information, and how to engage with them responsibly.
As I mentioned in a previous post, AI literacy doesn’t exist in isolation. It connects with other essential literacies such as media literacy, data literacy, computational thinking, and digital citizenship. Together, these literacies form the foundation for thoughtful participation in an AI-driven world.
Each plays a role in helping learners navigate digital spaces. Media literacy helps students recognize bias and understand how messages are constructed. Data literacy teaches them to read and question the numbers that drive decisions. Computational thinking encourages them to break down problems logically and understand the algorithms that power modern tools. Digital citizenship keeps the focus on responsible use, privacy, and respect for others online.
And if you are like me adhering to the socio-constructivist approach, then you would also view AI literacy as a socially and culturally situated practice, one that is context dependent and shaped by the interactions, norms, and values of the community where it develops.
Learning about AI happens through dialogue, collaboration, and reflection. Students make meaning together, not just by reading about AI, but by using it, questioning it, and seeing how it fits within their own worlds.
Where to Start Learning About AI Literacy
If you’re wondering where to begin your own exploration of AI literacy, the following guides and frameworks are excellent starting points. They provide practical perspectives for educators, policymakers, and anyone interested in understanding how AI intersects with teaching and learning:
- UNESCO (2024). AI Competency Framework for Teachers. https://doi.org/10.54675/ZJTE2084
- UNESCO (2024). AI Competency Framework for Students. https://doi.org/10.54675/JKJB9835
- OECD (2025). Empowering Learners for the Age of AI: An AI Literacy Framework. https://ailiteracyframework.org
- Digital Promise (2024). AI Literacy: A Framework to Understand, Evaluate, and Use Emerging Technology. https://doi.org/10.51388/20.500.12265/218
- CSTA & AI4K12 (2025). AI Learning Priorities for All K-12 Students. https://csteachers.org/ai-priorities.
- Digital Education Council (2025). DEC AI Literacy Framework: AI Literacy for All. https://www.digitaleducationcouncil.com/post/digital-education-council-ai-literacy-framework
- UNESCO (2021). AI and Education: Guidance for Policy-makers. https://doi.org/10.54675/PCSP7350
- UNESCO (2025). AI and the Future of Education: Disruptions, Dilemmas and Directions. https://doi.org/10.54675/KECK1261
- U.S. Department of Education (2023). Artificial Intelligence and the Future of Teaching and Learning: Insights and Recommendations. https://www2.ed.gov/documents/ai-report/ai-report.pdf
- Smith, J.M. et al. (2025). A Guide to AI in Schools: Perspectives for the Perplexed (MIT). https://tsl.mit.edu/ai-guidebook/
- UNESCO (2023). “Guidance for generative AI in education and research”. https://doi.org/10.54675/EWZM9535
These resources offer more than definitions or policy outlines—they help build awareness, agency, and ethical judgment in working with AI. Each framework brings a slightly different lens, but together they encourage educators to approach AI with curiosity, critical reflection, and a sense of shared responsibility.
In the end, developing AI literacy is about cultivating understanding, not compliance. It’s about helping teachers and students engage thoughtfully with the technologies that shape their learning and their future.
