AI Literacy Framework: What Every Educator Needs to Know Now

96% of older teens use AI weekly for learning, highlighting why an AI literacy framework is crucial for all educators right now.

In this episode:

• A 2025 survey by the European Commission and OECD revealed 96% of older teens use AI for learning weekly, underscoring the urgent need for an AI literacy framework.
• The AI literacy framework (AILit) from the European Commission and OECD defines four core domains: Engage with AI, Create with AI, Manage with AI, and Shape AI, guiding educators on teaching AI literacy.
• Effective teaching AI literacy means students understand AI's impact, critically evaluate outputs for bias, and make ethical choices, rather than just using AI tools.
• The 'Engage with AI' domain suggests activities like having students evaluate AI-generated historical summaries for accuracy and bias, fostering critical thinking skills.
• Educators must empower students to 'Shape AI' by investigating its ethical and environmental impacts, moving beyond consumption to proposing responsible design changes.

Chapters:

• 00:00 — Cold open & welcome
• 00:30 — Why an AI Literacy Framework is crucial for primary and secondary AI education
• 01:30 — Understanding AI literacy beyond tool usage: Outsourcing doing, not thinking
• 02:45 — Domain 1: Engage with AI – Critical evaluation in history lessons
• 03:45 — Domain 2: Create with AI – Using AI for imaginative exploration in art
• 04:45 — Domain 3: Manage with AI – Strategic delegation and human judgment in science
• 05:45 — Domain 4: Shape AI – Empowering students to influence AI's future and ethics
• 07:15 — The critical need for educator AI guidance and teacher support
• 08:15 — The AILit Framework as a roadmap for reflective and responsible learners

What is the AI Literacy Framework for primary and secondary education?
It's a joint initiative from the European Commission and the OECD designed to equip learners with the knowledge, skills, and attitudes to understand, critically evaluate, and ethically use AI systems, focusing on four domains: Engage, Create, Manage, and Shape AI.

How can teachers use AI marking safely and effectively in the classroom?
The framework suggests using AI to outsource 'doing' tasks like summarizing or organizing data, while teachers and students retain responsibility for critical thinking, interpretation, and drawing unique conclusions, ensuring AI enhances rather than replaces learning.

Why is teaching AI literacy important for young students?
It's vital because 96% of older teens already use AI weekly for learning, and this framework helps ensure they develop reflective awareness, critical judgment, and ethical considerations, preventing over-reliance that could diminish independent reasoning and social skills.

Featuring: Dan Fitzpatrick, OECD, European Union, European Commission, PISA Governing Board, CodeAI, AILit Framework, EU AI Act, Digital Education Action Plan 2021-2027.

Follow AI in Education with Dan Fitzpatrick for more on AI in education.

Transcript

SPEAKER_00 0:00

If this episode makes you think, please let us know in the comments and support us by subscribing and leaving a review. Thank you. Today we are exploring a really insightful document called Empowering Learners for the Age of AI, an AI literacy framework for primary and secondary education. This is a joint initiative from the European Commission and the Organization for Economic Cooperation and Development, the OECD. And what's particularly striking right off the bat is what they found about our young people's engagement with AI. A 2025 survey of European teens revealed that a staggering 88% of younger teens, those aged 13 to 15, and an even higher 96% of older teens aged 16 to 18, are using AI tools for learning and creative tasks at least a couple of times every single week. That's almost universal usage, isn't it? It really sets the stage for why this kind of AI literacy framework is so incredibly vital right now. This isn't just a casual observation either. It's a robust report supported by Code AI and a whole host of international experts, and it feeds into the PISA 2029 Media and Artificial Intelligence Literacy, or male assessment. So we're talking about a significant globally aligned effort here, rooted in policy frameworks from UNESCO, UNICEF and the World Bank, to name just a few. It really highlights that this isn't some niche educational concern. It's a global imperative. Now the report makes a crucial distinction right at the beginning, one that I often talk about. AI literacy is not just about using AI tools. It goes so much deeper than that. What the authors argue is that AI literacy is a blend of knowledge, skills, and attitudes that really equip learners to understand how AI systems work, to critically evaluate what they produce, and crucially to use them both ethically and creatively. Think about your students for a moment. Are they just clicking buttons or are they truly engaging their minds with these powerful new capabilities? This framework really resonates with my core philosophy that AI should be about enhancement, not replacement. It's about keeping the human in the loop, outsourcing the doing but absolutely not outsourcing the thinking. And this report backs that up, suggesting that without proper guidance, learners might lean on AI in ways that really diminish their reflection, their persistence or then or their independent reasoning. They even found, according to Common Sense Media, that many teenagers are seeing AI companions as replacements for human social interactions, which raises some serious questions about the impact on social skills and cognitive development. Machines can compute, but they cannot wonder and they certainly cannot care in the way a human can. So teaching students not to outsmart machines, but to outthink them becomes an urgent educational goal. This AI literacy framework proposes four core domains, kind of a journey for learners. It starts with engage with AI, then moves to create with AI and manage AI, which often happen in parallel and finally culminates in shape AI. These aren't just buzzwords, they represent a thoughtful progression of competence. So let's break down the first one. First we have engage with AI. This is the foundational domain really, all about becoming a critical and responsible participant in a world full of AI. It's about being able to recognize AI's influence in all sorts of contexts, from smart home devices to social media algorithms. The report gives some brilliant examples for the classroom. Imagine a year seven history lesson where students are given an AI generated summary of a historical event. Their task isn't just to read it, but to evaluate whether that output should be accepted, revised, or outright rejected. They'd be checking for accuracy, for relevance, for potential bias, by comparing it to trusted sources and their own understanding of the historical context. That's active learning, that's critical thinking, and it's a brilliant way to build AI literacy without getting bogged down in the technical minutiae. It's about developing that reflective awareness of AI's influence. The second thing teachers should know is about create with AI. This domain positions learners as imaginative creators, using AI not to replace their creative visions, but to realize them, to explore new ideas, to prototype and to iterate. This aligns perfectly with my view on design and learning that cannot be faked, because it demands depth, care, and imagination. Think about a primary school art class. Instead of just drawing a character, children could use an AI image generator to explore different visual representations for a story they're writing, perhaps for a year four English class. They can generate multiple ideas, compare how different prompts yield varied interpretations, and then use that as inspiration for their own drawings or models, reflecting on how their idea grew or changed with the AI. It encourages productive struggle, but with an intelligent partner, and they learn about ownership, originality, and intellectual property along the way, crucial ethical conversations for the age of AI. Here's what this means for school leaders and for all educators thinking about manage with AI. This domain is about intentional decision making, carefully considering how work is delegated between humans and AI tools. It's truly outsourcing the doing, not the thinking. Imagine a year ten science fair project. Students break down the complex research task into component parts. AI might be used to summarize initial research papers or help organize data, the doing. But the students remain responsible for designing the experiment, interpreting the results, drawing conclusions, and presenting their unique insights, the thinking and human judgment. The focus here is on purposeful scaffolding, making sure the AI enhances the learning process, deepening understanding, rather than just delivering answers. This also connects to the discussion in the framework about distinguishing between rule-based AI and machine learning, and deciding which approach is best suited for a given problem. If you're finding these insights helpful, make sure you hit that follow or subscribe button wherever you're listening, so you don't miss out on future episodes about AI in education. The final domain, and arguably the most ambitious for primary and secondary education, is Shape AI. This is where learners move beyond just using AI to understand and its technical underpinnings and even proposing improvements. It's about empowering young people to see that they can shape technology to reflect human values, not just be shaped by it. It compels them to move beyond being passive consumers to becoming responsible creators. This aligns perfectly with my call to teach students not to outsmart machines, but to outthink them. Think about a Year 12 computing or even a humanities class. Students could investigate the environmental impact of training large language models. The report explicitly raises this, noting the energy, mineral and water resources required. They could then research greener alternatives or propose design changes to an AI system that better serves human well-being or addresses a local environmental problem. This is about critical judgment, about understanding who benefits and who might be harmed, and making deliberate choices about how technology is developed and deployed. It's fostering that capacity for creativity and for holding the complexity. The report highlights something else that really struck me, the critical role of teachers and the overwhelming need for support. A Flash Eurobarometer survey found that 81% of European citizens agree that all teachers should be equipped with the skills to use and understand AI, including generative AI. Yet according to the OECD's TALIS 2024 survey, only about one in three teachers uses AI, and three out of four report lacking the knowledge and skills to teach using AI. This is not about resistance. It's about needing time and space, as I often say. Give teachers that, and they become the best drivers of innovation. We need to invest in professional learning that goes beyond just tool use, focusing on appropriate pedagogies for ethical reflection and student agency. This is an evolution, not a revolution, and it requires careful, deliberate leadership. Ultimately this AI literacy framework from the OECD and the European Union gives us a fantastic roadmap. It reminds us that AI literacy isn't just about technical know-how. It's about developing reflective, responsible, curious, innovative, adaptable, and empathetic learners. It's about equipping them to navigate an increasingly complex world where AI is interwoven into everything, ensuring they maintain their human judgment, their wonder, and their capacity to care. That's AI literacy, the compass, guiding us and our students through this incredible technological landscape. That's all for today, thanks for listening.