Building foundational AI literacy for every child

Andrew Sliwinski, Vice President and Head of Product Experience at LEGO® Education, answers questions about computer science and artificial intelligence (AI) instruction in the classroom and what we can do now to empower student agency in a changing world

Education systems across Europe and beyond are rushing to integrate AI into classrooms, motivated by the promise of personalized learning and improving outcomes. There is real potential here, and this ambition is welcome. But in our haste to apply AI to children—optimizing instruction, automating assessment, accelerating content delivery— we risk overlooking a parallel and equally urgent priority: equipping children with a fundamental understanding of how these technologies actually work.

The current “gold rush” to improve learning outcomes through AI (which, it should be noted, remains largely unproven at scale) must be balanced with a sustained investment in foundational AI literacy. If we get this balance right, we have an extraordinary opportunity: a generation of children who don’t just use AI but also understand it well enough to build a better future with it.

Q: What is the single biggest misconception about AI education we need to overcome?

The prevailing misconception is that AI education simply means using AI on children—deploying adaptive tutoring systems, AI-generated lesson plans, or chatbot-driven instruction to optimize the existing model. That is one dimension, but it is incomplete. In our obsession with what computers can do, we have lost track of what children are capable of.

One narrative in education right now frames AI as a tidal wave coming to wash away human relevance, and our job is to frantically teach children how to tread water. This perspective casts the child as a passive participants of progress rather than its primary architect. We need to balance “using AI on children” with “children using AI” and more critically understanding how it works and how it doesn’t.

AI is not magic … it is technology. And foundational AI literacy is not about teaching children how to use a “magic box.” It is about handing them a screwdriver to take the box apart and build things from the pieces. This is not a novel idea—decades of research consistently demonstrate that children develop deeper understanding when they build, test, and reflect on tangible artifacts rather than passively receive instruction.

When we talk to children, we find they don’t just want to learn how to use AI. They want to understand it, and they want to build things with it for their communities, their friends, and their families. They also have remarkably clear ideas about how AI should and should not be used in the classroom and in society more broadly.

Q: Why should governments and education ministries elevate computer science and AI from niche electives to core literacy?

If we want children to build the future of these technologies (and not merely consume them), then they need to understand how they work and what they can build with them. The structural foundations of AI (i.e., computer science, probability, data, sensing, and algorithmic bias) should not be elective luxuries reserved for a select few. These concepts must be elevated to the status of a new literacy, as fundamental to a modern education as reading, numeracy, problem-solving, creativity, and collaboration.

This is not just about workforce preparation or national competitiveness (although those matter). It is about ensuring that the next generation has the knowledge, skills, and agency to lead, design, and critique the systems that will shape their lives. We must stop preparing children for a world where they are secondary to AI. Instead, we should provide them with the foundational tools and literacies required to be its primary architects.

Q: What steps should governments take to make this a reality?

This is, perhaps, a once-in-a-generation opportunity. Governments can use AI to prop up the existing system (e.g., marking the same tests faster, writing the same reports more efficiently) or they can recognize this moment for what it is: the single greatest opportunity in our lifetimes to reimagine education. That starts with investment in AI literacy at scale, backed by national policy and funding that elevates computer science, data literacy, and computational thinking to the same level as reading and numeracy. But it also requires a more fundamental shift in pedagogy.

We need to support educators and students through an inclusive, guided pedagogy that creates space for children’s curiosity. Many educators and parents feel ill-equipped to guide children through the complexities of AI, even as many of them are already exposed to AI tools. Nearly half of all computer science teachers do not feel confident teaching AI even after training, according to a LEGO Education survey of computer science teachers.

We cannot wait for adult expertise to catch up to the speed of innovation. Instead, we can reframe our role from all-knowing experts to partners in learning. After all, one of the most powerful things you can say to a child is, “I don’t know. Let’s find out together.”

Q: How can schools address the skills gap and encourage more interest in STEM careers?

The answer is empowerment and engagement. For too long, computer science has been perceived as a subject for a narrow subset of children—the “nerds” and the “geeks.” We need to change that narrative by connecting these tools to the things children genuinely care about: their passions, their interests, and their communities.

Everything we know from decades of education research and practice tells us that children learn most effectively when they are actively engaged, when they can connect their learning to their interests and passions, and when they learn together. Hands-on, project-based, and collaborative learning are the most effective methods to engage all learners.

They also happen to be the most effective methods we have to support children’s understanding of these concepts. When a child builds a physical model and sees it come to life because of the code they wrote or the AI model they trained, computer science stops being abstract and starts being tangible. We need every child to engage with these topics and feel a part of it—not just as future software engineers, but also as future artists, innovators, scientists, and citizens.

Q: How does hands-on learning foster critical thinking and the foundational understanding necessary for innovation?

A substantial body of international research supports the connection between active, hands-on pedagogies and the development of higher-order thinking skills. The OECD’s multi-year project on Fostering and Assessing Creativity and Critical Thinking found that when students are encouraged to come up with their own solutions and iterate on their ideas, they connect more deeply with subject matter and are more likely to develop durable creative and critical thinking capacities.

UNICEF’s Policy Guidance on AI for Children further emphasizes the importance of child-centered AI design that promotes agency and active participation, rather than positioning children as passive recipients of algorithmic instruction. These findings are consistent with broader constructionist research showing that when learners build, test, and reflect on tangible artifacts, they develop not only technical competence but also the metacognitive skills essential for innovation such as the ability to decompose problems, reason about uncertainty, and evaluate the assumptions embedded in the systems around them.

Q: What does successful teacher training and continuous professional development (CPD) in AI literacy look like?

The challenge is not just access to tools but access to confidence. Research consistently shows that teacher self-efficacy is one of the strongest predictors of effective technology integration in classrooms. Less than half of computer science specialist educators currently feel prepared to bring AI topics into their teaching,(1) and this confidence gap is the bottleneck.

Effective CPD must go beyond one-off technical workshops. It requires sustained, curriculum-embedded professional learning that positions teachers as co-learners alongside their students. The OECD’s professional learning framework for creativity and critical thinking emphasizes that lasting change in teaching practice depends on experiential, cooperative, and applied models of learning, not passive instruction.

Teachers need ready-to-use, curriculum-aligned content, and the scaffolding to build their own understanding progressively. When teachers feel confident, students become confident. Closing the confidence gap is not a secondary priority; it is a prerequisite for everything else.

Q: How does LEGO Education Computer Science & AI meet high standards for safety, privacy, equality, and well-being?

Our approach is anchored in three non-negotiable commitments. First is prioritizing privacy. At the LEGO® Group, we believe privacy is a fundamental right, and that right extends fully to children. At LEGO Education we guarantee this through what is called “local inference,” meaning no data from a child ever leaves the classroom. No data is transmitted across the internet to us or any third party and is never used to train AI models.

Second, we do not anthropomorphize AI. We do not give AI systems a face, a name, or describe them as “creative.” Creativity is for humans. Creativity is for children. Research shows that anthropomorphism can lead to a range of cognitive, behavioral, and emotional side effects, including children forming parasocial attachments to AI systems and substituting those interactions for real human relationships.

Third is transparency: the models children interact with are accompanied by clear documentation (e.g., model cards) describing the data used to train them and the biases they may contain. If we want children to understand how these tools work at a fundamental level, then we need to show them—not hide behind proprietary black boxes.

The question before policymakers, educators, and industry leaders is not whether AI will transform education—it already is. The question is whether we will use this moment to simply optimize the systems we already have or to truly empower children and shift towards more effective pedagogy.

If we want children to build a better future, then we need to equip them with the skills and mindsets to do so. Image what’s possible if we equip them with the foundational literacies to understand how AI works, the creative confidence to build with it, and the critical judgement to know when and how it should be used.

More than ever, we need children learning together, not staring at screens in isolation. And we need their voices heard, their curiosity honored, and their agency placed at the center of every decision we make. The children are ready. The question is, are we?

1. “US Computer Science & AI Education Insights Report | LEGO® Education” LEGO® Education, 2026