At ENHANCE, we believe the future of learning cannot wait until university. In our current ENHANCE+ project, the Future Learning Work Package, led by Universitat Politècnica de València, explores disruptive technologies and new pedagogical models for the learners of tomorrow. We spoke with Maria Alfonso Molina (Universitat Politècnica de València), WP Lead on Future Learning, and Anna Sibilska-Mroziewicz, researcher at Warsaw University of Technology, about a live experiment at the intersection of AI, storytelling, and early STEM education.
As part of local integration of the learnings within ENHANCE+ at Warsaw University of Technology, you are producing AI-generated educational videos on the history of computer science — for primary school children. Where does this fit within ENHANCE+'s broader mission?
MAM: The ENHANCE+ project reminds us that higher education cannot be a closed system. The Future Learning work package functions as a living laboratory: a space where partners dare to experiment, apply new methods, and turn every attempt into transferable knowledge. What the Warsaw team is doing lies at the very heart of what we wish to explore — whether it is possible to use the most disruptive technology of our time in the service of a clear, rigorous, and ethically conscious pedagogical intention.
ASM: Our work is a direct contribution to those goals. While many initiatives within the alliance focus on current university students, we are deliberately building a connection between higher education and much earlier stages of learning. Warsaw University of Technology students act as creators of educational content, under academic supervision — taking responsibility for designing didactic experiences for younger learners. This transforms students from knowledge consumers into knowledge creators, while also serving the broader mission of preparing future-ready citizens from an early age.
Why the history of computing, and why primary-age learners?
MAM: The history of computing is not a purely technical topic — it is the story of how the human mind learned to build artificial minds, and of the reasons why. That narrative has protagonists, ethical dilemmas, moments of failure, and moments of brilliance. It is precisely the kind of content capable of awakening in a child the awareness that technology does not simply fall from the sky: it is created by people, with purposes, values, and mistakes.
ASM: We want children to understand that technology does not appear out of nowhere. We also believe that children need a certain level of technological familiarity before engaging directly with AI systems — which is why our materials focus on the reception of thoughtfully designed, AI-assisted content rather than unmediated interaction with AI. We also see great value in intergenerational dialogue: students can serve as authentic bridges, bringing complex ideas in a language and tone that feels natural and engaging to younger audiences.
How does the production process work — how do pedagogy and AI tools relate to each other?
MAM: What interests me most is not the technological aspect, but the order in which decisions are made. First: what do we want the learner to understand? Which conceptual misunderstandings must we anticipate? Only afterwards do we ask: what can AI contribute, and where do its limitations oblige us to compensate through human judgement? This order is not a minor detail. It is the difference between using a tool and being used by it.
ASM: In our approach, pedagogy and responsibility always come before technology. Before using any AI tools, students — guided by academic teachers — first define the educational goals, anticipate possible misconceptions, and design the intended experience for the child. AI serves as a supporting tool, never as the decision-maker. Every element undergoes rigorous content and pedagogical verification. We want students to feel like real creators, not just operators of tools.
The first results are already in. Anna's team has produced narrative modules — short AI-generated videos on the history of logic and on key figures such as Ada Lovelace and Alan Turing — and is testing them with children in the ScienceQuest workshops, where AI and VR technologies are balanced with play, collaborative group work, and storytelling. Early findings are striking: children's responses to AI-generated educational content are highly polarised, ranging from strong enthusiasm to complete rejection. That complexity is itself a finding worth building on.
A recurring concern is that AI in education risks homogenising content and diminishing the teacher's role. How do you respond to that?
MAM: I am less concerned about the homogenisation of content than about the homogenisation of the relationship with knowledge. The great question is not "Will AI replace the teacher?" — which strikes me as poorly framed — but rather, "What kind of teacher does the age of AI require?" My answer: a more sophisticated teacher, more reflective, more capable of asking questions. AI can generate explanations. It cannot generate the question that disrupts a comfortable certainty, or the human relationship that makes knowledge personally meaningful.
ASM: In our model, the role of the teacher and academic mentor does not diminish — it becomes more important. Teachers guide the pedagogical design, ensure quality and context, and create space for reflection and dialogue. We see our work as strengthening, rather than replacing, the human dimension of education.
What would you say to institutional leaders developing frameworks for responsible AI use in education?
MAM: Do not legislate from a distance. Frameworks written without contact with real practice are, at best, useless and, at worst, harmful. What institutions need is a culture of reflective experimentation, not merely compliance protocols. And they need to make use of what ENHANCE offers in an almost unique way: a network of universities with shared values and distinct traditions, capable of generating collective knowledge that no single institution could produce alone.
ASM: Any responsible framework must recognise a fundamental truth: the safe and beneficial development of AI cannot be separated from education. These two processes must advance together. Education is not an afterthought to technological development — it is one of its essential conditions.
This is, ultimately, what the Future Learning work package is for: not to accumulate outputs, but to build the collective intelligence of the alliance about what it means to learn. The Warsaw initiative is one contribution to that construction — patient, rigorous, and honest about the questions it cannot yet answer. Which is exactly where good research begins.
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Watch the first short educational videos, co-created by the team at Warsaw Tech
Contact
María Alfonso Molina
Work Package Lead "Future Learning"
malfmol@upvnet.upv.es
Anna Sibilska-Mroziewicz
Warsaw University of Technology
anna.mroziewicz@pw.edu.pl
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