The 2025 edition of the IEEE Global Engineering Education Conference (EDUCON), hosted at Queen Mary University of London, was a flagship international event that brought together a diverse community of educators, researchers, industry leaders, and policymakers to advance innovation in engineering and technology education. Here, Kennedy Offor shares his insights into the evolving role of critical thinking in engineering education in the age of generative AI, from stakeholder simulation to ethical decision-making and the future of professional skills.
I recently had the opportunity to participate and present in EDUCON 2025 at the Queen Mary University of London, a timely and thought-provoking event exploring the intersections of critical thinking, generative AI, and engineering education. My contribution focused on how generative AI can be leveraged to simulate stakeholder perspectives in engineering design, with a view to enhancing critical thinking and learner agency. But perhaps the most valuable part of the conference was the rich dialogue sparked by keynotes, panels, roundtables and the technical/special sessions and workshops—each raising questions we must now ask more boldly across our institutions.
This theme resonated deeply with my own work, where I’ve explored using AI to simulate stakeholder perspectives in engineering design. When used reflectively, AI can help learners ask better questions, test ideas, and examine multiple perspectives—especially if scaffolded by CT frameworks like Facione’s [4]. But as Wegerif argued, the goal isn’t to replace thinking, but to enrich it through generative, critical conversation—with machines and with ourselves.
Interestingly, Ahmed also noted that a healthy scepticism of AI tools is now seen as a core professional trait. With automation increasing, it’s no longer enough to use AI—we need to question it. This aligns with emerging research on cognitive offloading and the risks of overreliance, particularly in higher education. AI isn’t dumbing us down—but it can, if used without reflective judgement.
I recently had the opportunity to participate and present in EDUCON 2025 at the Queen Mary University of London, a timely and thought-provoking event exploring the intersections of critical thinking, generative AI, and engineering education. My contribution focused on how generative AI can be leveraged to simulate stakeholder perspectives in engineering design, with a view to enhancing critical thinking and learner agency. But perhaps the most valuable part of the conference was the rich dialogue sparked by keynotes, panels, roundtables and the technical/special sessions and workshops—each raising questions we must now ask more boldly across our institutions.
Rethinking Critical Thinking In the Age of GenAI
Critical thinking (CT) was a recurring theme across the technical and general sessions—not as a generic skill, but as a layered, intentional practice. What stood out to me was how the rise of Generative AI is reshaping the way we approach CT in engineering education. GenAI opens opportunities to foster CT—not replace it. When students use tools like ChatGPT to explore complex problems, they’re not just seeking answers. They’re engaging in a process that requires them to assess the quality of the output, challenge inaccuracies, prompt with precision, and navigate ambiguity. In other words, GenAI becomes both a mirror and a medium for thinking more critically.
One framework presented during the conference was combining mindset, emotional intelligence, and professional identity within engineering content. GenAI can support this when used deliberately: by prompting Socratic dialogue, enabling reflective self-assessment, or simulating multiple perspectives in ethical dilemmas. Rather than fearing automation, we’re invited to cultivate the critical habits needed to use these tools responsibly and thoughtfully.
Dialogue, AI, and Co-Intelligence
One of the highlights of the event was Professor Rupert Wegerif’s keynote on how education should respond to generative AI. He challenged us to see education as dialogue—not just between people, but between humans and technology [1, 2, 3]. His vision of “co-intelligence” invited a different kind of question: What if AI isn’t just a tool, but a partner in the thinking process?
This theme resonated deeply with my own work, where I’ve explored using AI to simulate stakeholder perspectives in engineering design. When used reflectively, AI can help learners ask better questions, test ideas, and examine multiple perspectives—especially if scaffolded by CT frameworks like Facione’s [4]. But as Wegerif argued, the goal isn’t to replace thinking, but to enrich it through generative, critical conversation—with machines and with ourselves.Industry Needs and Future Skills
Tahir Ahmed from Nokia added an industry perspective that grounded the pedagogical themes in real-world expectations. The gap between graduate readiness and industry requirements remains wide—not just in technical areas like 5G, IoT, and cybersecurity, but in so-called “power skills”: curiosity, communication, and complex problem-solving. Critical thinking came up again here—not as a nice-to-have, but as a vital workplace skill.
Interestingly, Ahmed also noted that a healthy scepticism of AI tools is now seen as a core professional trait. With automation increasing, it’s no longer enough to use AI—we need to question it. This aligns with emerging research on cognitive offloading and the risks of overreliance, particularly in higher education. AI isn’t dumbing us down—but it can, if used without reflective judgement.Ethics, Sustainability, and Engineering Culture
Another standout keynote for me was from Professor Susan Lord, who spoke powerfully about integrating ethics into electrical engineering education — especially in ways that students can relate to. One thing that really struck me is the concept of conflict minerals — raw materials like those used in semiconductors that are mined from conflict zones such as the Democratic Republic of Congo (DRC) [5]. It hit me how using real-world issues like this in the classroom can make students reflect more deeply on their actions and responsibilities.
She also pointed out how engineering culture often carries terms and images that many of us have just accepted without question — like using slave/master terminology in computer networking or the image of a woman called Lena in image processing. I hadn’t thought about how these seemingly small things could reinforce bigger issues around inclusion and representation, but now it feels obvious.
Her talk was a strong reminder that engineering education shouldn’t just prepare us for jobs — it should also prepare us to think critically and act responsibly. It made me reflect on how important it is to connect what we learn in theory to the actual impact our work can have in the world.
Looking Ahead
The final roundtable was focussed on what many were thinking: the “Eleph-AI-nt” in the room. As generative AI transforms both education and industry, we must collectively rethink what learning looks like—and what it’s for. The conversation left me hopeful. Not because we have all the answers, but because we’re finally asking the right questions—together.
Attending this conference was both affirming and challenging. It confirmed the relevance of my ongoing work on stakeholder engagement and AI in engineering education, but also pushed me to think more deeply about the frameworks and values we bring to the classroom. As the boundaries between human and machine thinking continue to blur, one thing remains clear: we need more dialogue, not less.
References
- Mercer, N., Hennessy, S., & Warwick, P. (2019). Dialogue, thinking together and digital technology in the classroom: Some educational implications of a continuing line of inquiry. International Journal of Educational Research, 97, 187–199.
- Wegerif, R., & Major, L. (2024). The theory of educational technology: Towards a dialogic foundation for design. Routledge. https://www.routledge.com/The-Theory-of-Educational-Technology-Towards-a-Dialogic-Foundation-for-Design/Wegerif-Major/p/book/9781032056371. https://www.taylorfrancis.com/books/mono/10.4324/9781003198499/theory-educational-technology-rupert-wegerif-louis-major. https://ebookcentral.proquest.com/lib/sheffield/detail.action?docID=30853266.
- Kershner, R., Hennessy, S., Wegerif, R., & Ahmed, A. (2020). Research Methods for Educational Dialogue. Bloomsbury Academic.
- Facione, P. A. (1990). Critical Thinking: A Statement of Expert Consensus for Purposes of Educational Assessment and Instruction. The Delphi Report. Millbrae, CA: The California Academic Press. https://files.eric.ed.gov/fulltext/ED315423.pdf
- M. Susan, J. E. Mitchell. (2025). Ethical issues in electronic and electrical engineering. Routledge. https://doi.org/10.4324/9781003464259-20.