Smaller and Smarter: Trends in Education
Carlos Delgado, Universidad Carlos III de Madrid, Spain
From Stochastic Parrots to Synergistic Partners: Opportunities, Challenges, and the Way Forward
Mutlu Cukurova, UCL Knowledge Lab Institute of Education University College London, United Kingdom
Smaller and Smarter: Trends in Education
Carlos Delgado
Universidad Carlos III de Madrid
Spain
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Brief Bio
Carlos Delgado Kloos received the Ph.D. degree in Computer Science from the Technische Universität München and in Telecommunications Engineering from the Universidad Politécnica de Madrid. He is Full Professor of Telematics Engineering and Rector’s Delegate for Digital Microcredentials at Universidad Carlos III de Madrid, where he is also the Director of the GAST research group and Director of the UNESCO Chair on “Scalable Digital Education for All”. Previously, he has been Vice Rector for Strategy and Digital Education, Vice Rector for Infrastructures and Environment, Associate Vice Rector for International Relations and Cooperation, and Founding Head of his Department. He has carried out research stays at several universities such as Harvard, MIT, Munich, Passau, and Naples.
His main research interests are in Educational Technology. He has been involved in a large number of research projects and has published more than 500 papers (h-index 56 on Google Scholar). He has coordinated several MOOCs on edX and MiríadaX with around 700,000 registrations. He is presently promoting the adoption of digital micro-credentials in Spain through the project CertiDigital (certidigital.es) and has also recently recorded a MOOC about AI for Teaching and Learning (federica.eu/esplorare-ia).
From Stochastic Parrots to Synergistic Partners: Opportunities, Challenges, and the Way Forward
Mutlu Cukurova
UCL Knowledge Lab Institute of Education University College London
United Kingdom
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Brief Bio
Mutlu Cukurova is a Professor of Learning and Artificial Intelligence at University College London. Prof. Cukurova investigates human-AI complementarity in education, aiming to address the pressing socio-educational challenge of preparing people for a future with AI systems that will require a great deal more than the routine cognitive skills currently prized by many education systems and traditional approaches to automation with AI. He directs the UCLAIT team and leads the Design and Use of AI in Education course at UCL. In addition, he is engaged in policy-making activities as an external expert (including UNESCO, IAEA, and EU external expert groups and co-authored the UNESCO AI Competency Framework for Teachers). He was the programme co-chair of the International Conference of AI in Education in 2020 and CSEDU in 2022, is part of UCL's Grand Challenges on Transformative Technologies group, named in Stanford’s Top 2% Scientists List, Editor of the British Journal of Educational Technology and Associate Editor of the International Journal of Child-Computer Interaction.
Abstract
This talk explores the potential of artificial intelligence (AI) in education, focusing on its multifaceted conceptualisations as tools, cognitive models, and agents of human-AI hybrid intelligence [1]. Highlighting recent advancements in generative AI, the talk critically examines its promise and limitations in supporting both student learning and teacher practices. While AI presents some opportunities for task automation and learning-enhancement, it also raises critical concerns regarding human agency, ethical considerations, and systemic inequalities in education. Drawing on decades of research in AI and education, the talk emphasises the need to move beyond narrow applications of AI for productivity gains. Instead, it advocates for AI systems that augment human competence, foster lifelong learning skills, and align with broader societal values. Using examples from his own work on multimodal learning analytics and human-centred AI, Prof. Cukurova underscores the importance of designing educational systems that embed AI within intentional, evidence-informed, and human-centred pedagogical frameworks. The keynote concludes with a call for ecosystem-level innovation—spanning governance, teacher training, and assessment structures—to ensure that AI is not only a tool for automation but a catalyst for equitable, meaningful, and sustainable education. The talk invites CSEDU researchers to engage in a critical dialogue on redesigning pedagogy in the age of AI, rather than only focusing on the immediate micro-level concerns of the field.
Cukurova, M. (2024). The interplay of learning, analytics and artificial intelligence in education: A vision for hybrid intelligence. British Journal of Educational Technology, 1–20. https://doi.org/10.1111/bjet.13514