Conference

Effective Higher Education Despite(?) Artificial Intelligence

Four years after the release of ChatGPT, generative AI has become deeply embedded in higher education. From AI-assisted writing to emerging Vibe Coding, current discourse focuses on efficiency, productivity, advanced AI tool use, and prompt engineering. This raises a more fundamental question: Are we still fostering learning—or merely accelerating task completion while accepting gradual deskilling? This keynote argues that large language models’ responses should be understood as hypotheses. Meaningful learning requires students to critically analyze, falsify, and refine these hypotheses through scientific judgement. Accepting AI-generated output without this epistemic work risks bypassing the very mechanisms through which expertise develops.

Drawing on theoretical computer science, algorithmic learning theory, and inductive inference, the keynote presents learning as an iterative process of generating, analyzing, and falsifying hypotheses. Within this process, generative AI can become a valuable exploration partner—but only if learners remain responsible for defining learning objectives, solving problems, and extracting insights. Rather than celebrating or rejecting AI, the talk advocates a scientifically grounded approach to AI-supported education. Understanding the principles, conditions, and limitations of computation, learning, and verification is essential for effective higher education in the age of AI.

The speaker

Dr Oksana Arnold studied Technical Cybernetics and Automation at Leipzig University of Technology and earned her PhD in 1996 with a dissertation on a knowledge-based system architecture for therapy control of process engineering plants. The work received the 1997 Dissertation Prize from the Association of German AI Institutes. From 1997 to 2010, she worked for IBM Deutschland GmbH, where she applied her AI expertise as an IT architect in customer-specific solution design and delivery projects. She later assumed responsibility for medium and large-scale projects, serving in leadership roles including IBM Certified Executive Project Manager, Programme Manager for internet services for Deutsche Telekom, and head of several business service application departments. She received the IBM Global Services PM Excellence Award 2002 and is co-inventor of an IBM patent.

Since 2010, she has been Professor of Theoretical Computer Science and Artificial Intelligence in the Department of Applied Computer Science at the University of Applied Sciences Erfurt. Alongside her research and teaching in AI, she lectures in project management at master's level and has organized numerous AI4Kids courses, robotics children's universities, and media project weeks for school pupils in collaboration with students. Since 2015, she has served as a reviewer for AI and robotics projects at the Austrian Research Promotion Agency (FFG). Her research focuses on inductive learning methods, AI applications, and technology-enhanced learning, particularly exploratory and game-based learning. Her goal is to develop intelligent learning systems that combine human and machine capabilities through dialogue, drawing on language processing, inference methods, ai planning and machine learning. From 2016 to 2018, she coordinated the BMBF-funded collaborative project ODIN ("Open Data Innovation"), which explored web-based processing of heterogeneous data for exploratory knowledge analysis. Together with research partners, she received the Outstanding Paper Award at the 15th International e-Society Conference (2017) and the AI Prize of the German Federal Ministry of Labour and Social Affairs (2022). In 2026, she was appointed to a three-member expert commission established by the Voluntary Self-Regulation of Television (FSF) and the Voluntary Self-Regulation of Multimedia Service Providers (FSM), under the supervision of the Commission for the Protection of Minors in the Media (KJM), to develop quality standards for automated and AI-supported assessment systems.

AI ± Education: Transformation, Tension, and Opportunity

Will artificial intelligence (AI) transform teaching, learning, and assessment in schools and higher education? As AI capabilities continue to expand at an unprecedented pace, educational institutions face urgent questions about their pedagogical models, assessment practices, and the competencies graduates will need in the AI era. Drawing on current research, educational practice, and emerging policies, this keynote examines the challenges and opportunities of AI for learners, educators, and institutions. It argues that educational systems need to move beyond the hype and fear of AI to responsibly, persistently, creatively, and ethically develop learners’ human intelligence in an AI-enabled future.

The speaker

Demetrios Sampson is a Professor of Digital Systems for Learning and Education in the Department of Digital Systems at the University of Piraeus, Greece. He is also the Director of the Master of Science (MSc) Program in Digital Learning and the Director of the Research Laboratory for Digital Systems in Learning and Education. He serves as the Vice-President of the Governance Committee of the Public Onassis Schools, a Network of 22 Public Schools supported by the Onassis Foundation through a €160 million grant. Previously, he was a Professor of Learning Technologies and Director of Research at the School of Education, Curtin University, Australia. He has held visiting academic roles at 8 universities across 4 continents. He is the co-author of 320+ research publications with 11.600+ citations (h-index 52) in Google Scholar. His research in Learning Technologies and Digital Education has achieved significant international impact. He has been included on Stanford University's list of the World's Top 2% Scientists since 2022 based on Scopus data. He has served as the Chair and Vice-Chair of the IEEE Computer Society Technical Committee on Learning Technology for 18 years and the Editor-in-Chief of the Educational Technology and Society Journal. He is the recipient of the IEEE Computer Society Distinguished Service Award (July 2012) and was named a Golden Core Member of the IEEE Computer Society in recognition of his contributions to the field of Learning Technologies. Professor Sampson is the recipient of the Golden Nikola Tesla Chain Award of the International Society for Engineering Pedagogy (IGIP), awarded in September 2018 in recognition of my internationally outstanding achievements in the field of Engineering Pedagogy.