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Keynote Lectures

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Lluís Vicent Safont, Universitat de Barcelona, Spain, Spain

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Mairead Pratschke, Mairead Pratschke Ltd, Ireland / London School of Economics and Political Science, United Kingdom, Ireland

Authentic Assessment in Computer Science: Projects, Teams, and Human Skills in (Online) CS Education
Thomas Staubitz, German University of Digital Science, Germany, Germany

 

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Lluís Vicent Safont
Universitat de Barcelona, Spain

 

Brief Bio
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Abstract
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Mairead Pratschke
Mairead Pratschke Ltd, Ireland / London School of Economics and Political Science, United Kingdom

 

Brief Bio
Professor B. Mairéad Pratschke is founder and principal of an independent advisory practice (Mairead Pratschke Ltd) working at the intersection of AI strategy, governance, design, and education. Her work is focused on designing future-ready learning systems that align human expertise with intelligent technologies. Mairéad works with governments, institutions, and organisations internationally to rethink learning models and lead systems-level change, aligning programmes and pedagogy with the future of work, learning, and society. Prof. Pratschke is the author of Generative AI and Education: Digital Pedagogies, Teaching Innovation and Learning Design (Springer, 2024); New Horizons for Higher Education: Teaching and Learning with Generative AI (NDLN, 2025); and a chapter in the forthcoming Handbook on Generative AI and Education: From Research to Practice (Springer, 2026). She is Visiting Professor at the London School of Economics and Political Science (LSE) Data Science Institute; External Advisory Board member and Research Fellow at the US National Science Foundation-funded AI Institute for Adult Education and Online Learning (AI-ALOE); and member of the Executive Committee (EC) for the AI-MetaACES conference series - the International Conference on Artificial Intelligence, Metaverse and Artificial Companions in Education and Society, one of the Theme-Based International Conference Series (TBICS) organised under the Asia-Pacific Society for Computers in Education (https://apsce.net/). Website: https://maireadpratschke.com/ LinkedIn: https://www.linkedin.com/in/maireadpratschke/


Abstract
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Authentic Assessment in Computer Science: Projects, Teams, and Human Skills in (Online) CS Education

Thomas Staubitz
German University of Digital Science, Germany

https://german-uds.de/
 

Brief Bio
Thomas Staubitz is Professor of Educational Technology and Social Learning at the German University of Digital Science. He teaches several online courses on software development to students with diverse academic backgrounds and varying levels of prior experience. He holds a bachelor’s and a master’s degree in International Media and Computer Science, as well as a doctorate in Internet Technologies and Systems. His research focus is on the delivery of such courses in a scalable way. Before joining the German University of Digital Science in 2024, he served as a Senior Lecturer at the Hasso Plattner Institute’s openHPI MOOC platform for over a decade. In this role, he was involved in a broad range of projects in collaboration with industry and public-sector partners, including SAP and the World Health Organization, as well as in publicly funded national and European research initiatives. At openHPI, he taught several MOOCs on Java programming and contributed to the design and production of numerous additional courses in collaboration with faculty members and students. Within this context, he also completed his doctoral dissertation on the assessment of team-based, gradable assignments in large-scale learning environments. His interest in online learning dates back to his undergraduate studies, where he worked on the development of an automated grading system for programming exercises. During his master’s studies, he worked on educational projects involving children in schools, including the production of radio plays using the XO laptop. Guided by the conviction that teaching is a powerful means of learning, he began teaching programming to diverse audiences while still completing his bachelor’s and master’s degrees. In addition to his teaching activities, he has held several roles in software development and product management and has published research on open online learning in international conferences and journals. He is a member of the Association for Computing Machinery (ACM), a Senior Member of the IEEE, a member of the ACM Learning@Scale and EMOOCs steering committees, and serves as a reviewer for multiple conferences and academic journals.


Abstract
Computer science education is undergoing a fundamental shift. With generative AI systems capable of producing code, explanations, and even full solutions, traditional assignments and assessments no longer reliably measure learning or understanding. This keynote argues that project-based learning and teamwork are no longer optional pedagogical choices, but central design principles for meaningful computer science education. Drawing on examples from teaching practice, the talk explores how to assess authentic projects, collaborative work, and processes in computer science classes. This is particularly challenging in online classes where learners are distributed all over the globe. The session addresses key challenges in the age of AI: assessing individual contribution within teams, evaluating learning when AI tools are ubiquitous, and designing assessments that reward understanding, judgment, and responsibility rather than mere code production. The talk concludes with design principles for rethinking computer science education—focusing on learning as a socio-technical process rather than a solitary technical task.



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