Pre-Conference Workshop M4
M4 - Get the AI Tool for your Task - Refining a Taxonomy of Criteria for the Assessment of AI Tools in HE
Date Wednesday, 2 Dec Time – Price: 95.00 € Status: places available
Michael Dietrich
Senior Engineer, Educational Technology Lab, Deutsches Forschungszentrum für Künstliche Intelligenz
Michael Dietrich has been working in the field of technology-enhanced learning since 2001. He started as a research assistant and, after completing his graduation, became a full member of a research group at Saarland University. In 2012, he joined the Educational Technology Lab at the German Research Center for Artificial Intelligence (DFKI). Throughout his career, he has worked as an engineer on intelligent tutoring systems for mathematics, physics, chemistry, and medicine, as well as on health-related mobile applications for kindergarten staff. In addition, he has contributed to projects focusing on performance support and knowledge application for industrial shop-floor environments.
Sheikh Faisal Rashid
Professor of Artificial Intelligence, International University of Applied Sciences (IU)
Dr. Sheikh Faisal Rashid is a Professor of Artificial Intelligence at the International University of Applied Sciences (IU) and a Senior Researcher and Project Lead at the Educational Technology Lab, German Research Centre for Artificial Intelligence (DFKI), Berlin. He holds a Ph.D. in Computer Science specializing in machine learning, with over 15 years of experience in academia and industry. His research focuses on supervised machine learning, generative AI, and responsible AI applications in healthcare and education. Dr. Rashid has authored around 40 publications in leading conferences and journals and received international recognition, including a Best Paper Award and first prize at ICDAR 2013. He also serves as Vice President of the Pakistan Pattern Recognition Society (PPRS) and was a professional member of the ACM.
Miloš Kravčík
Senior Researcher Educational Technology Lab (EdTec), German Research Center for Artificial Intelligence (DFKI)
Dr Miloš Kravčík is a Senior Researcher at the Educational Technology Lab (EdTec) of the German Research Center for Artificial Intelligence (DFKI) in Berlin. His research focuses on learning technologies, particularly personalised and adaptive solutions in university and workplace settings. He has successfully acquired funding for, and contributed to, several EU and national projects. These have included projects focusing on developing adaptive learning environments and tools for self-regulated learning, as well as solutions that support personalised competence development, scalable mentoring, and psychomotor training. Dr Kravčík is the editor of various conference and workshop proceedings as well as the author of numerous publications, articles and book chapters.
Alexander Zimmermann
Technical Support and Software Development , DFKI Berlin
Alexander does technical support and software development at DFKI Berlin. He is interested in AI technology and finding new applications for it.
With the rapidly growing number of AI tools available, how can universities identify which tools are actually suitable for specific educational and administrative tasks? This interactive workshop introduces a taxonomy of criteria developed to support the systematic assessment and comparison of AI tools in higher education.
Participants will explore how the taxonomy was developed, examine a selection of AI tools already reviewed through the project, and gain insight into the underlying evaluation process. They will then work in groups to review AI tools and apply the criteria in practice, using their own experience and perspectives to assess how useful and meaningful the framework is.
A central part of the workshop will be the critical discussion of the taxonomy itself. Participants will identify strengths and weaknesses, consider which criteria and feature groups matter most, and highlight aspects that are missing, unclear or insufficiently detailed. The workshop will also explore how the taxonomy and evaluation approach could be adapted to other contexts, including companies and public administration. Participants will contribute to refining a practical framework while exchanging perspectives with researchers and practitioners working with AI in higher education.
The workshop will be conducted by researchers from the Education Technology Lab, which is part of the Deutsches Forschungszentrum für Künstliche Intelligenz GmbH (DFKI) in Berlin.
Agenda:
- Welcome & Project Framing (25 min)
- Exploring the Taxonomy & Evaluation Process (30 min)
- Reviewed AI Tools & Assessment Examples (25 min)
- Coffee Break (10 min)
- Hands-on: Reviewing AI Tools in Groups (35 min)
- Refining the Taxonomy: Strengths, Gaps & Priorities (45 min)
- Wrap-up (10 min)
Target Audience: Higher Education Leaders, Educators, Researchers, Learning Designers, Educational Technology Professionals, University Administration and Digital Learning Professionals
Target Audience Sector: Higher Education
Prerequisite Knowledge: Some prior experience with AI tools or digital technologies in higher education. Participants do not need prior knowledge of the taxonomy or its evaluation methodology.
Expected Outcomes:
- Understand the purpose and structure of a taxonomy for assessing AI tools in higher education.
- Apply evaluation criteria to assess AI tools against specific educational or administrative needs.
- Identify strengths, weaknesses and gaps in the current taxonomy.
- Contribute practical insights to refine and extend the evaluation framework.
- Explore how the taxonomy could be adapted to other contexts, including companies and public administration.