12-11-2025 –, Spinoza foyer
Are you curious about how artificial intelligence (AI) can redefine education? Until now, AI has mainly supported existing practices, like automated grading or efficiencies in processes. But AI also has the potential to create entirely new learning environments and redefine the roles of educators, learners, and institutions. This workshop invites you to develop innovative teaching approaches that leverage AI as a catalyst for profound change in education. You will gain a deeper understanding of AI's transformative potential and brainstorming concepts that push beyond traditional methods. Use this space and join a short deep dive into the future of education and think along.
Are you thinking about how AI can shape the future of education? So far, AI and learning analytics in higher education have often focused on supporting established teaching and assessment practices, such as automated grading or process efficiencies (Bond et al., 2024). However, AI also offers the chance to create completely new learning environments and redefine the roles of educators, learners, and institutions. As Bozkurt et al. (2024) write in their Manifesto for Teaching and Learning in a Time of Generative AI:
“We must rethink the very nature of education, teaching, learning, and assessment in light of GenAI. GenAI could provide opportunities to move beyond a deterministic view of knowledge if, rather than expecting students to provide 'right answers', the focus shifts to the learning process, where GenAI may support personalized educational experiences” (p. 507).
This is also changing the role of universities, which are confronted with new questions about the role of education, their authority over the education they provide, the value of degrees and an increasingly rapid pace of technological change (Liu & Bates, 2025).
In this workshop, you will explore the transformative potential of AI in higher education. You will work together to develop innovative teaching approaches that use AI as a catalyst for change in education. The workshop consciously opens spaces to think outside the box while remaining practical and useful.
Session Structure:
The workshop is structured along four parts:
- Mindset Setting: What would you wish for education, if anything would be possible? (5 min)
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Input: Where do we currently stand and what would be possible? (8 min)
- Overview of the current use of AI in higher education
- Discussion of problematic applications and challenges
- Introduction to the potential of transformative approaches: How can AI rethink teaching and not just optimize it? What opportunities are there for innovative teaching and learning methods?
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Group work: Development of transformative AI concepts (25 min)
You work in small groups to develop and structure new concepts for the transformative use of AI in teaching. Possible topics are: AI as a co-lecturer, creative examination formats, AI-supported reflection processes, AI as a sparring partner (see also Bond et al, 2024 and Bozkurt et al., 2025). -
Round-up and Discussion (7 min)
The presentation of the group results is guided by the discussion on the questions:- Where is the line between support and real transformation through AI?
- What are the criteria for transformative AI teaching?
- What ethical implications need to be considered?
- What could be the next steps?
Expected Outcomes: After the workshop, you will have a deeper understanding of AI's transformative potential in higher education and concrete starting points for developing innovative teaching and learning concepts. These insights can serve as a basis for future scenarios of implementing AI-based teaching innovations.
Target Group: Are you a student, educator, IT manager, or educational leader interested in shaping AI in education and trying something new? Then this session is for you.
References:
Bond, M., et al. (2024). A meta systematic review of artificial intelligence in higher education: A call for increased ethics, collaboration, and rigour. International Journal of Educational Technology in Higher Education, 21(1), 4.
Bozkurt, A., et al. (2024). The Manifesto for Teaching and Learning in a Time of Generative AI: A Critical Collective Stance to Better Navigate the Future. Open Praxis, 16(4), pp. 487–513.
Liu, D., & Bates, S. (2025). Generative AI in higher education: Current practices and ways forward. Whitepaper von der Association of Pacific Rim Universities.