Exploring AI in the VET Classroom: GenAI Makerlab Workshop in Teacher Education

By Stefanie Panke for AACE Review, August 11th 2025

Design Thinking, Making, and Serious Play are three distinct yet interrelated approaches to problem-solving, resilience and innovation that have gained increased traction in education over the past decade (Panke & Harth, 2023). How can these techniques be applied to nurturing and developing GenAI Literacy? At the end of June 2025, ten pre-service vocational education and training (VET) teachers gathered at the Muenster University of Applied Sciences for a two-day hands-on workshop that combined creativity, experimentation, and critical reflection on the role of generative AI in teaching.

The thematic focus was Vertretungsunterricht (substitution teaching)—a pressing reality in the daily life of vocational schools. Through structured activities, participants explored how generative AI tools can help teachers prepare for these situations: quickly creating relevant lesson materials, adapting content to different learning levels, and providing alternative modes of engagement. Equally important was the discussion of new problems AI can introduce into the classroom, such as over-reliance on machine-generated content, risks to academic integrity, and potential biases in AI output.

GenAI-Makerlab Setting

The GenAI-Makerlab workshop took place in a flexible learning space designed to encourage innovative strategies for the classroom. Participants could move between activities: recording a podcast episode, exploring LEGO Serious Play, tinkering with maker kits, and applying design thinking to real-world teaching challenges. The open layout and adaptable furniture created a collaborative, idea-rich environment.

From Preparation to Practice

Before the 2-day workshop, participants completed preparatory sessions and independent learning activities, including starting an AI journal to record and reflect their use of AI, and building a digital “toolbox” of playful, practical, and experimental genAI applications. In addition, students collected scenarios from their respective disciplines of both easy and challenging classroom settings for a substitute teacher. The shorter foundational sessions, conducted hybrid, in-person and on Zoom, helped ensure that the workshop days could focus on deeper exploration and problem-solving.

Lego Serious Play (LSP)

Lego Serious Play (LSP) is an open source moderation method that uses Lego bricks to facilitate strategic planning, team building, problem solving, and creative expression. Participants learned the principles of LSP, which ensures equal participation and fosters creative thinking. They followed the four-step process: Challenge, Build, Share, Reflect.

Warm-up task: Build a tower in five minutes and reflect on perspective and placement.
Main challenge: Create a model of a classroom situation in your subject area that would either be made possible or impossible through AI.

Ideation

Empathy and divergent thinking are crucial in the initial phase of the design process to encourage heterodox perspectives. We introduced students to two techniques and apllied these to generative AI:

Love-Letter / Breakup Letter: The love/breakup letter task allows participants to balance different perspectives in a personal way (Molinari & Gasparini, 2019). We asked students to express a stance toward AI from a teacher’s perspective by drafting a “love letter” or a “breakup message” to generative AI.
Crazy 8: In eight minutes, participants generated eight ideas for assignments that would engage students in reflective and transparent AI use.

Tackling a Core Challenge: Substitution Teaching

Each student was assigned a substitute teaching session in a subject outside their own area of expertise, which they had to transform into a lesson plan under time pressure using AI tools.

Agile Techniques

To foster collaboration, creativity, and iterative problem-solving, we incorporated agile, hands-on activities that encouraged participants to experiment, take risks, and adapt quickly.

Making: Maker pedagogy draws from core tenants in the maker movement, and is characterized by student agency, hands-on learning, a focus on practical application and personal meaning. Participants formed three groups and created different microbots (doodle-bot, brush bot, tooth brush bot). Microbots are simple robotic devices that use vibration from a small motor to move, often created from everyday materials and used for educational purposes to teach basic principles of physics and engineering. We also provided a MakeyMakey set with a more open-ended task (‘create anything’). Makey Makey is an invention kit that allows users to turn everyday objects into touchpads.
Marshmallow Challenge: Teams were given 20 spaghetti sticks, 1 marshmallow, 1 meter of string, and 1 meter of tape. The goal was to build the tallest freestanding tower capable of supporting the marshmallow at the top. This hands-on exercise fostered teamwork, rapid prototyping, and iterative problem-solving.

Design Thinking

Participants learned about Design Thinking as a playful, human-centered approach to solving complex (“wicked”) problems through analysis, synthesis, collaboration across disciplines, and rapid prototyping.

Working in design-client pairs with partners from different perspectives, participants tackled either: (1) A teaching problem created by AI, or (2) An innovation made possible by AI. Pairs exchanged ideas, provided feedback, and each ‘designer’ selected one idea to develop further, created a prototype, and presented their solutions to their partner.

Podcasting

We introduced podcasting as a medium for storytelling and sharing educational content. After an overview of the process of audio recording, cloud hosting, RSS feed creation, and distribution via podcast apps, we provided a group task. In MakerLab Podcast Teams, participants created a short episodes on topics such as: Future Teacher 2030: Skills for the AI Era, Substitute teaching: experiences as a student, expectations as a teacher, Beyond ChatGPT: Exploring the wider world of AI tools. As the final activity, this brought out participants creativity. It revealed in-depth genre knowledge of podcasting, and allowed teams to explore the use of AI for scripting and editing assistance.

Related Workshop Concepts & Results

Sullivan, McAuley, Degiorgio, and McLaughlan (2024) investigated the effectiveness of a brief, 90-minute workshop aimed at improving university students’ generative AI (genAI) literacy. The format significantly boosted students’ confidence, intentions to use AI, and understanding of relevant policies.

Our workshop concept extended these results : participants moved from general, non-specific ideas about AI to envisioning targeted, subject-specific uses that aligned with vocational education needs. In line with Sullivan et al. (2024), one ongoing challenge was developing robust strategies to critically evaluate AI-generated content—an area identified for continued training.

David, Krebs, and Rosenbaum (2023) investigated the use of generative artificial intelligence tools within a design thinking academic makeathon involving over 700 design and engineering students at Shenkar College of Engineering, Design and Art during a “jam week”. They found specific use patterns: Most students used GenAI as an assistive tool rather than a dictating one, primarily during research and empathy stages for information gathering. Text-based tools (e.g., ChatGPT) were used more than visual tools early in the process. The combined use of text and visual AI tools increased in the ideation and prototyping stages. Overall, students predominantly showed a pattern of surface-level, search-focused engagement with GenAI tools, with limited exploration of creative or interactive capabilities.

While David at el. (2023) focused on the potential of GenAI within DT workflows, we specifically wanted to use design thinking as a technique to approach the use of generative AI with a human-centered, creative and empowering stance. Our workshop focused on exploring the intersection of agile methods and generative AI in creative lesson preparation, particularly for substitute teaching scenarios. The goal was to practice participatory, innovative, iterative, and resilient approaches.

A Laboratory for Teacher Education

After the workshop, participants completed an online survey and took part in an oral exam, where they answered questions about the format and their individual learning experiences.

By combining hands-on experimentation, targeted AI literacy training, and critical discussion, the workshop created a living laboratory for the next generation of VET teachers. Participants left with not just new tools in their teaching repertoire, but a stronger sense of how—and when—to use AI responsibly and effectively in the vocational classroom.

References

David, Y., Krebs, A., & Rosenbaum, A. (2023). The use of generative AI tools in Design Thinking academic makeathon. CERN IdeaSquare Journal of Experimental Innovation, 7(3), 43-49.

Panke, S., & Harth, T. (2023). Design Thinking, Making and Serious Play: Similarities, Differences, and Workshop Concepts. International Journal for Educational Media and Technology, 17(2).

Sullivan, M., McAuley, M., Degiorgio, D., & McLaughlan, P. (2024). Improving students’ generative AI literacy: A single workshop can improve confidence and understanding. Journal of Applied Learning and Teaching, 7(2), 88-97.