THEME: How Does AI Affect Group Work? – Insights from DMJX

The results were presented at TAL2025, showing that AI is often used without critical reflection, which can challenge the pedagogical principles of collaboration.

Pedagogical Framework

Teaching at DMJX is based on reflective practice learning, which emphasizes collaboration, dialogue, and the integration of personal experience. But how does AI fit into this framework? The study reveals that students see both benefits—such as idea generation, text summarization, and proofreading—and concerns: that AI may reduce learning opportunities or be used uncritically by peers. When AI becomes a “stowaway” in group work, it affect collaboration without the teacher’s awareness.

Activities and Initial Experiences

The study also found that students rarely discuss how and why they use AI in group work. Consequently, the focus has shifted to developing classroom activities that foster reflection and strengthen students’ AI literacy—the ability to use, evaluate, and discuss AI, including its ethical aspects. Three activities have therefore been tested during study start to support the development of AI literacy and make AI a conscious element in group work.

• Activity 1: A shared starting point with a quiz on basic knowledge of language models, followed by a review of DMJX’s guidelines and tools. Participants then exchange experiences, opinions, and their understanding of AI.
• Activity 2: A prompt workshop where students collaboratively experiment and learn the key principles of crafting effective prompts.
• Activity 3: Collaboration and group contract. Based on a set of illustrations, students discuss the possible roles and partnerships of genAI. These reflections are then incorporated into the development of their group contracts, which are then shared on a digital whiteboard.

Preliminary evaluations show that the activities create dialogue and reflection, but the long-term effect has not yet been measured.

Reflections

AI is not just a tool—it is an active participant in problem-solving. Therefore, the presenters emphasize the importance of helping students move from basic familiarity to critical and ethical use of AI. They highlight the following practical activities that can be applied in most teaching contexts:

• Facilitating structured reflections and collaborative agreements on AI use in projects and group work
• Experimenting with prompts that position AI as a sparring partner, including for groups in project work