A: The aim was to demonstrate why genAI is (or is not) wrong regarding solving legal problems. This was intended to demonstrate to students that genAI can be used, but that its errors and limitations must be recognised. 

B: The aim was for students to understand what genAI can do and how to prompt in a legal context. At the same time, it provided an opportunity for active student involvement in the teaching. 

Out of the 4 principles for digitally supported learning, these are relevant:

Variation: 

A: AI helps me as a lecturer to more easily generate the variation that a case offers students. It also adds extra variation because we address AI’s own solution to the case. Highlighting that the case was created by AI is a new variant for students, which sparks their curiosity.

B: Variation is achieved by having the students prompt their own case, freeing them from PowerPoint presentations.

Co-determination and Empowerment: 

B: Although this is not project work, students themselves prompt a case based on their acquired knowledge, giving them co‑determination and empowerment to control and assess when AI has produced a satisfactory result. Additionally, they share each other's work and provide feedback.

(Du kan læse lidt om deres indhold nedenfor, og ellers kan du se mere her: https://www.iaspbl.aau.dk/projects/principles-for-digitally-supported-pbl)

1. Variation: Students are motivated and learn in different ways, which is the reason why variation can benefit all students in the form of multiple approaches to learning, lecturing, and education. In this context, the digital can help expand the scope of possibilities for education and support variation as a principle at multiple practical levels.
2. Collaboration and Openness: Digital technologies enable new types of collaboration that extend beyond the individual course or project work, making it easier to open up to other stakeholders, a larger number of participants, create cross-collaboration, or envision entirely new forms of cooperation.
3. Co-determination and Empowerment: Digital technologies can support empowerment and help increase student co-determination beyond project work. They can enable larger and more active learning communities that involve both students and educators in the individual programs, but also across them.
4. Inclusion: Digital technologies can contribute to supporting the work of creating inclusion through a conscious focus on accessibility, diversity, and flexibility. The principle aims to make educational and teaching activities available to all students and also ensure that the individual student has a sense of being able to participate with their individual premises.

A: The class teaching consisted of a continuous review of legal texts, explained both in a broader context and with concrete examples. When a topic had been covered, students solved a mini‑case. The case was generated by AI, and after students had discussed answers in small groups and these had been reviewed, they were shown how genAI had answered the case and why the answer was correct or incorrect.

B: In the workshop, students were briefly introduced to a given topic, after which they worked independently to find, discuss and understand relevant material. Then examples from practice that supported learning were reviewed. Finally, they had to use Microsoft Copilot to generate a case related to the topic and also create a guidance for correction. If the guidance was incorrect, they had to prompt Copilot to produce a correct version. After creating the material (case + guidance), cases were circulated among groups so that each group were to solve a genAI case. The solutions were reviewed on the board and compared with the guidance for correction. 

A: By addressing and showing genAI and its possibilities to students, openness and recognition of the technology arise. This helps legitimise the use of AI but hopefully also ensures it is not used blindly, because students become aware of its errors and limitations, and why these can only be identified once they understand the subject matter themselves. In addition, it can ease lesson preparation when genAI can generate cases (or other teaching material) for you.

Since Marianne prompts genAI almost every day, she is very comfortable with it, but if you have not worked with genAI before introducing it to students, it may feel difficult and like an extra workload.

B: Students found prompting both difficult, fun and exciting. The majority had never tried it before. Allowing students to experiment with genAI and its possibilities creates openness and recognition of the technology. This helps legitimise AI use but also ensures it is not used blindly, because students become aware of its errors and limitations, and why these can only be identified once they understand the subject matter. It was therefore meaningful that they were prepared academically to assess whether genAI provided correct or incorrect answers. 

Be open to Copilot and start prompting. “Play” with how different prompts produce different answers and how your prompts can steer it towards an output you can use. My experience is that if you just start, it quickly becomes intuitive, so do not be discouraged. As mentioned, the tool can be used not only to support student learning but also as a time‑saving aid in lesson preparation.