For departments and programs

The rapid development of generative AI is such that it is not reasonable to leave it to each individual teacher to explore the field and draw conclusions for teaching on their own. The short-term challenges regarding examination practices require collegial discussions, as do the long-term challenges regarding how generative AI might affect students’ learning in the future.

Complete consensus on all issues is neither possible nor desirable, but within each department, subject, or program, it is necessary to discuss what should apply to everyone and what needs to be decided at the course and teacher level. Naturally, it is then important to communicate clearly to both teachers and students what applies, but also to be able to justify what applies.

Step 1: Determine the Starting Point

Knowledge about generative AI, and interest and engagement in AI-related issues, varies not only between scientific fields and subjects but also within each subject. A first step is therefore to gather the teaching staff and appropriately inventory the range of hopes, fears, questions, and wishes within the teaching staff. One of the goals of this review is to identify the continuing education needs within the teaching staff so that everyone can develop a basic AI literacy.

Doing this together, in small group discussions, and not primarily through, for example, a survey, is a good idea, partly because more unexpected things can come up in informal conversations with colleagues, in addition to what the groups are asked to discuss. Once you have gathered what has emerged, you can, if necessary, follow up with a survey to get even better data for the continued work from a management perspective - but start rather with the collegial conversation!

This first step should result in a concrete proposal for continued development, with purposes, a timeline, and responsible contact persons indicated, shared with the teaching staff.

Step 2: Measures in Three Areas

As university teachers, we usually and fortunately enjoy a great deal of trust from the employer to independently design the teaching. However, during the ongoing AI development, there are three areas where initiatives from the management level play a crucial role.

Review of Examination Practices

Each course and program needs to review and, if necessary, develop its examination practices so that they still provide teachers with a good basis for assessing how much students have learned. Here, directors of studies and others need to take multiple responsibilities:

• They need to ensure that examination practices in all programs have considered the AI issue.
• Program managers need to ensure that changes made at the course level do not lead to distortions that make student progression more difficult.
• They may need to initiate a discussion in the teaching staff about whether examination practices need to be improved. Replacing all home assignments with in-class exams is a simple way to handle risks with generative AI but can lead to significant quality losses. How could the quality of the examination be improved without compromising security?

Communication with Students about What Applies

From the students’ side, uncertainty about what applies regarding the use of generative AI is a growing concern. Exactly what limitations apply often must, of necessity, be decided within the framework of each course. From the management level, in consultation with the teaching staff and student representatives, you can:

• Discuss the need for common, local guidelines for the use of generative AI, and formulate such guidelines if necessary.
• Determine how students should be informed about what applies, both at the department or program level and at the course level.

Continuing Education and Reflection

To develop a basic, general AI literacy, there is a lot that teachers (including those working at the management level!) can do on their own (but encourage teachers to carry out such activities together!).

But it may also be appropriate to gather the entire or parts of the staff for more exploratory workshops. Three important areas for such workshops can be:

• Practical skills, where teachers test, try and compare prompts, review results, etc.
• How to maintain and strengthen the academic learning environment - curious exploration and critical examination, with research and teaching close to each other - within the department/subject/program.
• How to maintain and strengthen academic integrity, i.e., “compliance with ethical and professional principles, standards, practices, and a consistent system of values, that serves as guidance for making decisions and taking actions in education, research, and scholarship” (definition from ENAI).

Step 3: Structures for Long-Term Work

The most important contribution that the management level can make to promote long-term and deepened development is to ensure that there is a well-functioning, fixed structure that gives teachers the opportunity to regularly share their experiences from teaching (and it does not have to be solely about generative AI!). Hearing colleagues talk about, and discussing concrete examples from teaching, with reflections on the implementation, whether it turned out more or less successful, can be among the most effective ways to develop a deeper understanding of the possibilities and limitations of generative AI within one’s own subject. And why not let students hold a teaching day and show examples of how they use generative AI?

Some departments already have such a vibrant culture of sharing, but others may need to strengthen it. Of central importance can also be how the experiences that emerge are managed so that they are included in an accessible knowledge bank and can be passed on to new teachers.

Support for Implementation

If you would like advice or practical support in implementing the measures described above, you are welcome to contact the unit for Academic Teaching and Learning. We have conducted workshops on generative AI for teachers from all of the university's three domains and led discussions and exercises tailored to the different needs and conditions that different departments, subjects, and programs may have. Please contact us for a consultation!