NT Teachers Retreat 2026
The Faculty of Science and Technology and the Pedagogical Academy welcome you to this year’s teaching seminar on 5 March. The goal of the seminar is to facilitate good conversations and discussions among teachers, as well as to highlight relevant topics and perspectives important for NT’s education, teaching staff, and students. This year we follow up on two important themes: AI in teaching and learning, and UiB’s focus on the First-Year Student.
Main content
The seminar runs from 08:30 to 15:00 and includes a varied programme with keynote lectures, a panel discussion, roundtable sessions, a workshop, and a poster session. Tor Ole Odden from UiO will give the keynote lecture and lead a workshop on AI and teaching. We will also learn more about some of NT’s major first-semester courses included in many/all programmes, and the faculty’s education-focused PhD candidates (and others) will present their research in the poster session.The roundtable discussions cover a wide range of topics, from e.g. 3D models and case assignments to how NT welcomes and supports its first-year students.
As always at NT’s teaching seminar, the focus will be on learning from, discussing with, and being inspired by colleagues at NT! Welcome to the seminar!
Overview program
08:45: Welcome and introduction to the programme
09:00: Keynote lecture: What Is AI Actually Doing? Conceptual Tools for Science Teachers, Tor Ole Odden (Center for Computing in Science Education, UiO)
09:30: Poster session: posters on research related to NT’s education and students
10:15: Panel discussion: First-year courses at NT (mathematics, chemistry, informatics, and physics)
11:00: Roundtable discussions (parallel sessions): various topics from NT teachers and students
12:00: Lunch
13:00: Roundtable discussions (parallel sessions): various topics from NT teachers and students
13:40: Workshop: Helping Students Learn with AI: A Hands-On Workshop for Science Educators, Tor Ole Odden (UiO)
Abstract: Generative AI is now widely available to both science students and instructors, but using it well requires strategy, discipline, and clear pedagogical intent. In this two-part session, I will provide some conceptual tools and concrete strategies for using AI to support learning in science. In the first part, I will introduce three research-based frameworks for understanding how large language models work: AI as an improv artist, a blurry JPEG of information, and a conceptual blender operating in a space of meaning. These frameworks help explain why AI outputs can be simultaneously powerful, misleading, and highly sensitive to context. In the second part of the session, participants will take part in a guided, hands-on workshop focused on practical uses of these tools in higher education science. I will demonstrate and scaffold activities in which AI is used to support sensemaking while reading, help students get unstuck on problems, and assist with checking and refining reasoning without replacing thinking. Along the way, I will draw on examples from the history of physics and introduce four concrete prompting strategies that operationalize the metaphors for AI “cognition”.
14:50: Closing remarks (ends at 15:00)
