As part of the Pedagogy Unit (Uniped), the focus of this research group is to work with educators on the critical assessment of Artificial Intelligence (AI) in education to explore AI’s implications and identify appropriate applications.
In Uniped, we are particularly concerned with the ethical considerations and potential impacts on teaching and learning. Therefore, we engage educators in critical discussions about the challenges and opportunities of AI in education.
This research group aims to develop collective strategies to address ethical issues and share insights. We also aim to equip educators with the frameworks needed to evaluate AI’s role while keeping focus on educational outcomes and exploring the practical AI use cases in education. We will do this through demos and practical workshops that highlight responsible and effective applications in higher education practices.
Our work on AI, teaching and assessment
We work with teachers at UiS and the local community on AI and assessment in higher education and other teaching contexts. Our focus is on helping courses and programmes maintain meaningful assessment when students have access to AI tools as it becomes part of professional practices.
Our approach
We start from a question about assessment validity: can we still draw reliable conclusions about what students know and can do? This is a different starting point from trying to detect or prevent AI use, approaches that the available evidence, and now also national policy, suggest do not work well in practice.The alternative is structural: designing assessment so that genuine learning is the most efficient path to completion, regardless of what tools are available. Our work draws on established assessment research including validity theory, cognitive load theory, and layered verification models and translates it into a systematic process that helps educators make evidence-based decisions about each learning outcome in their course.
What we offer
We run a 25-hour professional development workshop (AI in Education) where teachers explore AI capabilities, work through the assessment evidence, and apply the framework to their own courses and assignments. The workshop is hands-on and discipline-specific where participants produce a documented redesign plan for their own teaching context.We also work with specific groups across the institution: programme coordinators mapping verification coverage across degree programmes, PhD supervisors, study programme boards, and faculty leadership.
Institutional work
We advise UiS's AI committee (KI-utvalget) and contribute to institutional assessment strategy. We have produced practical guidance for both individual courses and whole programmes, including implementation within existing regulations. We also build tools to support this work including interactive assessment analysis toolkits, programme-level audit tools, and structured workshop materials in Canvas.
Department of Higher Education Pedagogies