Welcome to the 2026 Teach GenAI webinar series.
Running from August to November, the series presents current research, tools, and practices related to generative AI in higher education, including GenAI-supported literature searches, an introduction to the newest version of LearnGenAI, and a variety of teaching cases. The one-hour webinars are open to all and aimed primarily at university educators.
Time: 13.00-14.00 | Registration
Time: 14.00-15.00 | Registration
In this webinar, Inger-Marie will illustrate how she has supported her students’ use of AI in the 4th semester, 10 ECTS, BA-course Learning and knowledge sharing. As part of this course, students are to plan, carry out and report on an empirical investigation in a specific organisation, exploring an issue related to the course themes, learning and knowledge sharing. This also constitutes the competence goal of the course, and students submit their report for the final assessment. In the course, students’ use of AI in relation to the different phases of the empirical inquiry was supported by templates that scaffolded iterative and critical use, as well as reflection on AI-supported learning. Inger-Marie will share the learning design and its theoretical underpinnings as well as her own and students’ evaluation.
Time: 14.00-15.00 | Registration
Time: 14.00-15.00 | Registration
How can we support meaningful student learning in an era where generative AI is readily available? In this webinar, associate prof. Sille Schandorph Løkkegaard shares how a largescale course for first-year bachelor psychology students was redesigned to address (potential) AI use. Drawing on experiences from a 2026 spring course on Developmental Psychology, incl. Qualitative Methods, Sille will present and discuss her work with revisions of learning objectives, exam assessment criteria, teaching activities and -materials, and strategies for fostering teacher-student and student-to-student dialogue on use of generative AI in an academic context. The presentation offers practical examples for university teachers who wish to move beyond control and detection towards a transparent and learning-oriented approach to generative AI where the goal is to get first year students to consciously reflect on their use of generative AI as university students, active learners and future professionals (such as psychologist or the like).
Time: 13.00-14.00 | Registration
AI is rapidly reshaping how we search for academic information – but also how we evaluate and trust what we find. In this webinar, we explore the evolving landscape of AI-supported information searching, including tools, data sources, and common pitfalls.
We will discuss key questions:
How do AI tools influence search practices?
What are their strengths and limitations?
How can we critically assess AI-generated search results and avoid common pitfalls?
Participants will gain practical strategies for choosing the proper tool for your task, evaluating output and sources, and integrating AI into academic teaching and research.
Time: 14.00-15.00 | Registration
What happens when students create their own AI learning companion? In this webinar, Anne Mølgaard Nielsen, Learning and Development Consultant at SUND, will explore how Microsoft Copilot Agents can be designed to support learning rather than replace it. Drawing on experiences from health education, she will demonstrate how tailored AI agents can guide student reflection, provide feedback within pedagogical boundaries, and encourage deeper engagement with course objectives. Participants will gain practical inspiration for integrating AI agents into university teaching while maintaining a strong focus on learning, reflection, and academic responsibility.
Time: 13.30-14.30 | Registration
In this presentation, we will look at the unique potentials of digital technologies to expand learning activities across four different types of learning spaces: individual learning spaces, group work, communities of interest, and finally open connections (networks). We will highlight how we can design and evaluate learning activities that can strengthen students’ agency and opportunities for learning within these different spaces with a particular reference to how AI can be understood in relation to the framework.
Dalsgaard, C., & Ryberg, T. (2023). A theoretical framework for digital learning spaces: Learning in individual spaces, working groups, communities of interest, and open connections. Research in Learning Technology, 31. https://doi.org/10.25304/rlt.v31.3084
Time: 14.00-15.00 | Registration
In this webinar, Carmen Heine and Helle Dam Jensen will present how they began working with custom GPTs in language courses and how their create-and-configure processes developed from guided initial experiments into structured classroom applications and self-study tools. They will discuss the pedagogical considerations behind designing custom AI tools for reading and writing, including how the GPTs were developed, tested, revised, and integrated into course design. Two concrete applications will be introduced: a study-buddy approach to AI-supported reading and the systematic integration of AI into text production. They will also share how students experienced, used, and valued these tools in their learning processes. The webinar concludes with lessons learned and future perspectives on how custom GPTs may support guided, reflective, and pedagogically meaningful uses of AI in language education.
Also check out the webinars and other events from IT-vest: https://www.it-vest.dk/arrangementer