“AI and Teaching” Grant Scheme 2026–2027

The “AI and Teaching” scheme supports the design, testing and development of teaching practices that integrate artificial intelligence (AI) at the University of Fribourg. It forms part of the EduKIA project (2025–2026), led by the University of Fribourg and HES-SO and supported by swissuniversities as part of the PgB Open Education & Digital Competencies program.

Le dispositif en bref

What can the funding cover?

The funding, up to a maximum of CHF 8,000 per project, may be used to cover resources directly required for the design, development and implementation of the project.

Types of eligible projects

• Creation of a discipline-specific toolkit

  A discipline-specific toolkit could bring together and organise AI-related resources and tools selected according to the specific features of the discipline and the teaching and learning activities. It would provide teaching staff and students with selected, documented resources adapted to their context. It would thereby help teaching staff and students explore and use AI applications, and reflect critically on them, in relation to the practices, needs and tasks specific to the discipline.

  Example for inspiration

  MyPLE.chAn open-access toolkit offering selected resources and digital tools to help students carry out their academic tasks.

• Implementation of a documented educational experiment

  An exploratory project could design and test an educational approach integrating AI, particularly within a course or seminar, to identify its benefits, limitations and conditions for implementation. The experiment should be documented so that lessons can be drawn from it.

  Example for inspiration

  Apprendre grâce à un « chatbot » personnalisé  (UniNE)

  An experiment conducted in a Master’s-level course using a personalised AI assistant called Brian – The AI Tutor for Adaptive Learning, designed to support students in their learning. Led by a lecturer with support from the University of Neuchâtel’s Teaching and Learning Support unit, the project illustrates the integration of an AI tool tailored to a specific teaching context.

• Career Design project

  Career Design projects could prepare students for AI-driven changes in their professional field. They could address shifts in occupations and tasks, emerging skills, experimentation with sector-specific tools, simulations of professional situations or human–AI collaboration. They could also involve experts from the relevant professional field, allowing students to test what they learn against the realities and evolving demands of their future professions. The aim would be to connect disciplinary skills, an understanding of how professions are changing, and the appropriate, critical and responsible use of AI.

  Example for inspiration

  Career Design - Préparer le corps estudiantin à une entrée réussie sur le marché du travail (HES-SO)

  A project designed to prepare students for entry into professional life through a competency-based approach, reflective practice and experimentation with authentic recruitment situations. In particular, the project enables students to showcase their skills and develop their career plans.

• Creation and facilitation of a community of practice

  A community of practice could regularly bring together members of the university community to explore how to integrate AI into teaching. It would enable participants to share experiences, pool practices and resources, collectively test new approaches and develop shared knowledge. It would thereby foster collaboration and the development of appropriate, critical and responsible AI-related teaching practices.

  Example for inspiration

  Community of Practice « Digital Learning and Teaching in Sports » (HEFSM)

  A community of practice dedicated to digital teaching and learning, enabling members to share their expertise and practices, document their experiences and develop new educational approaches. This model could be adapted to integrating AI into teaching at departmental or faculty level, or across faculties, to encourage exchange, resource sharing and the collective development of practices.

• Scholarship of Teaching and Learning (SoTL) project

  A project following a Scholarship of Teaching and Learning (SoTL) approach could enable teaching staff to systematically and critically study teaching practice that integrates AI, drawing on theoretical frameworks and data collected from students. It would seek to analyse the effects of this practice on teaching and learning, to better understand educational uses of AI and refine practice based on the findings.

  To find out more about the SoTL approach and the support offered by the DidaNum Service:accompagnement/sotl/

• Educational co-design with students

  An educational co-design project could involve teaching staff and students in designing teaching scenarios, activities or resources integrating AI. Involving students would help ensure that their needs, experiences and uses are considered, while keeping the knowledge, methods and skills specific to the discipline at the heart of learning. The resources or activities developed could then be tested with the target audience and refined based on the feedback collected.

  Example for inspiration

  Formation IA générative en droit à l’UQAMCollaborative development of an asynchronous course designed to introduce law students to generative AI and its responsible uses, while preserving the critical thinking and methodology specific to legal studies. Students contributed to the writing, instructional design and production of the resources. After an initial pilot in two courses, student feedback also helped identify areas for improvement.