Courses and workshops
The Teaching and Learning Centre Science provides lecturers with opportunities to professionally develop themselves, share knowledge, and innovate their education.
Below, you can see an overview of the courses and workshops that FNWI lecturers can follow.
Introduction to Embodied Learning
In this introductory course in Embodied Learning, we explore what embodied teaching and learning can entail and how it relates to traditional teaching.
Smarter or Dependent - The impact of AI use on Learning, Thinking, and Writing
AI tools make it possible to produce texts faster, more easily, and sometimes with a more polished appearance than ever before.
Storytelling as a didactic tool
Unlock the power of storytelling in academia with this specialized course on Educational Storytelling.
AI Advanced Context Engineering
Learn how to use UvA AI Chat more effectively by working with multiple sources, different types of input and simple workflows.
Daily office tasks with UvA AI Chat
In this practical workshop, you will get to know concrete applications for your own tasks, such as improving texts, organising information, summarising content, and streamlining workflows more efficiently.
Using UvA AI Chat to Collaborate with AI
Learn how to use UvA AI Chat as a secure “AI layer” on top of your own course materials, documents and datasets.
GenAI and Assessment 1 - Understanding the Impact
Learn about the capacity of GenAI and how your unsupervised assessments are impacted.
AI and Visualizations
Learn how to use UvA AI Chat to create and refine images and other visual materials.
GenAI in the classroom
Do you want to learn how to design learning activities that genuinely support student learning?
Guiding discussions
Learn about methods to stimulate discussion and what you can do to keep students engaged in discussion.
Contemplative Pedagogy
How to introduce slow-paced, introspective, and intersubjective learning activities into university education.
AI Data & API
Learn how to use UvA AI Chat to work safely with your own documents and datasets, and why popular external tools are often not suitable for sensitive or institutional data.