Facilitator: Victoria Sheldon, Educational Developer, Teaching, Learning and Technology, CTSI
With AI tools now widely available to students, traditional assignment designs that focus only on final products may miss opportunities to understand and support student learning. Grounded in the University of Toronto AI Task Force’s principles, this session takes a pedagogy-driven approach to assessment design that documents student thinking and development.
In this session, you will explore ways to:
- Design scaffolded assignments where students document their workflows and decision-making
- Create checkpoint strategies that reveal how students are thinking, not just what they produce
- Build in space for metacognitive reflection that helps students develop critical judgment about AI use
- Shift from product-oriented approaches to assessment designs that prioritize transparency and the learning process while remaining sustainable and manageable
This session provides practical frameworks for designing assignments where evidence of learning emerges naturally through the process. Whether you are integrating AI as a learning tool or designing assignments where AI is intentionally limited, we will explore how process-based approaches support authentic engagement and help students develop essential judgment about when and how to use AI effectively. We will also reflect on the challenges this approach presents, particularly around increased workload for both instructors and students, and discuss strategies for implementing process-based assessment in sustainable ways.