Can AI Teach Reflection? Measuring Learning with AI Beyond Outcomes

Can AI Teach Reflection? Measuring Learning with AI Beyond Outcomes

AI tools are becoming an increasingly large part of education, but how can we tell whether they actually help people learn? In this talk, I’ll share insights from a research project on AI-supported reflective writing.
Why you should attend the talk: You will gain a clear understanding of the challenges of evaluating learning with AI and what UX researchers and designers can take away for their own practice.
Rather than only looking at final outcomes, this project focused on the learner’s experience and their learning process. I’ll show how we combined quantitative and qualitative research methods to do so. I will discuss why evaluating learning with AI is challenging and what UX researchers and designers can take away for their own work. Overall, the talk connects academic research with applied UX practice by offering practical perspectives on how to assess the real impact of AI on users.

A bit more about the project: The presented research was published at a Human-Computer Interaction conference and involved the iterative design of a reflection tool with different types of AI feedback. The evaluation with users was then conducted during 6 weeks in 2024.

Léane Wettstein is a PhD student at the HAIS (Human AI Learning Systems) Lab at Bern University of Applied Sciences (BFH) and University of St. Gallen. Her research looks at how students use AI feedback and how it affects their ability to think about and manage their own learning (metacognitive skills). The goal of her work is to help design AI tools and learning systems that encourage effective use of AI and support long-term learning.
She holds a Master’s degree in Psychology from University of Basel. Before starting her PhD, she worked as a research assistant at the University of Basel and ETH Zurich.