Research
Research Interests
My work sits at the intersection of cognitive science, AI, and education. I study how people learn — and how intelligent systems can support that process.
Intelligent Tutoring Systems
I develop and evaluate intelligent tutoring systems (ITS) that use AI to personalize learning. Key questions include:
- Adaptive scaffolding — how can a system dynamically adjust support as a learner’s knowledge grows?
- Formative feedback — what makes feedback effective, and how can AI deliver it?
- Worked examples — how can generative AI produce high-quality examples tailored to individual learners?
- Misconception diagnosis — how can systems detect and address learner misconceptions in real time?
Bayesian Models of Cognition
I use Bayesian probabilistic models to understand human learning and reasoning. This includes modeling belief updating, concept learning, and decision-making under uncertainty.
AI in Higher Education
At a broader level, I study how AI tools are reshaping teaching and learning in universities — and what evidence-based guidance can help educators use them well.
BeLEARN Network
My research contributes to BeLEARN, the Swiss research network for the science of learning.