How can AI systems help with differentiation in education? My work is focused on making learning experiences more adaptive, transparent, and motivating.

I am specialised in human-centred explainable AI, studying how outcomes of AI models can be explained to and controlled by different audiences in different contexts. For example, in the context of teenagers using an adaptive learning platform, I have looked into how to justify recommended exercises and give teenagers control over their difficulty level.

I design and implement explanations and control mechanisms that typically involve interactive data visualisations. Crucially, I also evaluate how they affect people’s behaviour. Mixing quantitative and qualitative research methods, I have conducted many user studies and experiments with teenagers and teachers to test the impact of explanations and control mechanisms on trust, understanding, motivation, and learning, for example. Given my interest in motivation, I have also worked on personalised gamification.

My background lies in fundamental mathematics (MSc), applied informatics (MSc), and computer science (PhD).