I am a Ph.D. candidate focused on developing computational models of child cognition in an adaptive online learning environment, employing a Bayesian approach. I am affiliated with the EdAptive Lab and the  Amsterdam Mathematical Psychology Lab (AMPL) within the Psychological Methods Group.

My research lies at the intersection of cognitive development, educational technology, and statistical modeling. I investigate how children learn and think, emphasizing the combination of theories from (mathematical) cognition with Bayesian computational models applied to large-scale behavioral data. Using data from an adaptive online learning platform used in Dutch primary schools, I study how cognitive skills develop and how those developmental trajectories can inform adaptive learning systems.
Currently, I lead two projects that reflect this goal. The first centers on working memory, where I examine how performance on serial recall tasks develops across childhood. The second project focuses on clock reading, a cognitively demanding skill that draws on time perception, language, math, and memory. Both projects aim to contribute to theoretical understanding while offering insights that can improve adaptive educational technologies.

Research expertise

• Working Memory
• Adaptive Online Learning
• Developmental Cognitive Science

Other links

• AMPL
• EdAptive