I work on metacognition in general, and in motor metacognition in particular. I am interested in how we can best measure the brain’s ability to monitor and control itself. In the case of motor metacognition, I also wonder how this ability interacts with our ability to learn a new motor skill. I use mostly behavioural methods, but also sometimes use neuroimaging (EEG/MRI).
On an independent line, I am also excited about the possibilities of collecting data online.

I am a postdoctoral researcher at the Hector Research Institute of Education Sciences and Psychology, working on the intersection of education, cognitive science, and human-AI interactions. My work focuses on studying question-asking mechanisms during learning and how AI can reshape their cognitive demands and benefits.

I’m a cognitive (experimental) psychologist with passion for methodology and statistics. My past research was concerned with how individuals learn to protect themselves from danger. To this end, I pursued the idea that individuals estimate the risk of harm using a ‘cognitive map’ of their environment built from multiple separate learning episodes acquired in safety on the one hand, and minimal aversive experience on the other.
At the Hector Research Institute for Education Sciences and Psychology I work as a postdoctoral researcher and continue studying fundamental aspects of memory but in a naturalistic setting with the aim to better elucidate on how we learn and remember.

My expertise lies in network analysis and large language models (LLMs) within educational psychology. I’m currently focused on combining these two approaches to better understand and improve the motivational aspects of learning materials. By using LLMs to analyze text and applying network analysis, I examine how content structure, language, and topic flow influence student engagement and motivation. In my additional role as scientific lab organizer, I am responsible for ensuring smooth and efficient operations within our research team.

I am researching interactions between teachers and students, i.e., I do not only focus on effects of teachers on students but also analyze how students shape the teaching they receive. It is important to me to move away from purely correlational studies towards studies that address causal research questions. To achieve this I use a variety of methods and designs ranging from qualitative analyses to advanced quantitative methods for causal inferences. In the future I would like to leverage the growing potential of AI for automated assessments of teacher-student interactions based on classroom recordings to gather more intensive longitudinal data for the assessment of dynamic interactions between teachers and students.

I am a postdoctoral researcher at the Hector Research Institute for Education Sciences and Psychology and my research currently focuses on the modeling of social contagion of classroom behaviors. While this phenomenon has been investigated in social psychology, its application in educational contexts has been limited. To address this gap, I employ immersive virtual reality to investigate how exactly students “copy” each other and what the outcomes of this social contagion are. My other field of research is developing computational models of dynamic self-regulated learning to better understand how academic goals are revised and how other factors, such as achievement emotions, may influence the way students learn.

I am a postdoctoral researcher at the Hector Research Institute for Education Science and Psychology at the University of Tübingen working in the field of developmental neuroscience with a focus on intellectually gifted children. My interest lies in how the spatial organization of the cerebral cortex subserves learning and cognition in the human brain. To this end, I pursue questions about the developmental mechanisms by which the spatial arrangement of functions may emerge in the cerebral cortex, and its ramifications for cognitive abilities.

I am a post-doc at the Hector Institute of Educational Sciences and Psychology. I am working towards an algorithmic- and computational-level understanding of various aspects of human exploration, including the emergence of situational curiosity as motivation for information-seeking, emergence of interest and curiosity traits, generation, selection, and pursuit of goals. My hope is to develop knowledge that can be useful in educational contexts. I rely on theory-driven statistical/cognitive modeling to explain data collected in behavioral experiments.