Overview of our research

This page sketches the common framework of our research. For the specific research interests of our team members, please visit their individual homepages.

Most generally speaking, we share an interest in cognition and experimental psychology. One primary focus of our work is the study of intra- and interpersonal processes of human cognition and behavior, including the adaptive nature thereof. More specifically, we study judgment / decision making (very broadly defined) and memory, including probabilistic (memory-based) inferences, risky choice, real-life choices (consumer choice, pro-environmental behavior), moral and ethical decision making, truth judgments, zero-acquaintance personality judgments, and social dilemma decision making. Our research aims to explain and critically test (a) how humans search for, process, and store/retrieve information, (b) how individuals differ in their behavioral preferences, beliefs, and basic tendencies (personality dimensions) including "dark" traits (cf. darkfactor.org), (c) how situational factors shape or constrain cognition, behavior, and/or (the expression of) individual differences, and (d) how the methods of behavioral scientists to address these and other questions can be improved.

On the methodological side, we mostly rely on behavioral/experimental methods and paradigms, complemented by an array of methods ranging from traditional questionnaires to interactive multi-person games (as developed in behavioral economics), process measures (e.g., eye- and mouse-tracking), and statistical/computational modeling; correspondingly, we are part of the Research Training Group Statistical Modeling in Psychology (SMiP), co-hosted by the Universities of Freiburg, Heidelberg, Landau, Mannheim, and Tübingen and funded by the German Research Foundation. The SMiP group aims to overcome a persistent and growing challenge in behavioral research, namely, the gap between substantive research in basic and applied fields of psychology and latest developments in statistical modeling and psychometrics.

Crucially, we also develop tools for other researchers to use, most notably the lab.js Software for building web-based experiments. Indeed, we share the conviction that science is a highly collaborative effort and also embrace the principles of open, transparent, and reproducible research.