Models in the Study of Human Behavior

Lecturer (assistant)
TermWintersemester 2023/24
Language of instructionEnglish
Position within curriculaSee TUMonline


Upon completion of the module, students possess profound knowledge about the utility and limitations of formal modeling approaches to the study of human behavior. Specifically, students are familiar with the goals and problems of the behavioral sciences and understand how they can be addressed through formal modeling. They know different model classes – including some state-of-the-art models in decision making – and which research question and inferences they are appropriate for. Based on this knowledge, students are able to interpret and evaluate models in the relevant literature and to make reasonable modeling choices for future research or applied projects. In addition, students improved their ability to effectively communicate the main ideas and results of a published paper or a broader research project in concise scientific talks.


Formal models (in mathematical or programming language) figure prominently in the natural science (e.g., physics), but less so in the behavioral sciences (e.g., behavioral economics, psychology). The lack of models – particularly of those that attempt to explain the cognitive processes underlying human behavior – led to the emergence of distracting labels and narratives (e.g., “biases”, “thinking fast and slow”). These distractors are remarkably popular in behavioral sciences as well as in business and society, yet they have done so little to advance our understanding of why people behave the way they do. This course shows how modeling is invaluable for gaining genuine insights into human behavior and how it can drive empirical research and real-world applications (e.g., policy-making). Some state-of-the-art examples are presented by the students in the mock conferences. Some guiding questions and discussion points are: - What the behavioral sciences want and where they have gone astray? - Why the behavioral sciences cannot help but to model? - What are scientific models of human behavior? - What can the behavioral sciences learn from the natural sciences and their models? What not? - Which role do cognition and the environment play in the explanation of human behavior? - Case studies in decision making under risk and uncertainty (descriptive, predictive, process/cognitive models) - Relations among and integration of models within and across model classes - Modeling and the construction, development, and testing of theories about human behavior and cognition - Real-world applications of models of human behavior and cognition

Teaching and learning methods

Seminar sessions comprise of ca. 45 minutes talks (by the lecturer) aiming to complement the readings and convey relevant knowledge about the topic. Each talk is accompanied by group and small-group discussions which can be both prompted by students and the lecturer. Exercise sessions take the form of mock conferences, i.e., each student will provide a scientific talk (incl. discussion) based on a high quality publication relevant to the topic. As a prelude, the first three sessions are for training, i.e., important aspects of scientific talks are practiced in mini-exercises.

Recommended Literature

For an idea of the readings and the topics addressed in this course, you may see:

Example for a seminar paper:
Guest, O., & Martin, A. E. (2021). How computational modeling can force theory building in psychological science. Perspectives on Psychological Science, 16(4), 789–802.

Example for a mock conference paper: 
Zhao, W. J., Coady, A., & Bhatia, S. (2022). Computational mechanisms for context-based behavioral interventions: A large-scale analysis. Proceedings of the National Academy of Sciences, 119(15), e2114914119.