Siehe TUMonline
Anmerkung: - An introductory course in psychology/motivation/emotion, cognitive science, neuroscience, or computational methods is recommended. - Basic knowledge of programming and statistical analysis will be beneficial.

Theoretical Understanding: Gain a solid foundation in theories of motivation, emotion and coping, and understand their application in psychological research.
Computational Skills: Learn to use computational tools and techniques, including agent-based modeling, machine learning, and simulation, to model psychological phenomena.
Model Development and Application: Develop the ability to create and apply computational models to investigate questions related to motivation, emotion and coping.
Research Competency: Conduct a computer simulation or a part of an empirical research project or program a code that integrates theoretical and computational approaches, culminating in a comprehensive report and presentation.

The aim of the project work is to solve a theoretical or implementation-related problem, which is developed over several phases (initiation, problem definition, role distribution, idea generation, criteria development, decision-making, execution, documentation, presentation). The corresponding project task should be completed within 3 months using appropriate resources (literature research, programming environments, PowerPoint, Word). The project work concludes with a comprehensive documentation and presentation of the task. The project work can also be done in a group. The documentation should be between 2000 and 5000 words in length.
The project will be evaluated on a pass/fail basis ("successful" vs. "unsuccessful"; no grades).

Contents:
- Foundations of Motivation, Emotion and Coping: Key concepts in motivation; Zurich Model of Social Motivation; Neuroscientific underpinnings of motivation and coping
- Computational Modeling: Basics of computational thinking and programming
- Modeling techniques: agent-based models, machine learning, simulations
- Modeling Motivation and Coping: Techniques for representing motivational, stress, and coping processes in computational models; case studies and practical examples
- Integrated Modeling Approaches: Combining the modeling of motivation and coping; applications in predicting behavioral responses to situational changes and challenges
- Project Development and Presentation: Guidance on developing individual research projects; presentation of projects and peer feedback sessions

- An introductory course in psychology/motivation/emotion, cognitive science, neuroscience, or computational methods is recommended.
- Knowledge of programming in Python or Matlab/Simulink is necessary.

project work and a presentation of 20 minutes (plus 25min discussion) in English.

Basic Literature:
Bischof, N. (2016). Struktur und Bedeutung. Eine Einführung in die Systemtheorie für Psychologen, Biologen und Sozialwissenschaftler zum Selbststudium und für den Gruppenunterricht [Structure and Meaning: An Introduction to Systems Theory for Psychologists, Biologists, and Social Scientists for Self-Study and Group Instruction]. 3., überarbeitete und neu illustrierte Auflage. Bern: Hans Huber.
Kuhl, J., Quirin, M. (2024). Persönlichkeitspsychologie: Motivation, Kognition und Selbststeuerung [Personality Psychology: Motivation, Cognition, and Self-Regulation]. Göttingen: Hogrefe.

Additional Literature:
Research articles and book chapters to be announced.