This course focuses on integrating qualitative empirical methods with social simulation, specifically agent-based modeling. Students develop both quantitative and qualitative methodological skills to prepare for the collaborative design of a mixed-methods group project.

The quantitative component begins with an introduction to the science of complexity and the characteristics and mechanisms of complex adaptive systems, broadly conceived. It then examines the role of modeling and simulation in the social sciences, highlighting the advantages of endogenous dynamics, disaggregated processes, and the disequilibrium approach. Students master the agent-based methodology by working with NetLogo, the most widely used software environment for developing agent-based models.

The qualitative component is connected to the quantitative part through a discussion of what an 'agent' is from an empirical perspective. The aim of qualitative research is to inform the development of theoretical assumptions that can be further elaborated on in a mixed methods design, such as agent-based modeling. Working in project groups, students will collect primary data using methods such as (expert) interviews, focus groups and multi-person interviews. They will also learn how to analyse this data using various techniques, including MAXQDA software.

For the final project, students design their own mixed-methods group study by adapting and extending an existing agent-based model (drawing from textbook models covering economic, sociological, or environmental topics) to address a topic in social-ecological economics. Crucially, the model is grounded in empirical qualitative social science.

The implementation of this group project constitutes the focus of the winter term portion of the course.

After successful completion of this introduction, students

• understand different research methods and strategies
• know how to conduct interviews and focus groups
• know how to analyse qualitative data 
• understand the basic mechanisms and dynamics of complex adaptive systems
• have acquired basic programming skills for agent-based modelling (in NetLogo)
• are able to perform, alter and analyze single simulation runs of textbook models
• are able to design/sketch their own group-based agent-based modelling project with empirical validation by qualitative methods (to be implemented in the winter term)
• write a critical reflection on quantitative and qualitative methods of their designed project

80% attendance of the class is required! If you miss a class, please inform us in advance!

• prepare the literature for discussions in class (hands-on exercises) 
• handwritten quizzes in class for the qualitative parts
• collect first qualitative data (do expert interviews, focus groups) on your topic
• analyse qualitative data
• programming instructions and individual exercises with NetLogo
• analysis and interpretation of baseline models
• seminar paper on new design of mixed-methods project

Grading:

• Quantitative part 30 %

• Qualitative part 30%

• group-based seminar paper on mixed-methods project 40%

SEEP courses do not allow creation of assignments, exam answers or other assessed work using generative AI (e.g. ChatGPT).  All such work is expected to be the original work by the student concerned and is assessed as such.  Work copied from a generative AI source is equivalent to plagiarism and will be treated as such.

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Barbara.Haas@wu.ac.at

Manuel.scholz-waeckerle@wu.ac.at