Principles of Dynamic Modeling and Policy Design
Level of Study
Semester of Instruction
Objectives and Content
The course covers the basic building blocks of dynamic systems, provides a number of case studies, and illustrates the most important principles of model building. Exercises are used extensively to demonstrate and reinforce the student´s understanding of dynamic systems through model building and analysis.
Express knowledge and understanding
Students learn the principles for modelling and simulation in the analysis of complex, dynamic problems in interdisciplinary social science domains. Complexity is predominantly determined by the variety of accumulation and non-linear feedback processes that characterize the systems under investigation. The students develop an intuitive understanding of the behaviour arising from the underlying causal systems structure and how that behaviour feeds back to the underlying structure. They gain insights into the practice of the entire research cycle from problem formulation to policy design. In their learning process, they actively use graphical techniques and tools (software) for the purpose of exhibiting the structure-behaviour relationships investigated.
Apply knowledge and understanding
Students receive training in applying knowledge in the firm of well-constrained case studies. Students try out their intuitive knowledge and knowledge acquired in computer based simulations.
Using the techniques and tools at hand, students learn to make judgment about both structure (relationships between variables) and behaviour of systems.
Students are encouraged to participate actively in class. The graphical stock and flow and the causal loop diagrams are seen as tools for effective communication at an intermediate level between imprecise narratives and formal simulation models.
Develop learning skills
After completing the course, students typically have a new and different appreciation of how dynamic social systems work. This encourages them to ask new questions such as: what are the stocks, flows and feedback loops in a system that, at any point in time, endogenously governs systems behaviour, what is the role played by exogenous factors, do data represent causal relationships or correlations only representative for a limited time interval, will the system counteract proposed policies etc. Once these questions are asked, they motivate learning.
Required Previous Knowledge
Teaching Methods and Extent of Organized Teaching
Lectures, seminars, lab exercises and advisory sessions in
Early April (2 weeks)
15 hours (lectures) plus 10 hours (assignment assistance)
50 hours in total
Compulsory Assignments and Attendance
Classroom participation in lectures and assignment consultations
Forms of Assessment
3 hours written exam, graded (100%)
GEO-SD201 will be evaluated minimum every third time it´s taught.