Level of Study
Objectives and Content
In this course, students apply the System Dynamics method to problems in both the public and private sectors. Students will apply and gain reinforcement of skills learned in other system dynamics courses as they follow a structured process for modelling and simulation of dynamic problems in both social and natural systems. Emphasis is on the design of simulation models to explain problem behaviour in dynamic systems, and on the re-design of such models to represent the implementation of policies aimed at improving their behaviour. Students learn to use the system dynamics modelling process: define the dynamics of problems, develop hypotheses regarding the structure underlying problem behaviour, analyse and validate computer simulation models, and design policies to improve systemic behaviour. In addition to learning from the lectures and materials, students gain hands-on experience through in-class exercises, assignments, and an in-depth project. The reading list includes a primary textbook and supplemental material.
Express knowledge and understanding
Students should be able to describe and explain in detail the system dynamics modelling process, with particular emphasis on defining the dynamics of a problem; formulating hypotheses regarding the structure underlying dynamic problem behaviour; analysing a model to improve its reliability and usefulness; analysing a model's structure to understand the origin of its dynamic behaviour; testing a model's sensitivity to parameter assumptions; testing changes in a policy parameter; designing and testing new policy structure; and planning for policy implementation. The students should through this work deepen their understanding of the structural causes of dynamic behaviour and hone their skills with system dynamics software tools.
Apply knowledge and understanding
Students should be able to (1) define the dynamics of a problem; (2) formulate hypotheses (in words, diagrams, and a set of model equations) as tentative explanations of problematic dynamic behaviour; (3) analyse a model's structure to discover the endogenous source of particular dynamic patterns; (4) analyse and test a model to improve its reliability and usefulness; (5) test a model's sensitivity to parameter assumptions; (6) identify and evaluate potential leverage points for improving model behaviour through policy parameter analysis; (7) conduct policy design and evaluation with modifications in the structure of an explanatory model; (8) identify obstacles to policy implementation and include feasibility criteria in policy design; (9) develop and analyze a simulation model that provides a useful explanation of a given problematic behaviour in a narrowly-defined task; and (10) identify a real-world dynamic problem and conduct a 6-week empirical and theoretical investigation, culminating in an explanatory model, a policy model, a written report, and an oral presentation.
Students should be able to (1) adopt a client's perspective to assess the definition of a problem, the boundary of a model, and the model's reliability and usefulness; (2) establish and evaluate criteria for evaluating how well a model structure contributes to the explanation of an observed or hypothesised dynamic behaviour; (3) assess data requirements in light of a model's sensitivity to parameter estimates; (4) determine whether simulated policy options are feasible in the real world; (5) evaluate policy implementation obstacles and modify expected benefits accordingly; and (6) take ethical considerations into account when conducting research and developing models, and when interacting with clients, stakeholders, and colleagues.
Students should be able to (1) organize a written discussion of a modelling project in a way that highlights the research problem or question, the hypothesis, the method of analyzing and testing the hypothesis, and the policy implications of the investigation; (2) make oral presentations of their work; (3) design and present model diagrams in a way that facilitates communication and understanding; and (4) translate technical information into language that clients understand. In addition, students should gain additional confidence in their communication skills through extensive discussion and debate in classroom settings.
Develop learning skills
Students should be able to (1) conduct research and engage in projects with a high degree of independence, responsibility, and reliability; (2) access and interpret relevant scientific and policy literature; and (3) write and speak effectively about their work and relevant issues.
Required Previous Knowledge
Credit Reduction due to Course Overlap
Access to the Course
The course is open to students enrolled in the Erasmus Mundus master program and to graduate and undergraduate students at the University of Bergen.
Teaching and learning methods
The course consists of live-streamed, recorded and stored lectures, seminars and computer labs with active participation by students, short in-class tasks, written assignments, and a major project requiring a written report, a model, and a presentation. Individual and group support will be provided in-person or remotely by teaching assistants and the professor.
Compulsory Assignments and Attendance
Forms of Assessment
Assessment consists of evaluating a modeling project. The modeling project consists of a simulation model (70% of the final grade), an oral presentation in the form of a video clip and response to examiners' questions (30% of the final grade).
An ECTS grade is provided to the student at the end of the course according to the A-F scale.
Assessment in teaching semester
The reading list will be ready before 1 June for the autumn semester and 1 Decemeber for the spring semester.
All courses are evaluated according to UiB's system for quality assurance of education.
The Programme Committee is responsible for the content, structure and quality of the study programme and courses
Course coordinator and administrative contact person can be found on Mitt UiB.
The Department of Geography at the Faculty of Social Sciences has the administrative responsibility for the course and the study programme.
Type of assessment: Modeling project
- Withdrawal deadline
Exam part: Simulation model
- Submission deadline
- 22.12.2022, 14:00
- Examination system
- Digital exam
Exam part: Oral presentation