Level of Study
Semester of Instruction
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 simulation modelling of dynamic problems in both social and natural systems. Emphasis is on designing simulation models to explain problematic dynamic behaviour, and then re-designing the models to represent the implementation of policies to improve behaviour. Students learn to use the system dynamics modelling process: define the dynamics of problems, develop hypotheses for problematic dynamic behaviour, analyze and validate computer simulation models, and design policies to improve systemic behaviour. In addition to learning from the lectures, students gain hands-on experience through quick tasks, weekly assignments, and an in-depth project. The reading list includes a primary textbook and supplemental materials.
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 of problematic dynamic behaviour; analysing a model to improve its reliability and usefulness; analysing a model´s structure to learn its behavioural dynamics; 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. In addition, students should 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. In addition, students should improve their abilities to translate between different modes of expressing structural causes of dynamic behaviour (e.g., narrative theories, causal loop diagrams, stock-and-flow diagrams, and mathematical equations).
Students 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 other projects with a high degree of independence, responsibility, and reliability; (2) function as a constructive member of a team; (3) access and interpret relevant scientific and policy literature; (4) write and speak effectively about their work and relevant issues; and (5) successfully complete a master´s thesis.
Required Previous Knowledge
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 if they have taken GEO SD302, GEO SD303, or other courses that provide an adequate background in System Dynamics.
Teaching Methods and Extent of Organized Teaching
The course consists of lectures and computer lab activities, short in-class assignments, weekly written assignments, and a major project requiring a written report, a model, an interactive learning environment, and a presentation. There is a four-hour written exam. Course meetings include 36 lecture hours and 18 hours of lab assistance over a 6-week period (two lectures and one lab per week) from the end of October until early December. The exam is in mid-December.
Compulsory Assignments and Attendance
Forms of Assessment
Assessment consists of evaluating a modeling project. The modeling project consists of a simulation model, a conference-style poster describing and explaining the model, and an oral presentation and response to examiner's questions.
An ECTS grade is provided to the student at the end of the course according to the A-F scale.
GEO-SD304 will be evaluated at least every third year
Type of assessment:
- Submission deadline
- 15.12.2017, 17:00
- Withdrawal deadline
- Examination system
- Digital exam