Modelling for Sustainability

6 EC

Semester 1, period 2

5132MOFS6Y

Owner Bachelor Future Planet Studies
Coordinator dr. ir. E.E. van Loon
Part of Minor Interdisciplinary Minor Sustainability, year 1Minor Sustainable Food System, year 1

Course manual 2023/2024

Course content

We use models of various forms, both in everyday life as in science, for many purposes: to express ourselves, understand the world around us and to solve problems of various kinds. Reasons to use models may be to exchange of ideas between  different disciplines, identify processes where understanding is lacking, generate predictions or test the theoretical consistency of an idea.

In this course our aim is to learn about the various ways by which models may be used to in relation to sustainability questions. The modeling skills you will acquire will not be limited to sustainability but be broadly applicable:  you will learn about the meaning of fundamental modeling concepts, the different phases in a modeling-project, conducting experiments with models and report about and the practical use and interpretation of different model-types that are frequently used.

In the first part of the course, basic concepts and skills are taught to translate a (complex and interdisciplinary) system into a computer model. While focusing on system dynamics and agent based models, we will explore the various opportunities this offers for understanding system behavior, assessing risk and uncertainty, and experimenting with possible interventions.

Besides these two important model types, we will also study, we will apply various types of socio-ecological models and explore the properties of these. The four types of models we cover are:
1. system dynamics models (contemporary climate models belong to this class)
2. agent-based models (these were e.g. used to inform decision making during the Covid pandemic)
3. statistical models (nearly every model in the realm of 'machine learning' is of this type)
4. decision making (e.g. used to find optimize allocation of resources)

Study materials

Literature

  • is available in the UvA library (made available via hyperlinks) and otherwise open source material is used

Syllabus

  • is available at the Canvas site

Practical training material

  • is available at the Canvas site

Software

  • various web-based tools & open source software that can easily be installed

Objectives

  • recognize and describe key properties of sustainability systems such that these can be translated into a (computer)model
  • recognize different phases in model development and use
  • recognize different model types (system dynamics, agent-based, statistical, decision and machine learning) and be able to describe differences among these
  • apply existing system dynamics, agent-based, statistical, decision models to analyze sustainability questions about climate, human behaviour and the managment of natural as well as non-renewable resources
  • evaluate and report about the results of existing system dynamics and agent-based

Teaching methods

  • Lecture
  • Presentation/symposium
  • Working independently on e.g. a project or thesis
  • Computer lab session/practical training

During the lecture and guided discussion on Tuesdays, important concepts and ideas will be explained and the study material will be placed in context. There will also be in-class activities that help to understand the material

During each (computer) lab session on Wednesday, we will illustrate the theoretical ideas of the week in the context of a hands-on case study or a task.

Starting from week 3,  students will work on a modeling case-study in a group. During the lab sessions in weeks 2 to 6 groups will present and discuss the progress in their modeling project.

In lab session 7, at the end of the course, the groups will present their project results during a symposium.

Learning activities

Activity

Hours

 

lectures

14

 

(computer) labs

24

 

seminar

4

 

digital exam

4

 

modeling project

60

 

Self study

62

 

Total

168

(6 EC x 28 uur)

Attendance

Programme's requirements concerning attendance (OER-B):

  • Participation in fieldwork is compulsory and cannot be replaced by assignments or other courses.
  • In case of practical sessions, the student is obliged to attend at least of 90% of the sessions and to prepare himself adequately, unless indicated otherwise in the course manual. In case the student attends less than 90%, the practical sessions should be redone entirely.
  • In case of tutorials/seminars with assignments, the student is obliged to attend at least 7 out of 8 seminars and to prepare thoroughly for these meetings, unless indicated otherwise in the course manual. If the course has more than 8 seminars, the student can miss up to 1 extra meeting for every (part of) 8 tutorials/seminars. If the students attends less than the mandatory tutorials/seminars, the course cannot be completed.

Additional requirements for this course:

Attendance to lectures as well as practicals is mandatory. Out of the 14 scheduled lectures, 2 may be missed at maximum.

Assessment

Item and weight Details

Final grade

0.2 (20%)

presentation or summary of paper

Mandatory

0.3 (30%)

group modelling project

Mandatory

0.5 (50%)

digital exam

Mandatory

The digital exam will consist of open questions about the reading material, discussions during the lectures and practicals. The study-material is available during the exam and also personal notes (hard-copies) can be used at the exam. 

Assessment diagram

Leerdoel: digital exam: presentation/summary modeling project:
#1. x   x
#2. x x  
#3. x x  
#4.   x x
#5.   x x

Students that were enrolled in the course in previous years

The partial grades remain valid for 1 year.

Inspection of assessed work

When the partial grades are announced, students can inspect their assessed work, as well as the answer models (or assessment models) in Canvas and/or the testing environment.

Assignments

The quality of the modeling project is a group assignment. Feedback on he group assignment is given half-way of the project.

An example exam will be available by November 30.

Fraud and plagiarism

The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

Course structure

Weeknummer Onderwerpen Studiestof
1 basic modeling concepts Chapt. 2 of Keane 2009
2 system dynamics modeling tba
3 agent based modeling tba
4 decision modeling tba
5 statistical modeling tba
6 machine learning tba
7 presenting modeling projects -
8 exam -

Additional information

It is important that everyone feels safe at the UvA and Future Planet Studies. We are committed to provide social safety and we offer various forms of support for people experiencing inappropriate or unsafe situations. Consult the UvA website or Future Planet Studies Canvas page for more information and contact info.

Last year's student feedback

In order to provide students some insight how we use student feedback to enhance the quality of educatio, we include it here in combination with the ways by which it has been used to improve the course.

It is the first year that this course is provided and therefore we don't have any input yet this time.

Contact information

Coordinator

  • dr. ir. E.E. van Loon