6 ECTS credits
152 h study time
Offer 1 with catalog number 4021209FNR for all students in the 2nd semester at a (F) Master - specialised level.
Despite the increased popularity of the use of the term "sustainability", the possibility that human societies will achieve environmental sustainability remains a major challenge in light of environmental degradation, climate change, overconsumption, population growth and societies' pursuit of indefinite economic growth in a closed system. In the course Decision Support for Sustainability, students will learn tools, models and instruments that enable to measure and improve the sustainability of products, measures and processes and helps them formulate recommendations and improvements.
Within this course we learn about rather 'hard methods' moving gradually towards the more 'soft methods'. Hard methods can be understood as very applicable, quantitative and hands-on tools, such as life-cycle assessment (LCA) and external cost calculations. Soft methods are more oriented towards participation and the human side of the transition, such as multi actor, multi-criteria analysis (MAMCA) and foresight methods.
The course is designed as a ‘flipped classroom’. The theory is provided through knowledge clips and/or other material on Canvas and covers the context and the methods. Students are expected to watch the clips before the on-campus workshops, where the theory is put into practice through exercises, group work, debate, etc.
The student understands the basic principles of sustainability and recognizes the possibilities of deploying quantitative and qualitative research methods that enable decision support for relevant stakeholders in order to improve sustainability.
The student is able to identify the appropriateness of using a particular decision support methodology on real world problems, The student can apply the method to the problem and knows the strenghts and weaknesses of each method.
The student is able to contribute in a team with other students to solve problems during class exercises and is also able to work together in groups from two to four students during the task preparation.
The student is able to individually present the outcomes of a critical analysis
The final grade is composed based on the following categories:
Written Exam determines 70% of the final mark.
Other Exam determines 30% of the final mark.
Within the Written Exam category, the following assignments need to be completed:
Within the Other Exam category, the following assignments need to be completed:
Both assessment forms (that is, the written exam and assignment) are required to pass this course. For the second session, we keep the grade of the assignment if it was passed in the first session, then only the exam is required.
AI Usage Policy for the written assignment:
In this course, students are permitted to use artificial intelligence (AI) tools for spelling and grammar correction to enhance the clarity and coherence of their writing. Additionally, AI may be used to summarize academic papers and generate citations, provided that students verify the accuracy of AI-generated references against original sources. The use of AI for content generation, idea development, or any form of substantive writing assistance beyond these specified purposes is strictly prohibited. Students must ensure that all submitted work reflects their original thoughts and analysis, maintaining academic integrity and the authenticity of their individual contributions.
Students are required to disclose any use of AI in their assignments by including a statement such as: "AI tools were used for spelling and grammar correction, summarizing academic papers, and/or generating citations in this document." Any misuse of AI tools beyond the allowed scope or failure to disclose AI use will be considered a violation of academic policies.
This offer is part of the following study plans:
Master of Business Engineering: Standaard traject (only offered in Dutch)
Master of Business Economics: Standaard traject (only offered in Dutch)
Master of Urban Studies: Standard track
Master of Biology: Ecology and Biodiversity
Master of Biomedical Engineering: Profile Radiation Physics
Master of Biomedical Engineering: Profile Biomechanics and Biomaterials
Master of Biomedical Engineering: Profile Sensors and Medical Devices
Master of Biomedical Engineering: Profile Neuro-Engineering
Master of Biomedical Engineering: Standaard traject
Master of Biomedical Engineering: Profile Artificial intelligence and Digital Health
Master of Sustainable Land Management: Urban Land Engineering
Master of Sustainable Land Management: Abridged Program AR UrbLandEng