Prerequisite/Recommended prerequisite for participation in the module

For students in the MTec Risk and Safety Management – successful completion of 1st semester module Systems Engineering. All other students must send email to course leader prior to enrolling, detailing their motivation and academic and/or professional background.

Content, progress and pedagogy of the module

In this module students will learn how to integrate considerations of risk, resilience and sustainability into a common decision analytic framework for societal decision support from local to global scales. Taking basis in systems engineering, the module will focus on state-of-the-art methods for the modelling of combined engineered-ecological-social systems, Bayesian Probabilistic Nets (BPNs), consequential Life Cycle Assessment (LCA) and techniques of network systems analysis. Combining flipped classroom and PBL approaches, students will work in groups on a case study and deliver a digital portfolio of their investigation, which they will present in an oral presentation for a hypothetical decision-making client.

Learning objectives

Knowledge

• Demonstrate theoretical understanding of the concepts of systems resilience and quantitative sustainability and the trade-offs between them in the context of risk-informed decision support.
• Demonstrate theoretical understanding of concepts that underpin the scientific frameworks and methods for the joint assessment of risk, resilience and sustainability, including: system boundary, Planetary Boundaries, scale, temporality, (ir)reversibility, (non)linearity, limit, threshold, (de)growth, informational event, indicator, preference, option, action, consequence, utility, equity, accountability.
• Demonstrate theoretical understanding of differences between stated, revealed and informed preferences and how those impact the setting of objectives and the choice of metrics for integrated risk, resilience and sustainability assessment, management and governance.
• Demonstrate theoretical understanding of BPNs and their application in various decision contexts
• Demonstrate theoretical understanding of differences between attributional and consequential LCA and how they impact on system boundaries and systems modeling

Skills

• Ability to identify relevant preferences and objectives for risk, resilience and sustainability informed decision making for different stakeholders and at different time-space scales
• Ability to model and quantify resilience characteristics for simple combined engineered-ecological-social systems
• Ability to create a simplified framework for a consequential LCA in the context of a given case study
• Apply simple tools for consequential LCA
• Ability to define and analyze decision problems for simple combined engineered-ecological-social systems and to assess tradeoffs between risk, resilience and sustainability
• Ability to choose relevant indicators for monitoring a systems performance based on informed preferences

Competences

• Ability to use terms and concepts with clarity and precision
• Ability to communicate scientific results in a manner appropriate for different audiences: scientific peers, decision-makers, general public
• Ability to use data visualization tools for e.g., cluster analysis
• Ability to use digital media for e.g., wiki for project reporting
• Ability to conduct group project work in synchronous and asynchronous learning environments
• Ability to work in a social learning environment in accordance with PBL philosophy

Type of instruction

Flipped Classroom, Classroom-based and virtual discussion sessions, Hands-on workshops in relevant digital tools/software.

Extent and expected workload

The module is 5 ECTS which is corresponding to 150 hours of study.

Exam

Exams

Name of exam	Integration of Risk, Resilience and Sustainability
Type of exam	Written or oral exam Based on digital portfolio and oral exam presentation.
ECTS	5
Assessment	Passed/Not Passed
Type of grading	Internal examination
Criteria of assessment	The criteria of assessment are stated in the Examination Policies and Procedures

Additional information

Teaching assistants:

Jinjun Qin, Adj. Prof.,  jq@civil.aau.dk

Linda Nielsen, PhD Fellow, ln@civil.aau.dk