42826 Introduction to Complex Systems Modelling
Warning: The information on this page is indicative. The subject outline for a
particular session, location and mode of offering is the authoritative source
of all information about the subject for that offering. Required texts, recommended texts and references in particular are likely to change. Students will be provided with a subject outline once they enrol in the subject.
Subject handbook information prior to 2025 is available in the Archives.
Credit points: 3 cp
Result type: Grade and marks
Anti-requisite(s): 42082 Introduction to Complex Systems AND 42085 Modelling for Complex Systems
Description
This microcredential introduces learners to the notions of complexity and complex systems, and to the modelling of such systems. Complex systems have characteristics that make their behaviour very difficult, if not impossible, to predict. Certainly, traditional analytic approaches are not adequate in the realm of complex systems.
Modelling and simulation offer a way to explore such systems. Such models provide a window through which we may study the behaviour of complex systems, and of the impacts our interventions into these systems may have. When we think about just how prevalent complex systems are – from naturally occurring ecological systems, climate systems through to social, financial, communications and transport systems, we can begin to appreciate the importance and significance of complex system models and simulations.
This microcredential introduces learners to the essentials of modelling complex systems. There are many approaches that are popularly used for such modelling. This microcredential shows learners how to determine which approach may be more useful in a given situation. Students learn to look at a particular system and, through studying its characteristics, classify it. This is important when we are trying to model the system.
Subject learning objectives (SLOs)
Upon successful completion of this subject students should be able to:
| 1. | Explain what complex systems are and classify them according to their characteristics. (C.1) |
|---|---|
| 2. | Explain the role of models and simulations, and the key steps in modelling through a review of case studies involving applications of modelling of complex systems and analysis techniques. (B.1, D.1) |
Course intended learning outcomes (CILOs)
This subject also contributes specifically to the development of the following Course Intended Learning Outcomes (CILOs):
- Socially Responsible: FEIT graduates identify, engage, and influence stakeholders, and apply expert judgment establishing and managing constraints, conflicts and uncertainties within a hazards and risk framework to define system requirements and interactivity. (B.1)
- Design Oriented: FEIT graduates apply problem solving, design thinking and decision-making methodologies in new contexts or to novel problems, to explore, test, analyse and synthesise complex ideas, theories or concepts. (C.1)
- Technically Proficient: FEIT graduates apply theoretical, conceptual, software and physical tools and advanced discipline knowledge to research, evaluate and predict future performance of systems characterised by complexity. (D.1)
Teaching and learning strategies
This subject uses supported online learning strategies. Self-paced online learning material, including appropriate readings and videos.
Case studies help develop and reinforce the concept of complex systems and the techniques of modelling those. Students will learn about complex systems and their occurrence before studying ways to model them. Opportunities to reflect on the materials, engage in discussions and receive feedback are available throughout the modules.
Regular online consultations at times nominated on CANVAS and moderated discussion boards enable clarification of issues and peer/expert support for learning. Feedback on assessments, will also be available through the LMS.
Content (topics)
1. Introduction to complex systems
- Case study introduction
- Definition of systems
- System characteristics
- Complexity and complex systems
2. Introduction to Modelling
- What is a model and what does it do?
- Model characteristics
- The modelling process
Assessment
Assessment task 1: Identify a complex system
| Intent: | Allow students to demonstrate their ability to identify a complex system using methods studied in the subject |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): C.1 |
| Type: | Report |
| Groupwork: | Individual |
| Weight: | 30% |
| Length: | 1500-2500 words. |
Assessment task 2: Peer Feedback
| Intent: | Provide two sets of peer review. |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1 and 2 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): B.1, C.1 and D.1 |
| Type: | Report |
| Groupwork: | Individual |
| Weight: | 10% |
| Length: | 250-350 each |
Assessment task 3: Develop a model for your complex system
| Intent: | Demonstrate the ability to assess a complex system in its context, posit, and recommend and indicate how a model of such a system may be designed. |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1 and 2 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): B.1, C.1 and D.1 |
| Type: | Report |
| Groupwork: | Individual |
| Weight: | 60% |
| Length: | 1650-2350 words |
Minimum requirements
Overall mark of 50% or more.