Outline

Overview

This unit of study is designed to provide students an in-depth appreciation of the inter-connected world, its complexities and challenges, and the necessary systems-thinking and analytical skills to handle them. Globalisation, better transport, as well as technical and cultural exchanges have made the modern world truly interconnected, interdependent, and diverse. This interdependent structure and behaviour bring about significant new challenges associated with the design and management of complex systems. This unit will enable the students to tackle these challenges by providing them with the necessary systems-thinking, inter-disciplinary analysis, and leadership skills. The studied topics will include dynamical analysis of complex interdependent networks, local and global measures of network structure and evolution, cascading failures, as well as predictive measures of catastrophic failure in complex adaptive systems, and the tools that enable planning for resilient system design. This unit will equip future professionals with sufficient expertise and technical know-how for the design of efficient failure-prevention and intervention policies, and robust crisis forecasting and management.

Unit details and rules

Academic unit	Civil Engineering
Credit points	6
Prerequisites ?	must be in the Dalyell stream
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	Assumed level of preparedness includes an understanding of current issues of globalisation and interdependencies in modern world, across a range of domains, from engineering to economics to ecology to health security, caused by global economic volatility, high rates of urbanisation, limited habitable land areas, continuing climate variability, threats of pandemics, dispersed infrastructure, and long-range transport networks and supply chains.
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Mikhail Prokopenko, mikhail.prokopenko@sydney.edu.au
Lecturer(s)	Kyrylo Glavatskiy, kirill.glavatskiy@sydney.edu.au
Tutor(s)	Sheryl Chang, sheryl.chang@sydney.edu.au

Type	Description	Weight	Due	Length
Assignment	Home project Develop a network model and evaluate it. Write a report.	40%	Formal exam period	5 weeks
Outcomes assessed:
Assignment	Computing assignment Develop a system dynamics model in Vensim and write a report.	30%	Week 07	2 weeks
Outcomes assessed:
Assignment	Calculation Assignment Analyse a network and compute different network measures.	30%	Week 12	4 weeks
Outcomes assessed:

Assessment summary

Assessment feedback will be in written form via Turnitin and/or canvas, to each student individually, provided within two weeks of the
submission of relevant assessment.

The computing assignment will test the level of fluency the students have achieved with the systemd dynamics modelling software, Vensim, and their ability to use it effectively in analysis and design tasks.

Calculation assignment will test the grasp of students and in basic topological principles that they have learned in class, as well as have
qualitative questions to test the level of systems thinking, high level analysis and design, and written presentation skills of students.

The final assignment, home project, will test the grasp of key concepts that the students have achieved, their ability to apply these concepts in analytical and design tasks, as well as their ability to link these concepts to system level outcomes, and their ability to undertake systematic analysis to make predictions about the evolution of systems.

Assessment criteria

Final grades in this unit are awarded at levels of HD for High Distinction, DI (previously D) for Distinction, CR for Credit, PS (previously P) for
Pass and FA (previously F) for Fail as defined by University of Sydney Assessment Policy. Details of the Assessment Policy are available on the
Policies website at http://sydney.edu.au/policies . Standards for grades in individual assessment tasks and the summative method for obtaining a
final mark in the unit will be set out in a marking guide supplied by the unit coordinator.

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Weekly schedule

WK	Topic	Learning activity
Week 01	Introduction	Lecture and tutorial (3 hr)
Week 02	The interconnected world	Lecture and tutorial (3 hr)
Week 03	Topological analysis of networks - I	Lecture and tutorial (3 hr)
Week 04	Topological analysis of networks - II	Lecture and tutorial (3 hr)
Week 05	Cascading failures	Online class (3 hr)
Week 06	Robustness and resilience: Analysis and design	Online class (3 hr)
Week 07	Dynamics of Interconnected systems - I	Online class (3 hr)
Week 08	Dynamics of Interconnected systems - II	Online class (3 hr)
Week 09	Game theory and Interconnected systems	Online class (3 hr)
Week 10	Growth and evolution of networked system	Online class (3 hr)
Week 11	Modelling human societies as networks	Online class (3 hr)
Week 12	Modelling cyber-physical systems as networks	Online class (3 hr)
Week 13	Leadership and innovation in a globalised world through systems thinking	Online class (3 hr)

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. develop a high-level view (big picture thinking or systems-thinking) about how people and institutions interact together in achieving goals, and recognise identifiable patterns in such interactions
LO2. understand and appreciate the concepts of self-organisation and emergent behaviour, and how they influence and shape the dynamics of the interconnected world
LO3. appreciate the concept of ‘guided self-organisation’ as a novel approach to leadership and management of large systems
LO4. understand and appreciate the inter-connectedness of the world and its socio-technical and cyber-physical systems, the evolution of this inter-connectedness over time, and the advantages and disadvantages of this inter-connectedness.
LO5. Use elementary and intermediate computing skills to analyse, understand and simulate the dynamics of complex systems and interconnected systems
LO6. creatively use different systems-thinking approaches to model and present the complexity of interconnected systems in a meaningful way
LO7. understand the nature and dynamics of interdependent systems
LO8. apply topological analysis to a particular complex system to critically understand its structure
LO9. efficiently use existing software tools (e.g., Cityscape, Pajek ) in complex network analysis
LO10. design basic network structures that satisfy structural and functional criteria within given domains and contexts

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

This is the first time this unit has been offered.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect

Current students

ENGD3003: Complexity of the Interconnected World

Semester 1, 2020 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect