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Unit outline_

FMBA5004: Nature of Systems

Intensive October - November, 2024 [Block mode] - Castlereagh St, Sydney

This unit aims to introduce the central concepts of systems thinking. Topics covered include micro-foundations of aggregate patterns, tools for systems modelling, scenario-based decision-making, network analysis and design thinking, data sources and new technologies to inform systems-orientated approaches. This unit provides students with an opportunity to use the systems approach to discover new ways of conceptualising complex enterprise problems and identifying innovative solutions to address complex, multi-dimensional and multi-scale issues.

Unit details and rules

Academic unit Management Education
Credit points 6
Prerequisites
? 
None
Corequisites
? 
FMBA5001
Prohibitions
? 
None
Assumed knowledge
? 

None

Available to study abroad and exchange students

No

Teaching staff

Coordinator Dirk Hovorka, dirk.hovorka@sydney.edu.au
Lecturer(s) Dirk Hovorka, dirk.hovorka@sydney.edu.au
The census date for this unit availability is 1 November 2024
Type Description Weight Due Length
Assignment Reflection
Written assessment
40% Formal exam period
Due date: 26 Nov 2024 at 23:59

Closing date: 02 Dec 2024
1000 words
Outcomes assessed: LO1 LO2 LO4 LO5
Small continuous assessment Weekly reflections
Written task
20% Multiple weeks 4 x 350 words
Outcomes assessed: LO1 LO5 LO4 LO3 LO2
Assignment group assignment Collaboration process document
Written assessment
0% Week 02
Due date: 24 Oct 2024 at 23:00

Closing date: 29 Oct 2024
4 pages
Outcomes assessed: LO1
Assignment Casual loop diagrams
Written assessment
10% Week 02
Due date: 24 Oct 2024 at 23:59

Closing date: 31 Oct 2024
1 diagram, 500 words
Outcomes assessed: LO1 LO5 LO4 LO3 LO2
Assignment group assignment Model a system and intervention
Video delivery
30% Week 06
Due date: 10 Nov 2024 at 23:59

Closing date: 11 Nov 2024
5 minutes
Outcomes assessed: LO1 LO5 LO4 LO3 LO2
group assignment = group assignment ?

Assessment summary

  • Weekly learning reflections: This assessment consists of participation in online discussion throughout the semester, in parallel to the lectures. Every week there will be a discussion topic relating previously introduced concepts to each team’s complex issue. Students will submit learning reflections to Canvas and to a weekly discussion thread on Canvas.
  • Causal loop diagrams: After introductory reading and class, students will explore suggested system phenomenon and then create a causal loop diagram and explanation.
  • Describe an intervention: In interdisciplinary groups, students will analyse current trends and dynamics in  suggested phenomenon and identify potential opportunities for intervention. Students will present recommendations in a short video, supplemented by a written appendix that maps key causal drivers, business environment and exogenous forces..
  • Collaboration process document: This assignment consists of two documents that summarise the development of the team
    assignment. Students will 1) prepare a team charter that outlines the groups’ approach and 2) submit their ‘meeting minutes’ to document regular meetings concisely. This assessment is not worth 'marks' by itself. Insead, NOT submitting it will result in a 10% reductionin the group project mark.
  • Reflection: In this assignment you will evaluate your own role and your team’s processes and dynamics during your development of your systems intervention. Building on relevant examples from your teamwork experience, analyse the ways of working with each other, including emergent norms, sources and flows of information, collaboration, joint learning and feedback. Applying suitable frameworks from the unit, you will critically reflect on your own role in the team and it’s dynamics and identify practical improvements for future team work.

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name

Mark range

Description

High distinction

85 - 100

Awarded when you demonstrate the learning outcomes for the unit at an exceptional standard, as defined by grade descriptors or exemplars outlined by your faculty or school. 

Distinction

75 - 84

Awarded when you demonstrate the learning outcomes for the unit at a very high standard, as defined by grade descriptors or exemplars outlined by your faculty or school.

Credit

65 - 74

Awarded when you demonstrate the learning outcomes for the unit at a good standard, as defined by grade descriptors or exemplars outlined by your faculty or school.

Pass

50 - 64

Awarded when you demonstrate the learning outcomes for the unit at an acceptable standard, as defined by grade descriptors or exemplars outlined by your faculty or school. 

Fail

0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

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.

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.

Support for students

The Support for Students Policy 2023 reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy 2023. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

WK Topic Learning activity Learning outcomes
Week 01 1. Introduction 2. Examples of complex systems approaches Workshop (4 hr)  
1. Emergence and self-organisation; 2. Introduction to modelling Workshop (4 hr)  
Week 02 1. Feedback systems thinking. 2. Causal loop models/landscapes. 3. Project Introduction Workshop (4 hr)  
1. Systems dynamics; modelling process and tools 2. Places to intervene Workshop (4 hr)  
Week 03 1. Group Project Work Workshop (4 hr)  
Week 04 1. Design and its consequences. Workshop (4 hr)  
1. Behavioural economics. Workshop (4 hr)  
Week 05 1. Social networks; 2. Teams as systems Workshop (4 hr)  
Week 06 1. Computer simulation and experiments Workshop (4 hr)  
Week 07 1. Wrap-up 2. Project videos on complex systems interventions Workshop (4 hr)  

Attendance and class requirements

Lecture recordings and attendance: Note that MBA classes held at the CBD Campus are not systematically recorded and 100% class attendance is expected for each unit of the MBA Program. If there are extenuating circumstances as to why you are not able to attend a particular class, please contact your unit coordinator as soon as possible, and also notify your group members (if the unit has a group work component). A unit requirement is 80% attendance, and those who drop below this level may not pass the unit.

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 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.

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

  • LO1. demonstrate a multi-level perspective to complex issues
  • LO2. understand key concepts of complex systems theory and their relevance in addressing complex problems
  • LO3. use suitable tools to understand health and related social and economic systems
  • LO4. integrate the expertise of multidisciplinary teams to identify novel solutions
  • LO5. apply theoretical concepts of complex systems thinking to a range of practical challenges.

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
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

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

No changes have been made since this unit was last 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.