Outline

Overview

The Planning Dissertation is a capstone unit involving the completion of a substantial piece of independent research undertaken under academic supervision. The unit provides students with the opportunity to investigate an approved topic in urban and regional planning or policy in depth, and to apply advanced research skills to a clearly defined planning problem or question. Through the development of a research question, project scope and research design, students will undertake a critical review of relevant literature and conduct primary and/or secondary research using appropriate methodologies. The unit emphasises analytical rigour, ethical research practice, and the synthesis of evidence to generate original insights relevant to planning theory, policy and professional practice. The Planning Dissertation is particularly suited to students seeking to deepen their analytical and research capabilities and provides a strong foundation for those considering further academic research, policy analysis, or advanced professional practice in urban and regional planning.

Unit details and rules

Academic unit	Urban and Regional Planning and Policy
Credit points	12
Prerequisites ?	None
Corequisites ?	PLAN9010
Prohibitions ?	None
Assumed knowledge ?	PLAN9068, PLAN9061, PLAN9063, PLAN9045, PLAN9064, ARCH9100
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Sandy Burgoyne, sandy.burgoyne@sydney.edu.au

Assessment

The census date for this unit availability is 31 March 2026

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Dissertation or thesis	Dissertation or Thesis A written and designed dissertation or thesis	100%	Week 13 Due date: 25 May 2026 at 23:59	25000 words + maps, tables, figures etc	AI allowed
Outcomes assessed:

Assessment summary

Assessment 1: Dissertation or Thesis

Students should be present and engaged in their learning during classes. Late arrival/early departure will be deemed as an absence. Students who do not meet the minimum 90% threshold, who have reasonable evidence to support their absence, may be offered the opportunity to sit an alternative assessment to pass this unit at the discretion of the unit coordinator.

Detailed information for each assessment, including instruction for submission of different parts, 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	Work of outstanding quality, demonstrating mastery of the learning outcomes assessed. The work shows significant innovation, experimentation, critical analysis, synthesis, insight, creativity, and/or exceptional skill.
Distinction	75 - 84	Work of excellent quality, demonstrating a sound grasp of the learning outcomes assessed. The work shows innovation, experimentation, critical analysis, synthesis, insight, creativity, and/or superior skill.
Credit	65 - 74	Work of good quality, demonstrating more than satisfactory achievement of the learning outcomes assessed, or work of excellent quality for a majority of the learning outcomes assessed.
Pass	50 - 64	Work demonstrating satisfactory achievement of the learning outcomes assessed.
Fail	0 - 49	Work that does not demonstrate satisfactory achievement of one or more of the learning outcomes assessed.

For more information see sydney.edu.au/students/guide-to-grades

For more information see guide to grades.

Use of generative artificial intelligence (AI)

You can use generative AI tools for open assessments. Restrictions on AI use apply to secure, supervised assessments used to confirm if students have met specific learning outcomes.

Refer to the assessment table above to see if AI is allowed, for assessments in this unit and check Canvas for full instructions on assessment tasks and AI use.

If you use AI, you must always acknowledge it. Misusing AI may lead to a breach of the Academic Integrity Policy.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

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.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

As per ADP policies and procedures.

Academic integrity

The University expects students to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

Our website provides information on academic integrity and the resources available to all students. This includes advice on how to avoid common breaches of academic integrity. Ensure that you have completed the Academic Honesty Education Module (AHEM) which is mandatory for all commencing coursework students

Penalties for serious breaches can significantly impact your studies and your career after graduation. It is important that you speak with your unit coordinator if you need help with completing assessments.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

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.

Support for students

The Support for Students Policy 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. 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

Weekly schedule

WK	Topic	Learning activity
Multiple weeks	Supervisory meetings	Tutorial (13 hr)
Week 01	Introduction to the Unit	Lecture (1 hr)
Week 02	Knowledge and Research Process	Lecture (1 hr)
Week 03	Theory and Why Theorise.	Lecture (1 hr)
Week 05	Literature Reviews	Lecture (1 hr)
Week 06	Graphic Representation of Research	Lecture (1 hr)
Week 08	Writing Results and Analysis	Lecture (1 hr)
Week 09	Referencing and AI	Lecture (1 hr)
Week 13	Industry Panel	Lecture (1 hr)

Attendance and class requirements

Please refer to the Resolutions of the University School: University of Sydney School of

Architecture Design and Planning Faculty Resolutions 2022

Clause 8 (3) (a). Students are expected to attend a minimum of 90% of timetabled activities for each unit of study, unless granted exemption.

https://www.sydney.edu.au/policies/showdoc.aspx?recnum=PDOC2022/542&RendNum=0

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 12 credit point unit, this equates to roughly 240-300 hours of student effort in total.

Required readings

See Canvas for additional resources.

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. Identify, evaluate and synthesise relevant scholarly, policy and professional literature to situate an urban or regional planning problem within its theoretical and empirical context.
LO2. Critically formulate and refine a clear and feasible research question addressing a significant planning or policy issue.
LO3. Design and justify an appropriate scope, structure and research design for an independent thesis project that is achievable within defined constraints.
LO4. Select, apply and reflect on suitable research methodologies and analytical approaches consistent with disciplinary standards and ethical requirements.
LO5. Undertake, analyse and synthesise primary and/or secondary research data to generate original and well-supported insights relevant to planning policy or practice.
LO6. Communicate and defend research processes, findings and conclusions effectively in written and oral forms that demonstrate advanced academic and professional competence.

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.

Student feedback has been taken into consideration since this unit was last offered.

Additional information

All information for this unit will be on the designated Canvas site.

Canvas:

Additional costs

Some small costs may be incurred by the student in the production of the report/research proposal (such as for graphics,images, maps, etc).

Disclaimer

Important: the University of Sydney regularly reviews units of study and reserves the right to change the units of study available annually. To stay up to date on available study options, including unit of study details and availability, refer to the relevant handbook.

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

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Additional costs

Disclaimer

On this page

Useful links

PLAN9011: Planning Dissertation 2

Semester 1, 2026 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Additional costs

Disclaimer

On this page

Useful links