Outline

Overview

The combined research project and dissertation offers students the opportunity to work on an individual research project exploring current problems and issues in a wide range of application areas that would benefit from an inter-disciplinary design research approach. It introduces students to design research methodologies and practices, including qualitative and quantitative approaches, data collection and analysis, and research protocols and procedures. Students can choose to follow one of the primary types of design research: design (a fundamental component of the research is the design and implementation of a strategy, intervention, or product) or empirical (empirical data gathering is required to understand a phenomenon, practice or method). Students will produce a research proposal including the research aims, objectives, and questions of the project, a literature review of the topic being examined, the project's research methodology and methods and a project timeline. The project is written up into a research dissertation, and may include evidence and documentation of Built Work. A single result is given for the combined project and dissertation.

Unit details and rules

Academic unit	Design Lab
Credit points	12
Prerequisites ?	IDEA9106 and 18 credit points from (DESN9003 and DESN9100) or (DESN9004 and DESN9200)
Corequisites ?	DESN9203
Prohibitions ?	None
Assumed knowledge ?	DESN9001 or DESN9002
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Hao Zhou, hao.zhou@sydney.edu.au

Assessment

The census date for this unit availability is 1 September 2025

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Experimental design	Research proposal Research proposal (written)	10%	Week 03	2000 words	AI allowed
Outcomes assessed:
Interactive oral	Interactive Oral Assessment Interactive Oral assessment	20%	Week 07	15 minutes (oral)	AI prohibited
Outcomes assessed:
Dissertation or thesis	Research dissertation Written dissertation	70%	Week 13	10,000-15,000 words	AI allowed
Outcomes assessed:

Assessment summary

Research proposal: The first assignment involves preparing a research proposal, describing your research topic, identification of a gap, the research aims and questions, scope, intended outcomes, annotated bibliography, research design, a timeline and risk analysis.
Interactive Oral Assessment: The second assignment involves participating in a 1:1 interactive session with a tutor to discuss how you developed your your research proposal and your peer reflections on the poster exhibition and presentations.
Research report: This is a written assignment that describes the motivating context for the research, research aims and questions, scope, literature review, research methodology /methods, results and findings, evaluation, main outcomes and knowledge contributions.
Attendance hurdle tasks: Weekly hurdle tasks are used to support attendance and contribute to a productive peer-learning environment. Hurdle tasks include in-progress presentations, poster creation and exhibition, and peer review activities.
Detailed information for each assessment can be found on Canvas.
Note: For students taking this unit in conjunction with another, a single mark is awarded for both units.
Attendance: 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 approved special consideration may be offered the opportunity to sit an alternative assessment to pass this unit.

Assessment criteria

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 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.

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
Week 01	Introduction to design research	Lecture and tutorial (3 hr)
Week 02	Design research methods and methodologies	Lecture and tutorial (3 hr)
Week 04	Ethics and integrity in design research	Lecture and tutorial (3 hr)
Week 05	Poster presentation and peer review	Presentation (3 hr)
Week 07	Interactive oral assessment	Presentation (3 hr)
Week 09	Communicating your research	Lecture and tutorial (3 hr)
Week 10	Research with impact	Lecture and tutorial (5 hr)
Week 12	Final project presentations	Presentation (3 hr)

Attendance and class requirements

Attendance: All Capstone research students are expected to attend all sessions of the research seminar. You must attend the compulsory sessions in Week 1 – Intro, Week 5 – Research Proposal Presentation, and Week 12 – Final Project Presentation. The aim of the Research Seminar is to provide a group environment where supervision, discussion, exchange and peer learning take place. These are complemented by weeks devoted to one-one supervision, where the student meets with their supervisor to discuss the progress of their project and receive guidance on their research.
Booking supervision meetings: Each student has 7 x 30 minutes = 3.5 hours for supervision meetings. It is up to the student to negotiate suitable times with their supervisor. It is advisable to do this at the start of semester, as supervisors are busy with other academic duties. Do not leave it to the day before to book a meeting, as it is likely that your supervisor will not be available at such short notice.

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.

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. Plan, scope and manage an independent research-based project
LO2. Critically engage with published scholarship and trusted sources of data to identify gaps and contributions in knowledge
LO3. Select and apply appropriate research methods to answer research questions
LO4. Communicate persuasively through diverse forms of media the value and validity of design research proposals, findings and solutions to specialist and non-specialist audiences
LO5. Work independently, with an ability to make independent judgements, reflect, self-evaluate and self-improve, and incorporate the feedback of others

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.

Assessments updated

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

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

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links

DESN9204: Design Dissertation

Semester 2, 2025 [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

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links