Outline

Overview

Architecture Research Areas familiarises students with three broad research areas: architectural design; architectural theory and history; and architectural technologies. Academics with differing backgrounds and approaches to architectural research contribute to a suite of lectures, discussing their own projects and initiatives within the broader context of their research area. Students come to understand theoretical underpinnings affiliated with each area and become conversant with their contemporary concerns and methodologies. They conduct a limited-scope research project of their own enabling them to pursue their own emerging area of interest in architectural research.

Unit details and rules

Academic unit	Architecture
Credit points	6
Prerequisites ?	BDES2028
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Rebecca McLaughlan, rebecca.mclaughlan@sydney.edu.au

Assessment

The census date for this unit availability is 31 August 2026

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Research analysis	Planning an architectural research project Written assessment	60%	Formal exam period Due date: 20 Nov 2026 at 23:59	2500 words	AI allowed
Outcomes assessed:
Research analysis	Selecting appropriate methods for architectural research Written assessment	40%	Week 09 Due date: 09 Oct 2026 at 23:59	1500 words	AI allowed
Outcomes assessed:
Attendance - accreditation or faculty requirement	Hurdle requirement: attendance As per School Policy, 90% attendance to scheduled activities is mandatory to pass this unit of study.	0%	Week 12 Due date: 30 Oct 2026 at 11:59	Throughout semester	Not applicable
Outcomes assessed:
= hurdle task ?

Assessment summary

In Assessment 1 students will analyse 2 journal articles relative to an individual research topic of interest; and demonstrate an understanding of how different methods and approaches to their topic of choice would deliver different kinds of knowledge outcomes.
In Assessment 2 students will propose a detailed plan for undertaking a programme of research. This plan needs to include justification/ positioning of the research topic of interest; judicious selection of a method and sources for undertaking the research; and state who would benefit from it (e.g. who is the audience, how will they use it?).

Detailed information regarding each assessment can be found on Canvas.

Regarding the Responsible Use of AI: to understand what appropriate and responsible uses of AI might be for this subject, refer to the lecture provided on Canvas, which also provides a template for acknowledgement of use. A failure to explicitly acknowledge any and all uses of AI in your assessment tasks is tanamount to plagiarism and will be treated as such.

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 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:

In accordance with University policy, late penalties apply when written work is submitted after 11:59pm on the due date: A deduction of 5% of the maximum mark for each calendar day after the due date. After 10 calendar days, 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
Pre-semester	Log onto Canvas pre-semester to watch the following on-line mini lectures: (1) Welcome to Architectural Research Areas (2) Using AI responsibly in architectural research. (3) Case studies versus ordinary studies - there's actually a difference!	Self-directed learning (0.5 hr)
Week 01	Using architectural precedents	Lecture (1 hr)
Week 01	as above	Tutorial (2 hr)
Week 02	Spatial / ethnographic observations	Lecture (1 hr)
Week 02	as above	Tutorial (2 hr)
Week 03	Archival sources & mixed methods	Lecture (1 hr)
Week 03	as above	Tutorial (2 hr)
Week 04	Migrating Ideas Symposium, State Library NSW (students to attend only; 9.30-12.30pm, *please note the slight time change)	Lecture (3 hr)
Week 05	Working intensively with archives	Lecture (1 hr)
Week 05	as above	Tutorial (2 hr)
Week 06	Autoethnography / understanding practice	Lecture (1 hr)
Week 06	as above	Tutorial (2 hr)
Week 07	Engaging end users	Lecture (1 hr)
Week 07	as above	Tutorial (2 hr)
Week 08	Creative methods in research	Lecture (1 hr)
Week 08	as above	Tutorial (2 hr)
Week 09	Using literature to position an argument	Lecture (1 hr)
Week 09	as above	Tutorial (2 hr)
Week 10	Broader histories of architecture	Lecture (1 hr)
Week 10	as above	Tutorial (2 hr)
Week 11	NONE: Week 11 is a scheduled WELLNESS BREAK (no lecture or tutorial) to enable you to focus on your studio submission.	Self-directed learning (3 hr)
Week 12	ONLINE SYMPOSIUM (students to present): Formative Presentations (i.e. not marked) to provide you with critical feedback for Assignment 2 (5 mins pres + 7 mins feedback). These will be scheduled throughout the day in 3 streams: 8.30-11.30, 12.00-3.00 & 3.30-6.00 (individual times to be confirmed, online attendance is required for your 3 hour timeslot but attendance throughout the day is encouraged).	Assessment (8.5 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.

Required readings

There are required readings for Weeks 2-10 - these MUST BE COMPLETED BEFORE each week's lecture - please refer Canvas (both the Course Schedule and Reading List contain these details).

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. understand diverse research methods from architectural design, architectural history, architectural science, and other affiliated fields in relation to a research question.
LO2. articulate a clear, original argument about architecture through research.
LO3. evaluate a range of research methods using primary sources, secondary sources and other modes of documentation.
LO4. frame and plan an architectural research project with appropriate sources.
LO5. identify and review critical and relevant academic sources in order to position an architectural research project.
LO6. communicate and engage with peers through high level academic discussions.

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.

The current iteration of the course was piloted in 2024, with a view to better preparing students for the capstone semester through a more explicit focus on the design and application of various research methods. Students confirmed this was useful and wide-ranging. Given that writing an 8000-word dissertation for the first time (in ARCH4010) can be challenging, this unit focuses on: • Developing your understanding the close relationship of research questions to methods and approaches in achieving high quality research outcomes. This requires you to develop an understanding of the whole smorgasbord of methods that are available for undertaking architectural research. • Developing an understanding of how to read academic literature properly – what to think about, what to pay attention to, what to question – because it’s mostly through this process that we learn to position and to structure a convincing research argument.

Additional information

Additional costs

No additional costs are anticipated for completing this course.

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

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

ARCH4008: Architecture Research Areas

Semester 2, 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

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