Outline

Overview

How do we know what's out in the world? Indeed, how do we know anything at all? Sensing the world around us and turning that into a reliable representation that can guide behaviour and knowledge is fundamental to everything we do. The acts of `seeing' and `hearing' seem effortless and instantaneous, yet perception poses enormous challenges and is probably the most complex problem the brain must solve. In this course, you will learn how we see colour and movement, how we perceive surfaces and know materials, and how a robust perception must combine other senses such as sound, vision and touch, or taste and smell? You will also learn about the limits of perception, and surprisingly, how much it uses guesswork, prediction and filling-in to compensate. This unit draws on multiple perspectives (behaviour, neurophysiology, modelling, neuroimaging) to answer these questions and deepen your understanding of perception. The lecturers are all research-active leaders in the field and present the latest work on these research topics. In the advanced course, the tutorial component involves small groups taking a deep dive into key concepts at the forefront of the field, complemented by student presentations and discussion and some hands-on experience in a research lab.

Unit details and rules

Academic unit	Psychology Academic Operations
Credit points	6
Prerequisites ?	(A mark of 75 or above in PSYC2X10 or PSYC2X11 or PSYC2016) and PSYC2012
Corequisites ?	None
Prohibitions ?	PSYC3013
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	David Alais, david.alais@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
Written exam ?	Final Exam See Canvas for details.	40%	Formal exam period	2 hours	AI prohibited
Outcomes assessed:
In-class quiz	Lecture Quizzes An MCQ presented during the lecture on that lecture's content.	10%	Ongoing	See Canvas for details.	AI allowed
Outcomes assessed:
Written work	Research Report With methods and data provided to you, you will write up an experiment as a research article.	25%	Week 10 Due date: 19 Oct 2025 at 23:59 Closing date: 16 Nov 2025	See Canvas for details.	AI allowed
Outcomes assessed:
In-person written or creative task	Tutorial Quiz See Canvas for details.	15%	Week 12	45 minutes	AI prohibited
Outcomes assessed:
Presentation	Presentation See Canvas for details.	10%	Week 13	15 minutes	AI allowed
Outcomes assessed:
= hurdle task ?

Assessment summary

Lecture Quizzes: There will be one MCQ during each lecture on that current lecture's content. See Canvas for more details.

Tutorial Quiz: The Tutorial Quiz will assess the content from the tutorials in the form of multiple choice and/or short answer questions. If you miss the Tutorial Quiz, you may apply for Special Consideration, from which the outcome is a replacement assessment. See Canvas for more details.

Research Report: Students will be involved in several experiments - you will choose one to write up into a Research Report (in the form of a journal article) using a summary of methods and data to be provided to you. See Canvas for more details.

Presentation: Each student will make a brief presentation on a topic to be distributed. See Canvas for more details.

Final Exam: There will be a two-hour closed book exam held after the teaching period ends. If you miss the Final Exam and are approved by Special Consideration, you will sit a Replacement Exam during the Replacement Exam period. The Final Exam is a compulsory assessment, so if you do not attempt it, you will receive an Absent Fail (AF) grade, and it is also a hurdle assessment, so students will need to meet the required standard in order to pass the unit. See Canvas for more details.

Assessment criteria

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

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
Ongoing	See PSYC3013 outline for lecture schedule.	Lecture (25 hr)
Week 02	Introduction to perception and current research in perception labs	Tutorial (2 hr)
Week 03	The retina & receptive fields	Tutorial (2 hr)
Week 04	Natural images	Tutorial (2 hr)
Week 05	Serial dependence	Tutorial (2 hr)
Week 06	Hands-on experiments in perception labs	Tutorial (3 hr)
Week 07	Hands-on experiments in perception labs	Tutorial (2 hr)
Week 08	Action & proprioception	Tutorial (2 hr)
Week 09	Oscillations and predictive coding	Tutorial (2 hr)
Week 10	Theories & research on consciousness	Tutorial (2 hr)
Week 12	Tutorial Quiz	Tutorial (2 hr)
Week 13	Presentations	Tutorial (2 hr)

Attendance and class requirements

As noted in the Assessment table, the Final Exam is a compulsory assessment, so a student who does not attend it and is not approved to miss it will receive an Absent Fail (AF) grade.

Please note, marks for the Lecture Quizzes assessment are achieved by attending lectures, but there is no other consequence related to lecture attendance.

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. have a deep understanding of various areas of visual perception and a familiarity with auditory and tactile perception, too.
LO2. gain an understanding of the various research methods used in perceptual research and an understanding of the computational and neurophysiological underpinnings of perceptual processes.
LO3. gain an understanding of perceptual science, its methods, and how to present it to others.
LO4. (i) develop knowledge of several of the perceptual problems the brain must solve (such as combining information from distinct senses) (ii) Appreciation of common processing principles for how the brain solves perceptual problems (such as adaptation) (iii) Conceptual understanding of the limits on human perception and how they relate to the underlying mechanisms (such as acuity) (iv) Understanding of specific perceptual phenomena and how they arise as a consequence of processing architecture, especially in vision and audition (v) Basic knowledge of methods and measures commonly used in perception research (vi) Ability to understand and evaluate empirical studies in perception
LO5. (i) develop an understanding of the major methods of perceptual research (ii) Critically assess research findings and related theories in these areas (iii) Design and conduct basic studies to address perceptual questions: frame research questions; undertake literature searches; critically analyse theoretical and empirical studies; formulate testable hypotheses; operationalise variables; choose an appropriate methodology; make valid and reliable measurements; analyse data and interpret results; and write research reports.
LO6. (i) demonstrate an attitude of critical thinking that includes persistence, open---mindedness, and intellectual engagement. (ii) Evaluate evidence & information; differentiate empirical evidence from speculation. (iii) Think about how perception might be achieved mechanistically (iv) Evaluate issues using different theoretical and methodological approaches. (v) Use reasoning and evidence to recognise, develop, defend, and criticise arguments.
LO7. (i) develop an awareness of the applications of the theories and findings in the area. (ii) Apply psychological concepts, theories, and research findings to problems in everyday life and in society. (iii) Understand major areas of applied Perceptual Psychology.

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.

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

PSYC3913: Perceptual Systems (Advanced)

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