Outline

Overview

This unit focuses on developing an understanding of how circadian rhythm impacts athletic performance. The relationship between personal best performance and circadian phenotypes is examined through the predictors of peak performance time and optimal performance. There is an emphasis on the importance of aligning the body clock with the external environment for both health and sports performance. The unit also covers concepts of sleep as a performance enhancer, temporal variation in physiological variables, over-training, muscle damage and fatigue and recovery strategies.

Unit details and rules

Academic unit	Movement Sciences
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Chin Moi Chow, chin-moi.chow@sydney.edu.au
Lecturer(s)	Daniel Hackett, daniel.hackett@sydney.edu.au
Lecturer(s)	Chin Moi Chow, chin-moi.chow@sydney.edu.au
Tutor(s)	Kangchao Wu, kawu0609@uni.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
Written exam	EXSS2036 Final exam MCQ and short-answer questions (2 hours plus 10mins reading time)	40%	Formal exam period	2 hours	AI prohibited
Outcomes assessed:
In-class quiz	In-class Online Quizzes Online quizzes: Wk7 (3%), Wk9 (3%), Wk12 (4%).	10%	Multiple weeks	20 - 40 minutes	AI allowed
Outcomes assessed:
In-class quiz	Early feedback task In-class online quiz	0%	Week 03 Due date: 12 Mar 2026 at 23:59	20 minutes	AI allowed
Outcomes assessed:
Presentation	EXSS2036 Oral Presentation Oral presentation in scheduled tutorial times.	30%	Week 06 Due date: 02 Apr 2026 at 23:59	10 minutes per Team	AI allowed
Outcomes assessed:
Presentation	EXSS2036 Video Podcast in pairs. Video podcast as a supportive resource in engaging in learning activities. Evaluation will include a group mark for content and an individual mark for presentation skills.	20%	Week 08 Due date: 26 Apr 2026 at 23:59	Video 5 min +/- 1 min	AI allowed
Outcomes assessed:
= group assignment ? = early feedback task ?

Early feedback task

This unit includes an early feedback task, designed to give you feedback prior to the census date for this unit. Details are provided in the Canvas site and your result will be recorded in your Marks page. It is important that you actively engage with this task so that the University can support you to be successful in this unit.

Assessment summary

Final exam: Written exam, short answer questions and MCQ. Worth 40%.
Presentation (group): Oral presentation worth 30% (see details on Canvas for submission of slides etc). An Absent Fail (AF) will be awarded for non-contribution (therefore no submission) by a team member and deductions apply for students who have had a lesser contribution to others in the group.
One in-class online Early feedback task (0%).
Three in-class online quizzes worth a total of 10%.
Video podcast submission (evaluation will include a group mark for content and an individual mark for presentation skills) worth 20%

The early feedback task is not compulsory. Two of three in-class quizzes are required to be submitted to avoid an absent fail grade (AF). A submission is required for all other assessments to avoid an absent fail grade (AF). The details for assessment requirements will be available on CANVAS.

Group work: Individuals are responsible for keeping a record of their contributions and keeping these for 12 months. Students may be requested to submit these materials in response to an allegation of an academic integrity breach (Academic Integrity Policy 2022, Part 3 (7)).

Assessment criteria

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.

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:

Standard late penalties will apply for assessments that are not submitted on time unless a simple extension or special consideration is granted. An Absent Fail for the unit will be awarded for non-submission of any assessment.

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 Unit of study Lecture: Module 1: How cells keep time via genes and light.	Lecture (2 hr)
Week 02	Lecture: Module 1: How cells keep time via genes and light.	Lecture (2 hr)
Week 02	Practical: Chronotype and peak performance time	Practical (2 hr)
Week 03	Lecture: Module 1 and Module 2: How the clock runs the complex engine of sleep.	Lecture (2 hr)
Week 03	Tutorial 1 Balancing the clock and the need: Exploring sleep homeostasis and circadian timing	Tutorial (2 hr)
Week 04	Lecture: Module 2: How the clock runs the complex engine of sleep.	Lecture (2 hr)
Week 05	Lecture: Module 2 and Module 3: Why individuals experience time differently.	Lecture (2 hr)
Week 06	Lecture: Module 3 and Module 4: Applying circadian biology to athletic success.	Lecture (2 hr)
Week 06	Oral Presentation	Assessment (3 hr)
Week 07	Lecture: Module 4: Applying circadian biology to athletic success.	Lecture (2 hr)
Week 07	Tutorial 2 Sleep and skill acquisition	Tutorial (2 hr)
Week 08	Lecture: Module 4: Applying circadian biology to athletic success.	Lecture (2 hr)
Week 09	Lecture: Module 4: Applying circadian biology to athletic success.	Lecture (2 hr)
Week 09	Tutorial 3 Rhythms of performance: Understanding the body’s clock for better sleep and training.	Tutorial (2 hr)
Week 10	Lecture: Module 5: The health costs of misalignment.	Lecture (2 hr)
Week 11	Lecture: Module 6: Chronotherapy and future health directions.	Lecture (2 hr)
Week 12	Lecture: Module 6: Chronotherapy and future health directions.	Lecture (2 hr)
Week 12	Tutorial: Circadian rhythm entrainment and disruption: Factors influencing alignment and re-alignment	Tutorial (2 hr)
Week 13	Review lectures	Lecture (2 hr)

Attendance and class requirements

Attendance and participation are required for:

Week 2: Practical Session (+ select own team in class)

Week 3,7,9,12: Tutorial session + In-class online quiz + instruction/practice for video podcast(and selection of partner for this activity)

Week 6: Oral Presentation and submission of slides

Week 8: Submission of video podcast

Week 15/16 Final Exam

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

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. Demonstrate knowledge in the physiology of sleep and sleep as a performance enhancer
LO2. Comprehend the entrainment concept of the body clock and the external environment cue of light-dark cycle
LO3. Apply the knowledge of light and exercise as zeitgebers to phase-shifting and its application to circadian misalignments
LO4. Demonstrate competency in the skills of: a) reporting (data gathering, analysis and interpretation) b) oral presentation (organisation & visualisation; communication skills)
LO5. Recognise the impact of circadian timing on physiological, physical and cognitive performance
LO6. Understand the underlying chronotype on optimal athletic performance
LO7. Understand the circadian rhythms of muscle strength and fatigue and strategies for recovery

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.

In response to student feedback and suggestions, the lectures have been re-structured into six modules to facilitate systematic learning.

Additional information

Work, health and safety

The Work Health and Safety practical induction checklist must be completed by each student in consultation with the tutor.

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

Early feedback task

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

Work, health and safety

Disclaimer

On this page

Useful links

EXSS2036: The Body Clock and Athletic Performance

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

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Early feedback task

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

Work, health and safety

Disclaimer

On this page

Useful links