Unit outline_

EXSS2036: The Body Clock and Athletic Performance

Semester 1, 2025 [Normal day] - Camperdown/Darlington, Sydney

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
Chin Moi Chow, chin-moi.chow@sydney.edu.au
Tutor(s) Anju Verma, anju.verma@sydney.edu.au
Zohreh Sajadi Hezaveh, zohreh.sajadihezaveh@sydney.edu.au
The census date for this unit availability is 31 March 2025
Type Description Weight Due Length
Supervised exam
? 
EXSS2036 Final exam
MCQ and short-answer questions (2 hours plus 10mins reading time)
40% Formal exam period 2 hours
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7
Online task AI Allowed Online Quizzes
In-class online quizzes: Wk7 (3%), Wk9 (3%), Wk12 (4%).
10% Multiple weeks 20 - 40 minutes
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7
Tutorial quiz Early Feedback Task AI Allowed Early feedback task
In-class online quiz (#earlyfeedbacktask)
0% Week 03
Due date: 13 Mar 2025 at 18:00
20 minutes
Outcomes assessed: LO1 LO2
Presentation group assignment AI Allowed EXSS2036 Oral Presentation
Oral presentation in scheduled tutorial time on 2nd and 3rd April.
30% Week 06
Due date: 03 Apr 2025 at 23:59
10 minutes per Team
Outcomes assessed: LO4 LO5 LO6
Assignment group assignment AI Allowed 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: 17 Apr 2025 at 23:59
Video 5 min +/- 1 min
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7
group assignment = group assignment ?
AI allowed = AI allowed ?
early feedback task = 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

  1. Final exam: Written exam, short answer questions and MCQ. Worth 40%.
  2. 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.
  3. One in-class online Early feedback task (0%).
  4. Three in-class online quizzes worth a total of 10%.
  5. 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.

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) and automated writing tools

Except for supervised exams or in-semester tests, you may use generative AI and automated writing tools in assessments unless expressly prohibited by your unit coordinator. 

For exams and in-semester tests, the use of AI and automated writing tools is not allowed unless expressly permitted in the assessment instructions. 

The icons in the assessment table above indicate whether AI is allowed – whether full AI, or only some AI (the latter is referred to as “AI restricted”). If no icon is shown, AI use is not permitted at all for the task. Refer to Canvas for full instructions on assessment tasks for this unit. 

Your final submission must be your own, original work. You must acknowledge any use of automated writing tools or generative AI, and any material generated that you include in your final submission must be properly referenced. You may be required to submit generative AI inputs and outputs that you used during your assessment process, or drafts of your original work. Inappropriate use of generative AI is considered a breach of the Academic Integrity Policy and penalties may apply. 

The Current Students website provides information on artificial intelligence in assessments. For help on how to correctly acknowledge the use of AI, please refer to the  AI in Education Canvas site

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 Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

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

WK Topic Learning activity Learning outcomes
Week 01 Introduction to Unit of study Lecture: Sleep Lecture (2 hr) LO1
Week 02 Lecture: Overview of circadian rhythms; Sleep Lecture (2 hr) LO1
Practical: Chronotype and peak performance time Practical (2 hr) LO2 LO6
Week 03 Lecture: Sleep and exercise performance; sleep deprivation/restriction and sleep promotion Lecture (2 hr) LO1
Tutorial 1 Balancing the clock and the need: Exploring sleep homeostasis and circadian timing Tutorial (2 hr) LO1 LO2 LO4
Week 04 Lecture: Exercise on sleep; Keeping an internal sense of time Lecture (2 hr) LO1
Week 05 Lecture: Keeping an internal sense of time; The circadian molecular clock and circ rhythmicity Lecture (2 hr) LO2
Week 06 Lecture: Circadian alignment and misalignment. Oral presentation: Chronotype and performance. Presentation (2 hr) LO2 LO3 LO4 LO5 LO6
Week 07 Lecture: Variability in athletic performance 1 Lecture (2 hr) LO5 LO6
Tutorial 2 Rhythms of performance: Understanding the body’s clock for better sleep and training Tutorial (2 hr) LO1 LO2 LO5 LO6
Week 08 Lecture: Variability in athletic performance 2 Lecture (2 hr) LO5 LO6
Week 09 Lecture: Muscle damage and fatigue Lecture (2 hr) LO7
Tutorial 3 Circadian rhythm entrainment and disruption: Factors influencing alignment and re-alignment Tutorial (2 hr) LO1 LO2 LO5
Week 10 Lecture: Muscle damage and fatigue; strategies for recovery Lecture (2 hr) LO7
Week 11 Lecture: Circadian medicine 1 Lecture (2 hr) LO5
Week 12 Tutorial 4 Examining the relationship between exercise timing and muscle fatigue: How the skeletal muscle clock is affected by circadian disruption and the implications for athlete recovery strategies Tutorial (2 hr) LO3 LO5 LO7
Lecture: Circadian medicine 2 Lecture (2 hr) LO5
Week 13 Review lectures Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7

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

Recommended reading:

  1. Roenneberg, T., & Merrow, M. (2016). The circadian clock and human health. Current biology, 26(10), R432-R443.
  2. Roenneberg T, Wirz-Justice A, Merrow M. Life between clocks: daily temporal patterns of human chronotypes. J Biol Rhythms. 2003 Feb;18(1):80-90. doi: 10.1177/0748730402239679. PMID: 12568247
  3. Kantermann, T., & Burgess, H. J. (2017). Average midsleep time as a proxy for circadian phase. PsyCh journal, 6(4), 290-291.
  4. Chow CM. Sleep and wellbeing, now and in the future 2020. https://www.mdpi.com/1660-4601/17/8/2883
  5. Sandro Lecci, Jacinthe Cataldi, Monica Betta, Giulio Bernardi, Raphaël Heinzer, Francesca Siclari, Electroencephalographic changes associated with subjective under- and overestimation of sleep duration, Sleep, Volume 43, Issue 11, November 2020, zsaa094. https://doi.org/10.1093/sleep/zsaa094doi:10.1093/sleep/zsaa094
  6. Jelena Skorucak, Emma L Arbon, Derk-Jan Dijk, Peter Achermann, Response to chronic sleep restriction, extension, and subsequent total sleep deprivation in humans: adaptation or preserved sleep homeostasis?, Sleep, Volume 41, Issue 7, July 2018, zsy078, https://doi.org/10.1093/sleep/zsy078
  7. Rae, D. E., Chin, T., Dikgomo, K., Hill, L., McKune, A. J., Kohn, T. A., & Roden, L. C. (2017). One night of partial sleep deprivation impairs recovery from a single exercise training session. European journal of applied physiology, 117(4), 699-712.
  8. Shank SS, Margoliash D. Sleep and sensorimotor integration during early vocal learning in a songbird. Nature. 2009 Mar 5;458(7234):73-7. doi: 10.1038/nature07615. Epub 2008 Dec 14. PMID: 19079238; PMCID: PMC2651989.
  9. Kanaley JA, Weltman JY, Veldhuis JD, Rogol AD, Hartman ML, Weltman A. Human growth hormone response to repeated bouts of aerobic exercise. J Appl Physiol (1985). 1997 Nov;83(5):1756-61. doi: 10.1152/jappl.1997.83.5.1756. PMID: 9375348.
  10. Mah, C. D., Mah, K. E., Kezirian, E. J., & Dement, W. C. (2011). The effects of sleep extension on the athletic performance of collegiate basketball players. Sleep, 34(7), 943-950.
  11. Chow, C.M. Sleep Hygiene Practices: Where to Now? Hygiene 2022, 2(3), 146-151; https://doi.org/10.3390/hygiene2030013
  12. Vitale, J.A., Weydahl, A. Chronotype, Physical Activity, and Sport Performance: A Systematic Review. Sports Med 47, 1859–1868 (2017). https://doi.org/10.1007/s40279-017-0741-z
  13. Wright Jr, K. P., McHill, A. W., Birks, B. R., Griffin, B. R., Rusterholz, T., & Chinoy, E. D. (2013). Entrainment of the human circadian clock to the natural light-dark cycle. Current Biology, 23(16), 1554-1558.https://doi.org/10.1016/j.cub.2013.06.039
  14. Thorne, H. C., Jones, K. H., Peters, S. P., Archer, S. N., & Dijk, D. J. (2009). Daily and seasonal variation in the spectral composition of light exposure in humans. Chronobiology International, 26(5), 854-866.
  15. Kidd, P. B., Young, M. W., & Siggia, E. D. (2015). Temperature compensation and temperature sensation in the circadian clock. Proceedings of the National Academy of Sciences112(46), E6284-E6292.
  16. Wever, R. A. (1984). Properties of human sleep-wake cycles: parameters of internally synchronized free-running rhythms. Sleep7(1), 27-51.
  17. Jonathan S. Emens, Krista Yuhas, Jennifer Rough, Nidhi Kochar, Dawn Peters & Alfred J. Lewy (2009) Phase Angle of Entrainment in Morning and EveningTypes under Naturalistic Conditions, Chronobiology International, 26:3, 474-493, DOI: 10.1080/07420520902821077
  18. St Hilaire MA, Gooley JJ, Khalsa SBS, Kronauer RE, Czeisler CA, Lockley SW. Human phase response curve to a 1 h pulse of bright white light. The Journal of Physiology. 2012;590(13):3035-45.
  19. Youngstedt SD, Elliott JA, Kripke DF. Human circadian phase-response curves for exercise. J Physiol. 2019;597(8):2253-68.
  20. Eichner, E. R. (1988). Circadian timekeepers in sports. The Physician and sportsmedicine16(2), 78-85.
  21. Facer-Childs, E., & Brandstaetter, R. (2015). The impact of circadian phenotype and time since awakening on diurnal performance in athletes. Current biology25(4), 518-522.
  22. Facer-Childs, E. R., Middleton, B., Skene, D. J., & Bagshaw, A. P. (2019). Resetting the late timing of ‘night owls’ has a positive impact on mental health and performance. Sleep medicine60, 236-247.
  23. Vitale, J. A., & Weydahl, A. (2017). Chronotype, physical activity, and sport performance: a systematic review. Sports Medicine47(9), 1859-1868.
  24. Grgic, J., Lazinica, B., Garofolini, A., Schoenfeld, B. J., Saner, N. J., & Mikulic, P. (2019). The effects of time of day-specific resistance training on adaptations in skeletal muscle hypertrophy and muscle strength: A systematic review and meta-analysis. Chronobiology international, 36(4), 449-460. https://doi.org/10.1080/07420528.2019.1567524
  25. Allada, R., & Bass, J. (2021). Circadian mechanisms in medicine. New England Journal of Medicine, 384(6), 550-561. DOI: 10.1056/NEJMra1802337
  26. Ruan, W., Yuan, X. & Eltzschig, H.K. Circadian rhythm as a therapeutic target. Nat Rev Drug Discov 20, 287–307 (2021). https://doi.org/10.1038/s41573-020-00109-w

All readings for this unit can be accessed through the Reading List, available on Canvas.

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.

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
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

This section outlines changes made to this unit following staff and student reviews.

- We thank those who provided positive feedback and kind remarks. - The assignment has been changed from an infographic to a video podcast to offer a distinct learning experience and avoid duplication with EXSS2035.

 

Work, health and safety

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

Disclaimer

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