Outline

Overview

This introductory unit will provide students with skills and understanding of measurement and analysis core to becoming a proficient exercise professional. Students will learn technical skills for exercise data collection, the data handling, calculations and analytical approaches to examining data, and research methods used to collect evidence. Critical thinking approaches will be used to develop skills for assessing quality of evidence in exercise science. A focus Introduction to Exercise Science is the development of discrete skills and understanding of their application for accuracy.

Unit details and rules

Academic unit	Movement Sciences
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	OLET1514
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Kate Edwards, kate.edwards@sydney.edu.au
Lecturer(s)	Nathan Johnson, nathan.johnson@sydney.edu.au
Lecturer(s)	Michelle Hall, michelle.hall@sydney.edu.au
Tutor(s)	Helen Parker, h.parker@sydney.edu.au
	Kieron Rooney, kieron.rooney@sydney.edu.au
	Yorgi Mavrou, yorgi.mavros@sydney.edu.au
	Elizabeth Machan, elizabeth.machan@sydney.edu.au
	Heidi Morahan, heidi.morahan@sydney.edu.au
	Shane Ball, s.ball@sydney.edu.au
	Shaun Abbott, shaun.abbott@sydney.edu.au
	Suzie Mate, suzanne.mate@sydney.edu.au
	Kotryna Lewis, kotryna.lewis@sydney.edu.au
	Jeanette Thom, jeanette.thom@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	Final Exam Written exam including multiple choice and short answer questions.	30%	Formal exam period	1 hour	AI prohibited
Outcomes assessed:
Practical skill	IPL Introductory Workshop Complete pre-work, all 3 activity stations + post-workshop peer evaluation.	0%	Multiple weeks	Approx. 4-5hr incl workshop + homework	AI allowed
Outcomes assessed:
In-person practical, skills, or performance task or test	EFT Skill competency assessment Earn a badge (2%) for required skills #1	2%	Week 03	Ongoing	AI prohibited
Outcomes assessed:
Out-of-class quiz	Assignment Consent Matters: Online Consent Education Module Online module concerning sexual misconduct and gaining informed consent	0%	Week 06 Due date: 03 Apr 2026 at 23:59	1 hour	AI allowed
Outcomes assessed:
Out-of-class quiz	Academic Honesty Education Module Compulsory module to inform and assess academic integrity. Access in Canvas	0%	Week 06 Due date: 03 Apr 2026 at 23:59	1 hour	AI allowed
Outcomes assessed:
Interactive oral	Oral exam Oral exam, to include professional communication, and accurate assessments of clients including limitations, contraindications and modifications.	16%	Week 09	10 minutes	AI prohibited
Outcomes assessed:
In-person practical, skills, or performance task or test	Skill competency assessment Earn a badge (2%) for each of required skills #2-12	22%	Week 13	Ongoing	AI prohibited
Outcomes assessed:
Written work	Research report Pair or group of 3 critical appraisal of research article, including peer review	30%	Week 13 Due date: 29 May 2026 at 23:59 Closing date: 08 Jun 2026	2000 words report	AI allowed
Outcomes assessed:
= hurdle task ? = 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

***UNIVERSITY OF SYDNEY BARRIER TASKS***

Barrier tasks are compulsory items of assessment. If not completed, you will not receive your grade for the unit of study. Successful completion of ALL barrier tasks is required to receive a grade for this unit of study.

Interprofessional Learning (IPL) Introductory Workshop (0%): See the Interprofessional Learning (IPL) Canvas site for information about this compulsory task. Hurdle Task Information: Your final grade for EXSS1037 will only be released if you have completed the IPL Workshop and associated assessment activities. This includes:

- The completion of the Hand Hygiene certificate

- Attendance and participation in one (1) 2hr workshop

- Completion of the team Peer evaluation.

Academic Integrity Online Module (0%): See the Academic Honesty Education Module (AHEM) Canvas site for information about this compulsory module. Completion of the module is compulsory for all students commencing a new coursework degree, diploma or certificate, even if you have previously studied at university. Hurdle Task Information: Your final grade for EXSS1037 will only be released if you have completed the Academic Integrity Online Module.

Consent Matters (0%): See the Consent Matters Canvas site for information about this compulsory task. Hurdle Task Information: Your final grade for EXSS1037 will only be released if you have completed the Consent Matters online course.

If you have completed any of these barrier tasks in your previous enrolment and wish to seek an exemption, please contact the Unit of Study Coordinator with appropriate evidence of your completion of the task(s).

***UNIT OF STUDY ASSESSMENT TASKS***

Skills competency assessment (24%): Twelve (12) skills are assessed by tutors in tutorial and practical classes (ongoing assessment, with catch up time available in week 12 and 13).

The first skill badge (2%) must be attempted by week 3, this is the Early-Feedback Task.

A 'badge' for each skill can be earned by demonstrating competency (2% each). List of skills and rubric can be found on CANVAS. Special Consideration will not be approved for individual classes as catch up times are available. Failure to attempt the skills (that is, 0 skills attempted) will result in an AF grade being awarded for this unit of study.

Interactive Oral exam (16%): Week 9 NOTE this is in addition to normal lecture and prac classes, time to be booked on CANVAS: A 10 minute interactive oral exam will be completed in week 9, this will assess professional communication, and accurate assessments of clients including limitations, contraindications and modifications. Students will need to self-sign-up to a specific time for their assessment. Failure to attempt the assessment will result in an AF grade being awarded for this unit of study.

Students flagged for insufficent profession communication skills in this assessment will be referred to the Learning Hub and required to meet with the Unit Coordinator or delegate to discuss development.

Research report (30%): A written group assignment completed in groups of 2 or 3 students. Students submit a written report which consists of a critical appraisal of the quality of evidence journal articles provide, including a study quality checklist, and providing an evidence-based judgement on whether or not the findings should be incorporated into their clinical practice.

Completion of peer-evaluation of groupwork and reflection on teamwork will be assessed.

Standard late penalties apply.

For this report you are permitted to use generative AI to help you - this use must be acknowledged. For example it may be helpful to use AI tools such as Grammarly, Notion AI, ChatGPT, etc to directly suggest readability improvements to your text in terms of grammar and expression. You may choose to use tools such as elicit.org, perplexity.ai, and researchrabbit.ai to find and summarise research articles. You then need to incorporate the scholarship yourself in using the article you select for your report. The AI generated summary cannot be included in the submission.

Remember:

Do not enter confidential, personal, copyrighted or otherwise sensitive information into these tools. If you use these tools, you must be aware of their limitations, biases, and propensity for fabrication. Your use of AI tools must adhere to the Student Charter 2020, including upholding honesty, ethics, professionalism, and academic integrity.
Do not rely on the accuracy of outputs. You remain responsible for your work. This means you must independently verify and edit AI-generated content to ensure the integrity, accuracy, and suitability of the output.
If you use these tools, you must include a statement at the end of your assignment explaining what you used the tool for, and the prompts that you used. An example of what this might look like is: I acknowledge the use of researchrabbit.ai on to search for and summarise articles. We then selected the article we would use for our report. I used ChatGPT (https://chat.openai.com/) to refine the academic language of my own work. On I submitted my entire report () with the prompt to "Improve the academic tone and accuracy of language, including grammatical structures, punctuation and vocabulary”. The output () was then modified further to better represent my own tone and style of writing.

Final exam (30%): In person, 60 minute, written exam comprising MCQ and short-answer questions covering content from the entire unit of study. Includes questions from lectures, tutorials and practical class material. Week 15/16 (formal exam period). One sheet of A4 notes (double sided) will be permitted in the final exam

Assessment criteria

Result name	Mark range	Description
High Distinction	85-100%	Demonstrates extensive and thorough knowledge of exercise science principles and skills; demonstrates exceptional capacity to integrate complex concepts in exercise science; demonstrates high quality practical skills with ease and confidence.
Distinction	75-84%	Demonstrates thorough knowledge of exercise science principles and skills; demonstrates very good capacity to integrate complex concepts in exercise science; demonstrates high quality basic exercise science practical skills.
Credit	65-74%	Demonstrates good knowledge of exercise science principles and skills; demonstrates good capacity to integrate complex concepts in exercise science; demonstrates good capacity to perform basic exercise science practical skills.
Pass	50-64%	Demonstrates satisfactory knowledge of exercise science principles and skills; demonstrates some capacity to integrate complex concepts in exercise science; demonstrates satisfactory quality basic exercise science practical skills.
Fail	<50%	Does not demonstrate satisfactory knowledge of exercise science principles and skills; and/or, is not able to demonstrate capacity to integrate complex concepts in exercise science; is able to demonstrate satisfactory basic exercise science practical skills.
Absent Fail	0 to 49%	Fails to demonstrate the learning outcomes for the unit at an acceptable standard, or through failure to submit or attend compulsory assessment tasks. In cases where a student receives some marks but fails the unit through failure to attend or submit a compulsory task, or fails to achieve the minimum standard in applicable assessments (e.g. mid-semester written exam, practical exam), the mark entered shall be the marks awarded by the faculty up to a maximum of 49.

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:

For submitted work: Standard late penalties apply for the group assignment. Late penalties are a mark deduction (from the mark that would have been awarded for the quality of the work submitted) of 5% per day late or part thereof, to a maximum of 10 days (50% marks deduction), after which a grade of zero is awarded for that submission. Alternative assessments will only be conducted with approved Special consideration applications Please see https://sydney.edu.au/students/special-consideration.html for details on what events may constitute grounds for Special Consideration, and how to apply.

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 University, your degree and this unit, how to pass and be successful! The Exercise Professionals governing body - ESSA	Lecture (1 hr)
	Professional Practice 1: the role of the EP vs ES in the health system, introduction to informed consent ethical practise.	Lecture (1 hr)
	Intro to practicals, who are you? who are we? Transition to uni	Tutorial (2 hr)
Week 02	Pre-exercise screening, why and how	Lecture (1 hr)
	Data: How do we know what we know? Introduction to data	Lecture (1 hr)
	Resting measurements: HR, BP, Height, Mass, BMI	Practical (2 hr)
Week 03	How do we measure exercise? Quantifying work and power on an exercise bike	Lecture (1 hr)
	How do we measure exercise other than cycling? Measurement validity, and accuracy, importance of calibration	Lecture (1 hr)
	Using Excel to examine data: descriptive statistics and graphs	Tutorial (2 hr)
Week 04	Professional Practice 2: Professional attributes, need for knowing self, relationships to others, code of conduct	Lecture (1 hr)
	Data: How do you know if things are different or really just the same? Hypothesis testing and T-tests	Lecture (1 hr)
	Exercise measurements: HR and BP in response to steady-state cycling	Practical (2 hr)
Week 05	Professional Practice 3: Professional behaviours, communication, time management, teamwork, client centred practice	Lecture (1 hr)
	Professional Practice 4 - Reflection on personal experience and culture and initial reflection on others experience. Thinking about scope of culture aspects.	Lecture (1 hr)
	Using Excel to examine data: testing differences between groups or conditions	Tutorial (2 hr)
Week 06	The body's response to exercise: integrative physiology - getting the fuels in and the waste out	Lecture (1 hr)
	Data: How do we know if two things are related? Correlations and predictions	Lecture (1 hr)
	Exercise measurement: increasing exercise intensity responses	Practical (2 hr)
Week 07	The body's response to exercise: integrative physiology - getting oxygen in and carbon dioxide out.	Lecture (1 hr)
	The body's response to exercise: integrative physiology - ATP and how we make it	Lecture (1 hr)
	Using Excel to examine data: correlations. Thinking about evidence - what would you search for?	Tutorial (2 hr)
Week 08	Evidence: Where and how do we find evidence?	Lecture (1 hr)
	Evidence: what evidence do we use, and how do we trust it?	Lecture (1 hr)
	Measuring fitness: conducting sub-maximal exercise tests	Practical (2 hr)
Week 09	Maximal exercise intensity and VO2 max	Lecture (1 hr)
	Measuring maximal exercise capacity: a Max test in real time	Lecture (1 hr)
	Using Excel to examine data: how to predict VO2 max from data we collected	Tutorial (2 hr)
Week 10	Evidence: what evidence do you have? Research designs, quantitative and qualitative	Lecture (1 hr)
	Evidence: Is your evidence any good? Levels of evidence and quality appraisal	Lecture (1 hr)
	Measuring oxygen consumption, at rest and during exercise	Practical (2 hr)
Week 11	Consuming oxygen, calculating how much: VO2	Lecture (1 hr)
	Exercise efficiency: Link VO2 to energy expenditure, calculate exercise efficiency, what RER tells us about fuel.	Lecture (1 hr)
	Calculating VO2, the methods and the maths	Tutorial (2 hr)
Week 12	Evidence: Is your evidence any good, methods for critical appraisals, minimal clinically importance differences.	Lecture (1 hr)
	Evidence: Appraisal of evidence in Practice, RoB tools and interpretation for research report, citation approaches	Lecture (1 hr)
	Catch up time for skills badges	Practical (2 hr)
Week 13	Unit wrap up and final assessment: example of a marked EBP report	Lecture (1 hr)
	Final exam preparation	Lecture (1 hr)
	Catch up time for skills badges	Practical (2 hr)

Attendance and class requirements

While attendance at lectures, practical classes and tutorials is not compulsory, it is strongly recommended that students attend all allocated classes in order to keep up with the work, and to take the opportunity to ask questions of their teachers to clarify their understanding.

Without attending tutorial and practical classes it will be almost impossible to demonstrate competency in skill assessments.

In every class, you will be learning the building blocks that you will use for the remainder of your degree and beyond, so it is important to take your learning seriously and attend and participate in class as best as you can.

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

This unit of study has one prescribed textbook which coincides with the prescribed reading of EXSS1036, this textbook is:

Powers SK, Howley ET and Quindry J. Exercise physiology: Theory and application to fitness and performance. 11th edition. New York, NY: McGraw Hill LLC, 2021. NOTE: The 12th edition of this book has recently been released, and students may wish to obtain a copy of the more recent edition to support their future studies.

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.

At the completion of this unit, you should be able to:

LO1. Explain the roles of exercise professionals, understand the rationale for, and be able to apply risk stratification criteria in pre-exercise screening, and identify when further guidance is required prior to conducting a test.
LO2. Identify different ways to conduct accurate health, exercise, sport and physical activity assessments and begin to develop a critical analysis of their strengths.
LO3. Demonstrate an understanding of the limitations, contraindications or considerations that may require the modification of assessments.
LO4. Demonstrate practical competency to conduct pre-assessment procedures, select and conduct appropriate protocols for safe and effective assessments, including instructing clients on the correct use of equipment and obtaining measurements.
LO5. Develop basic professional skills including the ability to communicate in oral form effectively and provide written and graphical summaries of information from assessments, their limitations, and the interpretation of the results.
LO6. Begin to understand the requirement for evidenced-based models of practise based on how to conduct a critical analysis of quality of evidence, including the applications of qualitative and quantitative research study designs.
LO7. Understand, select and perform statistical analyses and interpret the results most relevant to Exercise Science data sets.

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

Alignment with Competency standards

Outcomes	Competency standards
	Accredited Exercise Scientist Professional Standards - 2024 - 1.2.2. Practice with integrity within the AES scope of practice and the ESSA Code of Professional Conduct and Ethical Practice, promote professional capabilities, and judge when to refer onwards. 1.2.3. Practice in line with relevant legislation and regulations including Australian Privacy Legislation, confidentiality, data security, informed consent, record-keeping, note taking and documentation. 1.2.6. Practice collaboratively within intraprofessional, interprofessional, and multidisciplinary teams, incorporating diverse perspectives and expertise to effectively address whole-person health and human performance needs. 4.2.2. Apply informed consent procedures, gather relevant medical and activity history, and conduct a pre-exercise risk assessment to ensure safety and suitability for activity.
	Accredited Exercise Scientist Professional Standards - 2024 - 4.2.4. Analyse and interpret information and results from assessments, including the accuracy and limitations of the assessments.
	Accredited Exercise Scientist Professional Standards - 2024 - 4.2.1. Explain the scientific rationale, reliability, validity, assumptions, and limitations of common health and exercise assessments and select appropriate equipment and digital practices based on individual needs.
	Accredited Exercise Scientist Professional Standards - 2024 - 1.2.4. Practice inclusively, respecting diverse backgrounds, including Aboriginal and Torres Strait Islander peoples, gender and sexually diverse persons, persons of culturally and linguistically diverse backgrounds, and those living with a disability. 4.2.1. Explain the scientific rationale, reliability, validity, assumptions, and limitations of common health and exercise assessments and select appropriate equipment and digital practices based on individual needs.
	Accredited Exercise Scientist Professional Standards - 2024 - 3.2.5. Exercise Physiology. Analyse and interpret physiological data obtained during acute exercise, and compare that data between time points, individuals, populations and environments.
	Accredited Exercise Scientist Professional Standards - 2024 - 2.2.15. Research Methods and Data Analysis. 2.2.15 Apply research methods and reports from a range of sources for a thorough understanding of research ethics and methodology in exercise science. 2.2.16. Research Methods and Data Analysis. Apply evidence-based practice that considers research evidence, emerging research, professional judgement, and client and service user preference. 2.2.17. Research Methods and Data Analysis. Examine research designs, their applications, and constraints, and apply data analysis methods as appropriate to evaluate outcomes within the context of exercise science settings.
	Accredited Exercise Scientist Professional Standards - 2024 - 2.2.17. Research Methods and Data Analysis. Examine research designs, their applications, and constraints, and apply data analysis methods as appropriate to evaluate outcomes within the context of exercise science settings. 3.2.5. Exercise Physiology. Analyse and interpret physiological data obtained during acute exercise, and compare that data between time points, individuals, populations and environments.

Accredited Exercise Scientist Professional Standards - 2024 -

Competency code	Taught, Practiced or Assessed	Competency standard
1.2.2		Practice with integrity within the AES scope of practice and the ESSA Code of Professional Conduct and Ethical Practice, promote professional capabilities, and judge when to refer onwards.
1.2.3		Practice in line with relevant legislation and regulations including Australian Privacy Legislation, confidentiality, data security, informed consent, record-keeping, note taking and documentation.
1.2.4		Practice inclusively, respecting diverse backgrounds, including Aboriginal and Torres Strait Islander peoples, gender and sexually diverse persons, persons of culturally and linguistically diverse backgrounds, and those living with a disability.
1.2.6		Practice collaboratively within intraprofessional, interprofessional, and multidisciplinary teams, incorporating diverse perspectives and expertise to effectively address whole-person health and human performance needs.
2.2.15		Research Methods and Data Analysis. 2.2.15 Apply research methods and reports from a range of sources for a thorough understanding of research ethics and methodology in exercise science.
2.2.16		Research Methods and Data Analysis. Apply evidence-based practice that considers research evidence, emerging research, professional judgement, and client and service user preference.
2.2.17		Research Methods and Data Analysis. Examine research designs, their applications, and constraints, and apply data analysis methods as appropriate to evaluate outcomes within the context of exercise science settings.
3.2.5		Exercise Physiology. Analyse and interpret physiological data obtained during acute exercise, and compare that data between time points, individuals, populations and environments.
4.2.1		Explain the scientific rationale, reliability, validity, assumptions, and limitations of common health and exercise assessments and select appropriate equipment and digital practices based on individual needs.
4.2.2		Apply informed consent procedures, gather relevant medical and activity history, and conduct a pre-exercise risk assessment to ensure safety and suitability for activity.
4.2.4		Analyse and interpret information and results from assessments, including the accuracy and limitations of the assessments.

Responding to student feedback

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

This unit was redesigned for 2025 and remains similar in 2026, we have removed in class tests and replaced them with a small final exam and an interactive oral exam to meet assessment security requirements. We have integrated practical data collection skills with data analysis skills, making the importance of data in the applied setting more obvious. We have also distributed assessment of practical and data skills in continuous assessment to reduce stress and emphasise competency. We are continuing a new tutorial support model, based on input from senior ES/EP students, and smaller tutorial class sizes to assist with the transition to university for first year students.

Additional information

Work, health and safety

Students must wear closed-in shoes (e.g. sneakers) to all practical classes. Students will be refused entry to practical class if closed-in shoes are not worn.

Students should come to practical class prepared to participate in [practical] learning activities and wear appropriate clothing accordingly. In addition, this may include the wearing of masks and other personal protective equipment as advised by the unit coordinator and tutors, according to the recommendations by NSW Health and University policies. Please practice good hand hygiene during class.

Students will complete a work, health and safety checklist before their first practical class. Any student who misses this WHS checklist must complete it before entering their first practical class.

Students must complete a pre-exercise screener (link available on Canvas) prior to exercise. Students with existing medical conditions that may confer a risk during exercise must seek clearance from their medical practitioner prior to undertaking exercise.

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

Alignment with Competency standards

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Work, health and safety

Disclaimer

On this page

Useful links

EXSS1037: Introduction to Exercise Science

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

Alignment with Competency standards

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Work, health and safety

Disclaimer

On this page

Useful links