Outline

Overview

This unit examines muscle and neural adaptations to high-resistance training (HRT, also known as strength training) in clinical and aged populations as well as in healthy adults. To understand these adaptations the basis of muscle force development is first examined in terms of myosin function and the structural organization muscle (e.g. myofilaments, sarcomeres, myofibrils, muscle fibers) and the neural processes involved in maximal voluntary contractions. Muscle hypertrophy in response to HRT is examined, and well as muscle atrophy in response to disuse. Neural adaptations to HRT and disuse are also discussed. The unit combines this biological approach with a parallel evidence-based development of practical guidelines for HRT prescription, and outcomes of HRT in randomised controlled trials (RCTs) and meta-analysis of RCTs in clinical conditions. Students gain skills in strength assessment in practical sessions, and in the prescription of HRT through participation in a brief HRT program. Students also gain skills in critical analysis of published RCTs examining HRT in clinical populations. Finally the unit examines concepts on muscle energy balance in terms ATP production and use during exercise, and the concepts of peripheral and central fatigue.

Unit details and rules

Academic unit	Movement Sciences
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	EXSS1036 and EXSS1040
Assumed knowledge ?	None
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Che Fornusek, che.fornusek@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
Written exam	Final Exam Short answer and MCQ	50%	Formal exam period	2 hours	AI prohibited
Outcomes assessed:
Out-of-class quiz	Quiz 1 Short answer and MCQ	5%	Week 03 Due date: 17 Aug 2026 at 23:59 Closing date: 21 Aug 2026	15 minutes	AI allowed
Outcomes assessed:
Written test	Mid-semester Exam In-class test with MCQ and short answer questions.	20%	Week 07 Due date: 14 Sep 2026 at 14:00 Closing date: 24 Sep 2026	1 hour	AI prohibited
Outcomes assessed:
Written work	Practical Report Written report	10%	Week 09 Due date: 09 Oct 2026 at 23:59 Closing date: 19 Oct 2026	4 A4 pages	AI allowed
Outcomes assessed:
Presentation	Evidence base presentation Oral presentation and power point slides (submitted prior in canvas).	15%	Week 10	15 minutes, 500 words	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

ONLINE QUIZ (Value: 5%) MCQ questions reviewing the previous 2 weeks lecture content. The quiz will take approximately 15 min to complete, but will be ‘open’ for four days.

MID-SEMESTER EXAM This is an in-class secure test (1 hour) which tests the lecture, practical, and tutorial material from weeks 1-6. The questions will be MCQ and Short Answer.

PRACTICAL REPORT: Group assessment (Value: 10%) Students will analyse data collected in Practicals. Report will use spreadsheet functions to determine group means, maximum and minimum values, and histogram plots. Reports will include short answer questions related to the interpretation of the data.

EVIDENCE-BASE PRESENTATION: Group assessment (Value: 15%) Students acquire skills evidence-based practice by evaluating and presenting a review of a randomised controlled trial (RCT) examining a high-resistance training intervention. The study is self-selected from a master list of studies in populations including healthy older-adult, frail elderly, a range of clinical conditions (including diabetes, CHF, CAD and COPD) and healthy young adults. All students in a group are expected to contribute to the live face-to-face presentation.

Attendance at the presentation session is compulsory. A pdf of your presentation slides is due on 13th October at 23:59. Changes to slides between that time and your presentation will result in marks deduction. Non-attendance of individual student in a group will result in that student receiving half marks for the presentation, in the absence of Special Consideration submission. Evidence of unequal contribution may result in marks deduction and evidence of non-contribution will result in an absent fail (AF). Further details on canvas.

FINAL EXAM (Value 50%) This will consist of short answer style questions. Content will cover the lecture and tutorial material from week 1-13.

Detailed information for each assessment can be found on Canvas.

Note: the Final Exam, the Mid-Semester Exam and the Evidence Base Presentation are compulsory assessment items. Students must attempt these assessments to avoid an Absent Fail

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 (HD)	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 (DI)	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 (CR)	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 (PS)	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 (FA)	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see sydney.edu.au/students/guide-to-grades.

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:

Practical report: 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
Week 01	1. Introduction to Strength and Training Principles	Lecture (2 hr)
Week 02	2. Why and how we train: Safety, Screening, and Muscle Basics	Lecture (2 hr)
Week 03	3. Muscle Structure and How Muscles Contract	Lecture (2 hr)
	-Tutorial 1	Tutorial (1 hr)
	-Practical 1: Introduction to Resistance Gym	Practical (1 hr)
Week 04	4. Muscle Types and How the Nervous System Controls Movement	Lecture (2 hr)
	-Tutorial 2	Tutorial (1 hr)
	-Practical 2: Resistance Training Practice	Practical (1 hr)
Week 05	5. How Training Changes the Nervous System and Muscles	Lecture (2 hr)
	-Tutorial 3	Tutorial (1 hr)
	-Practical 3: Resistance Training Practice	Practical (1 hr)
Week 06	6. Building Muscle: Adaptation and Recovery	Lecture (2 hr)
	-Practical 4: Resistance Training Practice	Practical (1 hr)
	-Tutorial 4:	Tutorial (1 hr)
Week 07	7. Mid-semester test [1 Hr] and 1 Hr lecture [What Happens When We Stop Training]	Lecture (2 hr)
	-Tutorial 5	Tutorial (1 hr)
	-Practical 5: Resistance Training Practice	Practical (1 hr)
Week 08	8. Applying Strength Training for Performance and Ageing	Lecture (2 hr)
	-Tutorial 6	Tutorial (1 hr)
	-Practical 6 (Buduwa 204): Elastic band training & muscle stimulation	Practical (1 hr)
Week 09	9. Public Holiday [Watch online lecture]	Lecture (2 hr)
Week 09	-Tutorial 7	Tutorial (1 hr)
Week 10	10. Energy Use in Short-Duration Exercise	Lecture (2 hr)
Week 10	Assessment - Student Presentation: Review of resistance training RTC	Tutorial (1 hr)
Week 11	11. Fast Energy Systems for Movement	Lecture (2 hr)
Week 12	12. Aerobic Energy and Muscle Metabolism	Lecture (2 hr)
Week 12	-Tutorial 8	Tutorial (1 hr)
Week 13	13. Review and revision: Applying knowledge to neurological conditions in growth, development and aging?	Lecture (2 hr)

Attendance and class requirements

Attendance: Students are encouraged to attend lectures, tutorials, and practicals.

The Week 10 presentations are group face-to-face presentations. All members of the group are required to participate in the presentation, i.e. each person has to participate in that presentation by speaking to some of the specific presentation slides. Evidence of unequal contribution may result in marks deduction and evidence of non-contribution will result in an absent fail (AF). Further details on canvas.

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 is no prescribed textbook for this unit. Content is referenced to primary research articles on a lecture-to-lecture basis. Some examples of core references are given below, however reading of these primary sources is not required. Links to references are available on Canvas.

Bickel CS et al. Exercise Dosing to Retain Resistance Training Adaptations in Young and Older Adults. Med Sci Sports Exerc 43: 1177 1187, 2011.
Egan, B., Sharples, A.P. Molecular responses to acute exercise and their relevance for adaptations in skeletal muscle to exercise training. Physiological Reviews 103; 2057-2170, 2023
Houston ME, et al Muscle performance, morphology and metabolic capacity during strength training and detraining: a one leg model. Eur J Appl Physiol 51 25 35 1983
Hubal MJ. et al. Variability in muscle size and strength gain after unilateral resistance training. Med Sci Sports Exerc. 37:964-72, 2005
Josse AR. et al Body composition and strength changes in women with milk and resistance exercise. Medicine & Science in Sports & Exercise. 42:1122-30, 2010.
Lopez, P., Radaelli, R., Taaffe, D.R., ... Häkkinen, K., Pinto, R.S. Resistance Training Load Effects on Muscle Hypertrophy and Strength Gain: Systematic Review and Network Meta-analysis. Medicine and Science in Sports and Exercise 53; 1206–1216, 2021
Mcleod JC et al. Resistance exercise training as a primary countermeasure to age-related chronic disease. Front Physiol. 10, 1-11, 2019
Wang N. et al. Muscle fiber types of women after resistance training — Quantitative ultrastructure and enzyme activity. Pflugers Archiv. 424:494 502, 1993.

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. Explain the limits to voluntary muscle force production in terms of both skeletal muscle structure and neural activation
LO2. Explain the neuro-muscular adaptations to high-resistance training in health, aging and disease
LO3. Explain the neuro-muscular adaptations to muscle disuse, aging and chronic disease states effecting skeletal muscle
LO4. Acquire skills in evaluating evidence-based guidelines for prescription of high-resistance training in health and disease
LO5. Acquire skills and experience in the assessment of maximal voluntary strength and in the prescription and evaluation of a high-resistance training program
LO6. Explain muscle energy metabolism in terms of ATP demand and supply and explain causes of fatigue during muscular exercise.

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.

Based on the thoughtful feedback we will continue with in-person lectures while further refining the material to reduce redundancy. We will support the complex topics with short, targeted recorded videos. Improvements to slide design are also recommended to enhance learning, clarity, and signposting. In addition, practical sessions and assessments should be strengthened to increase engagement and ensure that all students actively contribute to their group work. Students will be required to provide a reflection of their teammate’s effort.

Additional information

This unit of study may require you to attend a teaching activity timetabled in teaching venues installed with the University’s Clinical Recording and Observation System (CROS) in the Susan Wakil Health Building. Students should be aware of the privacy and information management implications of this system. For more information, please refer to the University’s Privacy Statement.

Student Administration Manual on the Faculty of Health Sciences

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

Disclaimer

On this page

Useful links

EXSS2030: Muscle Adaptations to Use and Disuse

Semester 2, 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

Disclaimer

On this page

Useful links