Outline

Overview

This unit will provide students with a grounding in the essential skills required for neurophysiology scientists to deliver high quality, safe and ethical care to their patients. Students will develop critical thinking and problem solving skills for a diverse range of scenarios which they may encounter within a clinical neurophysiology setting. Key ethical concepts and methods of ethical analysis, communication, quality control methodology, workplace health and safety, risk management and teaching skills required for effective work within the field will be discussed with a specific focus on their relationship to neurophysiological testing in both a clinical and intraoperative environment. Students with no neurophysiology workplace experience should undertake this unit towards the end of their course.

Unit details and rules

Academic unit	Clinical Neurophysiology
Credit points	6
Prerequisites ?	None
Corequisites ?	CLNP5001
Prohibitions ?	None
Assumed knowledge ?	Clinical neurophysiology experience is required for this unit. Students without clinical experience should enrol in CEPI5200
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Alison Szekely, alison.szekely@sydney.edu.au

Assessment

The census date for this unit availability is 1 September 2025

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Written work	Assignment 3 Assignment	20%	Formal exam period Due date: 17 Nov 2025 at 23:59	1500 words	AI allowed
Outcomes assessed:
Written work	Reflection and log book Log book	10%	Formal exam period Due date: 17 Nov 2025 at 23:59	See Canvas	AI allowed
Outcomes assessed:
Written work	Assignment 1 Assignment	20%	Mid-semester break Due date: 05 Oct 2025 at 23:59	1000 words	AI allowed
Outcomes assessed:
Contribution	Clinical discussions Online discussion	20%	Multiple weeks	600 words each	AI allowed
Outcomes assessed:
Written work	Assignment 2 Assignment	30%	Week 12 Due date: 02 Nov 2025 at 23:59	2000 words	AI allowed
Outcomes assessed:

Assessment summary

Clinical discussions: The clinical discussions are designed to help you understand and apply the theories and concepts covered within the modules. There will be 6 clinical discussions throughout the semester to be completed at the end of the relevant module.
Assignment 1: Assignment 1 is designed to help you synthesise and apply the knowledge you have gained in Modules 1-3.
Assignment 2: Assignment 2 is designed to help you consider opportunities for improvement within your practice or department, considering the risks of implementing new policies and/or procedures. You will be required to develop a risk management plan for the risks identified.
Assignment 3: Assignment 3 is designed to help you develop a learning and development plan for yourself or a student within your department or clinic.
Reflection and log book: The reflection and log book is designed to help you to reflect on how each module relates to your clinical practice in clinical neurophysiology.

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2021 (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	85 - 100
Distinction	75 - 84
Credit	65 - 74
Pass	50 - 64
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.

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	Module 1: Introduction to Patient Safety	Online class (10 hr)
Week 02	Module 1: Introduction to Patient Safety	Online class (10 hr)
Week 03	Module 2: Ethical Practice	Online class (10 hr)
Week 04	Module 2: Ethical Practice	Online class (10 hr)
Week 05	Module 3: Communication	Online class (10 hr)
Week 06	Module 3: Communication	Online class (10 hr)
Week 07	Module 4: Risk Identification and Management	Online class (10 hr)
Week 08	Module 4: Risk Identification and Management	Online class (10 hr)
Week 09	Module 5: Clinical Practice Improvement	Online class (10 hr)
Week 10	Module 5: Clinical Practice Improvement	Online class (10 hr)
Week 11	Module 6: Teaching and Training	Online class (10 hr)
Week 12	Module 6: Teaching and Training	Online class (10 hr)
Week 13	Revision and Assignments	Individual study (10 hr)
Week 14 (STUVAC)	Revision and Assignments	Individual study (10 hr)

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

All readings for this unit can be accessed through Canvas. The textbooks for this unit:

Textbook of Patient Safety and Clinical Risk Management by Donaldson, Liam; Ricciardi, Walter; Sheridan, Susan; Tartaglia, Riccardo 2021- First Edition
Patient Safety and Healthcare Improvement at a Glance by Panesar, Sukhmeet; Carson-Stevens, Andrew; Salvilla, Sarah; Sheikh, Aziz 2014
Healthcare Communication by Hugman, Bruce 2009
Handbook of Clinical Teaching by Mookherjee, Somnath; Cosgrove, Ellen M 2016

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. Describe key principles in safety and quality in health care and how they apply to neurophysiology clinical practice
LO2. Discuss key ethical concepts and their relevance to neurophysiology clinical practice
LO3. Demonstrate appropriate verbal and written communication with patients and their carers, colleagues and medical staff
LO4. Develop a risk management plan for a neurophysiology clinic
LO5. Plan a clinical practice improvement project
LO6. Create a professional development plan

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.

We value your feedback about any aspect of the unit of study and your experience as a student of Sydney Medical School. To help ensure our courses meet your needs and maintain a high standard, we welcome your feedback at any time and we ask you to complete the Mid-Semester Evaluation Survey and the Unit of Study Survey at the end of the semester. You can also rate any component of the unit using our star rating system found at the bottom of many pages as you progress through the unit. Your ratings and comments are anonymous and specifying what you liked and didn’t like about any of the learning materials, assessment items, discussion forums, feedback etc will help us to target our improvement efforts. Please note that your participation in this unit of study permits de-identified information about your learning experience and interaction with learning resources to be used for the purpose of improving the student learning experience.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links

CLNP5009: Neurophysiology Professional Practice

Semester 2, 2025 [Online] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links