Unit outline_

OPSC5030: Medical Retina

Semester 1, 2025 [Online] - Camperdown/Darlington, Sydney

This unit of study will provide candidates with the theoretical and practical foundations for the treatment of retinal disorders and diseases. On completion of this Unit of Study the successful student will be able to: (1) describe and classify the various clinical types of medical retina disease, (2) describe the pathology and pathophysiology of different types of medical retina disease, (3) describe appropriate diagnostic testing for medical retina disease, (4) have a detailed understanding of the range of medical disease affecting the retina. Candidates must be overseas trained specialists from countries with an established vocational ophthalmology training program. They must have satisfactorily completed the requirements to practise as ophthalmologists or be eligible to undertake further fellowship training in their country of residence.

Unit details and rules

Academic unit Postgrad Coursework - SMS
Credit points 6
Prerequisites
? 
OPSC5028 and OPSC5029
Corequisites
? 
None
Prohibitions
? 
None
Assumed knowledge
? 

None

Available to study abroad and exchange students

No

Teaching staff

Coordinator Peter McCluskey, peter.mccluskey@sydney.edu.au
The census date for this unit availability is 31 March 2025
Type Description Weight Due Length
Assignment AI Allowed Essay 2
Essay
30% Mid-semester break
Due date: 22 Apr 2025 at 23:59
2500 words
Outcomes assessed: LO1 LO2 LO3 LO4
Online task AI Allowed Online discussion forum
Online discussion forum
10% Multiple weeks Weekly
Outcomes assessed: LO1 LO2 LO3 LO4
Assignment AI Allowed Essay 1
Essay
30% Week 05
Due date: 24 Mar 2025 at 23:59
2500 words
Outcomes assessed: LO1 LO2 LO3 LO4
Assignment AI Allowed Essay 3
Essay
30% Week 12
Due date: 19 May 2025 at 23:59
2500 words
Outcomes assessed: LO1 LO2 LO3 LO4
AI allowed = AI allowed ?

Assessment summary

  • Essays: Students are to write 3 x 2,500 word essays on the topics provided.
  • Discussion: Online discussion is an essential part of the distance learning environment. The discussion is moderated by the unit coordinator. At the end of semester, the student’s discussions on the forum are graded. A total of ten marks are allocated to online discussion. As a rule of thumb, a significant contribution in 8 out of the 13 weeks will gain full marks.

 

Detailed information for each assessment can be found on Canvas.

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

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 sydney.edu.au/students/guide-to-grades.

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.

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 Clinical assessment and investigation - fluorescein angiography, indocyanine green chorioangiography, optical coherence tomography and ultrasonography Online class (3 hr)  
Week 02 1. Retinal aterial vascular disease; 2. Macroaneurysm and hypertension Online class (3 hr)  
Week 03 Retinal venous vascular disease Online class (3 hr)  
Week 04 Diabetic retinopathy Online class (3 hr)  
Week 05 Age-related macular degeneration Online class (3 hr)  
Week 06 Diagnosis and treatment for other causes of choroidal neovascularisation – retinal angiomatous proliferation, polypoidal, inflammatory choroidal neovascularisation and angioid streaks Online class (3 hr)  
Week 07 Surgical management of retinal and vitreous disorders Online class (3 hr)  
Week 08 Macular and retinal dystrophies 1 Online class (3 hr)  
Week 09 Macular and retinal dystrophies 2 Online class (3 hr)  
Week 10 Posterior segment inflammatory eye disease Online class (3 hr)  
Week 11 Infective posterior segment eye disease Online class (3 hr)  
Week 12 Management of penetrating eye injuries and globe trauma Online class (3 hr)  
Week 13 Retinal and choroidal tumours Online class (3 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 on the Library eReserve link available on Canvas.

  • Retina, 5th Edition; By Stephen J. Ryan, MD, Andrew P. Schachat, MD, Charles P. Wilkinson, MD, David R. Hinton, MD, SriniVas R. Sadda, MD and Peter Wiedemann, ISBN: 978-1-4557-0737-9;

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. describe and classify the various clinical types of medical retina disease
  • LO2. describe the pathology and pathophysiology of different types of medical retina disease
  • LO3. describe appropriate diagnostic testing for medical retina disease
  • LO4. have a detailed understanding of the range of medical disease affecting the retina.

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.

The use of Artificial Intelligence (AI) text generators such as Chat GPT is now permitted for submitted assignments to aide in brainstorming ideas, approaches, assisting with structure and improving grammar and expression in your own work. Do not post confidential, private, personal, 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. Developing responsible use of AI is a critical part of professional behaviour. Ultimately, you are 100% responsible for your assessment submission. Please refer to Part 4 9 (j)(i) and 13 (i) of the Academic Honesty Policy 2022. If you use Artificial Intelligence (AI) in submitted work, you need to acknowledge its use during your submission.

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.