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Unit outline_

MEDF5303: Project (Advanced Masters) (Part B)

Semester 1, 2023 [Supervision] - Camperdown/Darlington, Sydney

Candidates will work on an independent research project in an area of specific interest relevant to their master's degree. The project may take the form of analysis of an existing data set, a systematic or integrative review of the literature, a case series, survey or other project acceptable to the project supervisor. In some streams, projects may be available for students to select. It is essential where there is the use of patient information or recruitment of patient study subjects that appropriate ethics approval is gained from the governing body where the project will take place. The candidate will enter into a learning contract and will be guided through the steps required to plan and execute a substantial research project and prepare a scholarly work which may be a paper for publication. A candidate must enrol in a minimum of 12 credit points of project units of study in order to submit their final written work. Approval of the project and supervisor by the Program Director must be confirmed prior to commencing the project.

Unit details and rules

Academic unit Critical Care
Credit points 6
Prerequisites
? 
None
Corequisites
? 
None
Prohibitions
? 
None
Assumed knowledge
? 

None

Available to study abroad and exchange students

No

Teaching staff

Coordinator Iryna Zablotska-Manos, iryna.zablotska@sydney.edu.au
Project supervisor(s) Megan Cox, megan.cox@sydney.edu.au
Christopher Fox, c.fox@sydney.edu.au
Type Description Weight Due Length
Assignment Final report
Report
80% Formal exam period
Due date: 05 Jun 2023 at 23:59
7,000-10,000 words
Outcomes assessed: LO2 LO3 LO1
Presentation Final presentation
Presentation
20% Week 13 10-min presentation & 5-min discussion
Outcomes assessed: LO4

Assessment summary

Detailed information for each assessment can be found via Canvas or via your supervisor.

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 guide to grades.

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:

Late assignments that have not been granted extensions and are of a standard to receive a pass or higher mark will attract a penalty of 5% of the maximum mark per day late including weekend days. Assignments submitted more than 10 days late without prior approval from the unit of study coordinator will not be accepted and will be given a zero (0) mark.

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.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

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.

WK Topic Learning activity Learning outcomes
Week 01 Meet with your Supervisor. Initiate research project. Module 5: Quantitative Data Collection Methods: How do I gather data from my sample? Project (4 hr) LO1
Week 02 Continue work on your project implementation. Online Tutorial (mandatory for students): Monday 27 Feb, 7.30pm AEDT Project (4 hr) LO1
Week 03 Continue work on your project implementation. Project (4 hr) LO1
Week 04 Continue work on your project implementation. Project (4 hr) LO1
Week 05 Continue work on your project implementation. Milestone 1 (hurdle): Interim report on data collection - Due Monday 20 Mar, 23:59 AEDT Project (4 hr) LO1
Week 06 Module 6: Data analyses Continue work on your project implementation. Start planning your data analysis Project (4 hr) LO2
Week 07 Continue work on your project implementation. Project (4 hr) LO2
Week 08 Continue work on your project implementation. Initiate work on the final report. Milestone 2 (Hurdle) : Plan for data analysis - Due Monday 17 April, 23:59 AEDT Project (4 hr) LO2
Week 09 Finalise data collection for the research project. Initiate data analyses. Online Tutorial (mandatory for students): Monday 24 April, 7.30pm AEDT Project (4 hr) LO2
Week 10 Module 7: Research Appraisal Continue data analyses. Initiate final study report. Project (4 hr) LO3
Week 11 Continue work on your final project report. Project (4 hr) LO3
Week 12 Obtain feedback of your supervisor on your final project report Project (4 hr) LO3
Week 13 Finalise your final project report. Project (4 hr) LO4

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.

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. Collect information using appropriate research methods to address study aims
  • LO2. Analyse collected information using appropriate statistical or qualitative methods.
  • LO3. Synthesise relevant literature and statistical results into a manuscript ready for publication
  • LO4. Confidently present your work and research findings

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.

UoS coordinator considered feedback and made appropriate changes/improvements

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.