MDMP5225: Semester 2, 2021

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Units MDMP5225 Semester 2 2021 [Normal day]

Unit outline_

MDMP5225: MD Project Development 2

Semester 2, 2021 [Normal day] - Camperdown/Darlington, Sydney

Overview

By the end of the course, students will be expected to have completed a comprehensive Project Checklist for their MD Research Project, endorsed by their Research Tutor, Research Coordinator and one of the Unit of Study Coordinators. The proposal will include consideration of ethics and the need for ethics approval. Students will also have mastered core concepts in Information Literacy, Research Ethics and Evidence Based Medicine. Students are required to complete the compulsory MD Milestones (Milestones 2, 3 and 4) and any other progress checkpoint tasks required by their Research Tutor or Expert Advisor. Milestone 2 includes tasks focussed on ethics and on information literacy. Milestone 3 includes the MD Project Checklist, which covers all information required by the University for the purposes of ensuring that the MD Research Project complies with applicable University policy on research governance and the conduct of research. Milestone 4 includes a progress report written in the form of a scientific anstract, and a seminar presentation by each student on their MD Research Project at an MD Project Group Milestone 4 meeting attended by all members of the student's MD Project Group. The seminar is assessed by the Research Tutor and one independent examiner. Students will also complete Information Literacy learning and tasks focused on Evidence-Based Medicine (EBM), and ethics focused workshops and written tasks. Students' participation and performance in all academic tasks required in this unit of study must be graded as 'satisfactory' in Stage 2 to progress to Stage 3.

Unit details and rules

Academic unit	Department of Medical Sciences
Credit points	2
Prerequisites ?	MDMP5111 and MDMP5112 and MDMP5113 and MDMP5114 and MDMP5122 and MDMP5123 and MDMP5124 and MDMP5125 and MDMP5126 and MDMP5211 and MDMP5212 and MDMP5213 and MDMP5214
Corequisites ?	MDMP5221 and MDMP5222 and MDMP5223 and MDMP5224
Prohibitions ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Joanne Hart, joanne.hart@sydney.edu.au

Type	Description	Weight	Due	Length
Assignment	Milestone 2	0%	- Due date: 01 Mar 2020 at 00:00	n/a
Outcomes assessed:
Assignment	Milestone 3	0%	- Due date: 17 May 2020 at 00:00	n/a
Outcomes assessed:
Assignment	Milestone 4	0%	- Due date: 25 Oct 2020 at 00:00	n/a
Outcomes assessed:
Participation	Class attendance (MD project theme - research workshops etc)	0%	Ongoing	n/a
Outcomes assessed:

Assessment summary

Please see the unit’s Canvas page for full Assessment information.

Assessment criteria

At the end of Semester 1, students will receive a grade of UC – Unit of study continuing, which will be finalised at the end of the year where students will receive one of the following grades for both year 2 units of study; Satisfied requirements (SR), Failed requirements no mark (FR) or another non-completion grade as per Schedule 1 of the Coursework Policy 2014.

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.

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.

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.

Weekly schedule

WK	Topic	Learning activity	Learning outcomes

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 2 credit point unit, this equates to roughly 40-50 hours of student effort in total.

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. Appraise the ethical issues pertaining to their MD project and other research proposals
LO2. Identify and apply appropriate research methods for a research question
LO3. Prepare a structured literature search for their project
LO4. Apply research methods and ethics knowledge to progress their MD project
LO5. Produce a progress report that shows their project is advancing towards completion

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.

N/A

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

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

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