Outline

Overview

The candidate will understand how to effectively form, lead and successfully manage a clinical research project. The subject will address issues related to resource management (including team and finance). The key elements of putting together a solid funding application and developing a study protocol will also be covered. Issues involved in study start up (initiation) and study outcome collection and review will be introduced. Aspects of scientific leadership including skills to address/solve problems in recruitment, follow up and event assessment will be taught. Students will gain a detailed understanding of how to plan for issues arising during a clinical trial in a practical sense including dealing with unexpected events during a trial, addressing event rates lower than that expected, changes in outcome definitions and ethical dilemmas. This is a key subject where students will integrate knowledge from prior studies and gain an understanding of how to apply theory to practice.

Unit details and rules

Academic unit	NHMRC Clinical Trials Centre
Credit points	6
Prerequisites ?	CLTR5001
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Rebecca Mister, rebecca.mister@sydney.edu.au
Tutor(s)	Hannora Jurkovic, hannora.jurkovic@sydney.edu.au
	Katrin Sjoquist, katrin.sjoquist@sydney.edu.au
	Rebecca Mister, rebecca.mister@sydney.edu.au

Type	Description	Weight	Due	Length
Assignment	Assignment 2 Completion of concept outline and justification of design	40%	Week 07 Due date: 30 Mar 2020 at 11:47	Part 1: 3 pages Part 2: 3 x 200 words
Outcomes assessed:
Assignment	Assignment 3 Short answer questions	15%	Week 09 Due date: 27 Apr 2020 at 11:49	Multiple choice/Short ans (150 words)
Outcomes assessed:
Assignment	Assignment 1 Modules 1-5 via Discussion postings in Canvas	5%	Week 13 Due date: 07 Jun 2021 at 11:44	Weeks 1-12
Outcomes assessed:
Assignment	Assignment 4 Short essays - response to scenarios	40%	Week 13 Due date: 25 May 2020 at 11:51	3 x 2 pages
Outcomes assessed:

Assessment summary

This unit of study will be assessed via online participation (5%), one online quiz (15%) and two 2000 word written assignments (40% each). Further detail regarding the assessments is provided in the “Assessment Methods and Weightings” table on page 9.

Assessment 1 (online participation 5%) – To receive marks for online participation, you must make at least one meaningful discussion posting per Module in Canvas from week 1 – 12. A meaningful discussion posting is one that makes a valuable contribution to the group discussion. Contributions should relate to the content of the current module being studied.

Assessments 2 and 4 (written assignments, 40% each) - will be released in the “Assignments” tab in Canvas. You will also be required to submit (upload) your assessments in this same location. Please ensure you include your student number as part of the file name of your assignment: e.g. 123456_Assessment_3.doc. Please do not include your name in the assignment or the file name of the assignment.

Assessment 2 (online quiz 15%) – For assessment 2 you will required to complete an online quiz in Canvas. Further details are provided in the table on page 9.

This Unit requires you to demonstrate that you have read, and understood the Unit materials of this, and other prior Units. Assessments will ask you to apply this knowledge to different scenarios, and to justify your proposed solutions. Students who simply give generic responses, without reference to the specifics of the question; or do not answer all parts of the question, will be marked accordingly.

For this Unit we tend to post general feedback in one document and only give individual feedback to any students who may have had specific issues. The individual feedback will not include the information in the general feedback document.

In the assignments for this Unit there is no single correct answer; we are looking to see that students have understood the content and are able to apply these concepts to specific examples. Marks will not be awarded to students who simply repeat generic information without consideration of the specific scenario.

Your assignment should be uploaded onto Canvas, with you student number as part of the identification: 123456_Assignment_1.doc. Please do not include your name in the assignment or the file name of the assignment.

Marks for assessments will be posted using the “My grades” tool in Canvas.

Please note: Assessment deadlines are important. Extensions may be granted for special circumstances. It is the student’s responsibility to discuss arrangements with the course coordinator PRIOR to the release of the assessment material.

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:

It is expected that unless an application for Special Consideration (submitted centrally with the University) or Special Arrangements has been approved, students will submit all assessments by the specified due date. If the assessment is completed or submitted within the period of extension, no academic penalty will be applied to that piece of assessment. If an extension is either not sought, not granted or is granted but work is submitted after the extended due date, the late submission of assessment will result in an academic penalty as follows, unless otherwise stated in the course resolutions: • 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 (e.g. if the assignment is worth 40 marks, the penalty is 2 marks per day late) until the mark reaches 50% of the maximum mark (e.g. 20 marks if the maximum is 40 marks). • Assignments that are not of a pass standard will not have marks deducted and will fail regardless • 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.

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
Weekly	See Canvas	Online class (130 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

There is no required textbook for this subject. However, recommended readings will be provided with each module as required.

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. See canvas for further details

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

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

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

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links

CLTR5003: Leadership and Problem Solving

Semester 1, 2021 [Online] - Camperdown/Darlington, Sydney

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

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links