Outline

Overview

Simulation is now a required learning and skill maintenance tool in critical care medicine. This unit will provide students with the skills and knowledge to: construct a challenging, yet safe learning environment with realistic simulation scenarios; manage the technology and the learning environment; and provide effective debriefing and productive feedback. The unit of study will also aim to enhance the student's skills as a teacher in a busy clinical setting, improving supervision and feedback and creating effective teams.

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	Leonie Watterson, leonie.watterson@sydney.edu.au

Type	Description	Weight	Due	Length
Small continuous assessment	Online discsussions Online discussion	20%	Multiple weeks	200 to 600 words
Outcomes assessed:
Skills-based evaluation	Portfolio tasks Portfolio	30%	Multiple weeks	600 words each
Outcomes assessed:
Participation	Workshop tasks Participation	20%	Week 08	2 days
Outcomes assessed:
Online task	Written relection Written task	10%	Week 10	600 words
Outcomes assessed:
Online task	Essay Essay	20%	Week 11	1200 words
Outcomes assessed:

Assessment summary

Discussion forum: This task requires you to contribute to an online discussion. This task enables you to introduce yourself to other students and faculty. In face to face simulation training we consider it to be an important element of what we call ‘psychological safety’. You will address this in more detail in Module 2. Non simulation educators also use the term ‘positive group dynamic’.
Post workshop reflection: This assignment is a written reflection on the learning experiences in the two-day face to face workshop.
Essay: Using a video case study write an essay that explains the principles and stages of debriefing using the learner’s preferred debriefing model as an example.

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 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:

Please note, for this unit of study (CRIT5009) the late submission penalty will be 5% of the maximum awardable mark for each calendar day after the due date for 5 calendar days only. This is to ensure that timely feedback is provided to students. If the assessment is submitted more than 5 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
Mid-semester break	Live Webinar workshop	Workshop (10 hr)
Week 01	Module 1: Key concepts	Online class (10 hr)
Week 02	Module 1: Key concepts	Online class (10 hr)
Week 03	Module 2: Simulation learning theories and environment	Online class (10 hr)
Week 04	Module 2: Simulation learning theories and environment	Online class (10 hr)
Week 05	Module 3: Scenario design and realism	Online class (10 hr)
Week 06	Module 3: Scenario design and realism	Online class (10 hr)
Week 07	Module 4: Debriefing	Online class (10 hr)
Week 08	Module 4: Debriefing	Online class (10 hr)
Week 09	Module 5: Simulation technologies	Online class (10 hr)
Week 10	Module 5: Simulation technologies	Online class (10 hr)
Week 11	Module 6: Assessment	Online class (10 hr)
Week 12	Module 6: Assessment	Online class (10 hr)
Week 13	Module 7: Application to practice	Online class (10 hr)

Attendance and class requirements

Attendance: A mandatory two day workshop will be delivered on Thursday April 20 2023 and Friday April 21 2023.

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 the Library eReserve, available on Canvas.

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. Please see Canvas for individual module outcomes.

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 Evaluation 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.

Additional information

Work, health and safety

There are no specific WHS requirements for this unit.

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

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Work, health and safety

Disclaimer

On this page

Useful links

CRIT5009: Teaching with Simulation

Semester 1, 2023 [Distance education/intensive on campus] - Remote

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

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Work, health and safety

Disclaimer

On this page

Useful links