PSTY5108: Semester 2 Early, 2020

Units PSTY5108 Semester 2 Early 2020 [Supervision]

Unit outline_

PSTY5108: Psychotherapy Treatise

Semester 2 Early, 2020 [Supervision] - Westmead, Sydney

Overview

Research and treatise of up to 10,000 words.

Unit details and rules

Academic unit	Brain and Mind Science
Credit points	6
Prerequisites ?	PSTY5105
Corequisites ?	PSTY5107
Prohibitions ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Anthony Korner, anthony.korner@sydney.edu.au

Type	Description	Weight	Due	Length
Assignment	Treatise (Final) Refer to Canvas	100%	- Due date: 05 Mar 2021 at 23:00	7000 -10,000 words
Outcomes assessed:
Assignment	Treatise (Draft) NA	0%	Week 11	7000 -10,000 words
Outcomes assessed:

Write a treatise on a topic relating to psychotherapy using the Conversational Model. You should be guided by the interest that has been developed over the 3 years of the course in making a choice of topic, which should also involve discussion with supervisors and faculty. Aligning treatise topic with the research done in the program may allow acquisition of required resources (e.g. equipment, specific participants), and enhances the likelihood of successful submission in peer reviewed journals.

Your treatise should be written ideally for publication, making an original contribution to the field of psychotherapy. As such you should be interpreting clinical material, and/or the results of data analysis, in the context of recent scientific literature. A theoretical/conceptual treatise may not require data analysis; however such projects usually require a higher level of scholarship to reach a publishable standard.

The aim of this assessment is to demonstrate your understanding of CMT at both clinical and theoretical levels. The standard expected would be at a level consistent with presentation at a scientific meeting in the local health district.

Treatise (Draft)

You will be provided written feedback only (no mark)

Treatise (Final)

Written and verbal feedback should be considered and integrated in your Final treatise.

To pass this assessment, a mark of 12 or more out of 20 (i.e. 60%) is required. The treatise is marked by two examiners who will give feedback.

Assessment criteria

To satisfy the requirements for Treatise you must receive >=12/20 (60%).

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 6 credit point unit, this equates to roughly 120-150 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. Ability to interpret clinical material, and/or the results of data analysis
LO2. Demonstrate an understanding of the Conversational Model Theory at both clinical and theoretical levels.

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.

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

Treatise (Draft)

Treatise (Final)

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

On this page

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