Outline

Overview

This unit builds on the previous Research and Enquiry 1 unit of study. It will continue to expand students' appreciation of the contribution of research to the veterinary sciences and develop their skills in the synthesis and communication of new and existing knowledge. Along with this, it will equip students with new knowledge and analytical skills needed to solve problems in animal health using an evidence‑based and systematic approach. Students will extend their capacity to apply diagnostic strategies and interpret results to inform clinical and population‑level decision making, and to investigate disease, low productivity, and related health challenges to guide approaches to disease control, prevention, and surveillance. Students will also refine their skills in appraising and synthesising scientific literature, incorporating statistical reasoning and ethical considerations relevant to research and practice as a veterinary scientist. Through integrated learning activities, the unit supports the development of clear and effective communication of evidence to diverse audiences and fosters the critical thinking required for contemporary veterinary work.

Unit details and rules

Academic unit	School of Veterinary Science Academic Operations
Credit points	3
Prerequisites ?	(VETS6101 and VETS6102 and VETS6103 and VETS6104 and VETS6105 and VETS6106 and VETS6107 and VETS6108) or (VETS6104 and VETS6108 and VETS6111 and VETS6113 and VETS6115 and VETS6116)
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	Content of all DVM Year 1 units of study
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Jenny-Ann Toribio, jenny-ann.toribio@sydney.edu.au

Assessment

The census date for this unit availability is 31 March 2026

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Written exam	Final exam Final exam - MCQ and/or short answer question.	55%	Formal exam period	1 hour	AI prohibited
Outcomes assessed:
In-class quiz	In-Class Quiz MCQ related to Module 1	5%	Week 03 Due date: 12 Mar 2026 at 13:00	15 minutes	AI allowed
Outcomes assessed:
Written work	Assignment Disease Investigation Assignment	40%	Week 09 Due date: 01 May 2026 at 23:59 Closing date: 11 May 2026	1,500 words	AI allowed
Outcomes assessed:
= hurdle task ?

Assessment summary

Detailed information for each assessment can be found on Canvas.

All required hurdle tasks and compulsory assessments must be submitted by 11:59 PM Australian Eastern Time, unless an approved Special Consideration application or an academic plan with an adjusted submission date has been granted.

Final exam: If a second replacement exam is required, this exam may be delivered via an alternative assessment method, such as a viva voce (oral exam). The alternative assessment will meet the same learning outcomes as the original exam. The format of the alternative assessment will be determined by the unit coordinator.

A pass mark of at least 50% MUST be achieved for the final examination in order to pass the unit of study.

DVM students are expected to be present for all scheduled classes and activities to achieve learning outcomes. This includes arriving on time and staying for the duration of each class.

The Sydney School of Veterinary Science has established attendance guidelines to ensure compliance with accreditation requirements.

In accordance with the DVM attendance provisions, DVM students are required to complete all Required Learning Activities (RLA’s) and assessment tasks. If absent for any reason, students must notify the UOSC and apply for a special consideration at the earliest opportunity.

Classes identified as a RLA will be available on the Canvas site

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2021 (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.

For more information see guide to grades.

Use of generative artificial intelligence (AI)

You can use generative AI tools for open assessments. Restrictions on AI use apply to secure, supervised assessments used to confirm if students have met specific learning outcomes.

Refer to the assessment table above to see if AI is allowed, for assessments in this unit and check Canvas for full instructions on assessment tasks and AI use.

If you use AI, you must always acknowledge it. Misusing AI may lead to a breach of the Academic Integrity Policy.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

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:

In accordance with the University policy, these penalties apply when written work is submitted after 23:59 on the due date: 1) Deduction of 5% of the maximum mark for each calendar day after the due date. 2) After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The University expects students to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

Our website provides information on academic integrity and the resources available to all students. This includes advice on how to avoid common breaches of academic integrity. Ensure that you have completed the Academic Honesty Education Module (AHEM) which is mandatory for all commencing coursework students

Penalties for serious breaches can significantly impact your studies and your career after graduation. It is important that you speak with your unit coordinator if you need help with completing assessments.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

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.

Support for students

The Support for Students Policy reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

Weekly schedule

WK	Topic	Learning activity
Multiple weeks	Diagnostics	Lecture (6 hr)
	Diagnostics	Tutorial (12 hr)
	Investigation	Lecture (4 hr)
	Investigation	Tutorial (8 hr)
	Extension - considerations with multiple variables	Lecture (2 hr)
	Extension - considerations with multiple variables	Tutorial (4 hr)
Week 10	Extension - sample size for research studies	Lecture (1 hr)
Week 10	Extension - sample size for research studies	Tutorial (2 hr)
Week 13	Capstone application	Tutorial (2 hr)

Attendance and class requirements

The Sydney School of Veterinary Science has established attendance guidelines to ensure compliance with accreditation requirements.

The DVM Attendance Provision 2024 is available on the University of Sydney policy register.

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 3 credit point unit, this equates to roughly 60-75 hours of student effort in total.

Required readings

Detailed information on any required readings may be found 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.

At the completion of this unit, you should be able to:

LO1. Select, apply and interpret diagnostic strategies and results to inform veterinary decision-making.
LO2. Conduct investigations of disease and low productivity to inform disease control and prevention and contribute to surveillance.
LO3. Critically appraise, synthesise and communicate evidence, including statistical and ethical considerations, relevant to veterinary practice.

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

Alignment with Competency standards

Outcomes	Competency standards
	Australasian Veterinary Boards Council (D1Cs) - 17. Apply principles of population medicine and epidemiological skills to investigate veterinary problems. 25. Communicate effectively with clients, the public, professional colleagues, and responsible authorities, using language appropriate to the audience and context. 5. Select appropriate diagnostic tests and techniques, including diagnostic imaging. Safely apply diagnostic techniques and safely collect, preserve and transport samples as applicable. Interpret results of diagnostics, accounting for their limitations.
	Australasian Veterinary Boards Council (D1Cs) - 17. Apply principles of population medicine and epidemiological skills to investigate veterinary problems. 19. Recognise suspicious signs of reportable biosecurity risks (endemic, exotic and zoonotic diseases) and take appropriate action, including notifying the relevant authorities. 25. Communicate effectively with clients, the public, professional colleagues, and responsible authorities, using language appropriate to the audience and context. 4. Identify and prioritise problems to develop differential diagnoses and a diagnostic plan, then interpret clinical and diagnostic evidence to establish a diagnosis. 9. Adapt and apply knowledge and skills to varied scenarios and contexts, including where information is incomplete.
	Australasian Veterinary Boards Council (D1Cs) - 25. Communicate effectively with clients, the public, professional colleagues, and responsible authorities, using language appropriate to the audience and context. 34. Recognise limitations of knowledge, skills and resources, consult with colleagues as needed, and identify situations in which referral is warranted. 39. Critically review and evaluate evidence from traditional and digital resources, aligned to evidence-based veterinary practice. 40. Contribute as appropriate to the advancement and dissemination of veterinary knowledge to improve the quality of animal care and public health. 8. Utilise traditional and digital technologies and information sources to inform patient care and manage health data. 9. Adapt and apply knowledge and skills to varied scenarios and contexts, including where information is incomplete.

Australasian Veterinary Boards Council (D1Cs) -

Competency code	Taught, Practiced or Assessed	Competency standard
17		Apply principles of population medicine and epidemiological skills to investigate veterinary problems.
19		Recognise suspicious signs of reportable biosecurity risks (endemic, exotic and zoonotic diseases) and take appropriate action, including notifying the relevant authorities.
25		Communicate effectively with clients, the public, professional colleagues, and responsible authorities, using language appropriate to the audience and context.
34		Recognise limitations of knowledge, skills and resources, consult with colleagues as needed, and identify situations in which referral is warranted.
39		Critically review and evaluate evidence from traditional and digital resources, aligned to evidence-based veterinary practice.
4		Identify and prioritise problems to develop differential diagnoses and a diagnostic plan, then interpret clinical and diagnostic evidence to establish a diagnosis.
40		Contribute as appropriate to the advancement and dissemination of veterinary knowledge to improve the quality of animal care and public health.
5		Select appropriate diagnostic tests and techniques, including diagnostic imaging. Safely apply diagnostic techniques and safely collect, preserve and transport samples as applicable. Interpret results of diagnostics, accounting for their limitations.
8		Utilise traditional and digital technologies and information sources to inform patient care and manage health data.
9		Adapt and apply knowledge and skills to varied scenarios and contexts, including where information is incomplete.

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

In 2025 49% of students provided feedback on the unit of study Research and Enquiry 2A VETS6203. This response was similar to previous years. Students liked the enthusiastic teaching and the general structure of the course, although some tutorials were enjoyed more than others.. This is the last reiteration of the current content presented by this unit. From 2026 Research and Enquiry 2A will have a different structure and content.

Additional information

Work, health and safety

Risk assessments are regularly conducted for units that require the completion of compulsory learning activities that may expose students to zoonotic diseases. These assessments aim to identify appropriate risk mitigation controls, such as vaccination against vaccine- preventable zoonoses.

Vaccination against Q fever (Coxiella burnetii) is an inherent requirement for students enrolling in this unit of study. Students must be vaccinated against Q fever before commencing the unit or no later than the first day of the enrolled teaching session. Q fever vaccination is only available in Australia with the vaccination process taking three weeks to complete.

Students must also submit a Q fever Vaccination Declaration upon enrolment.

Students who fail to receive vaccination by the specified deadline and/or submit a Q fever Vaccination Declaration are precluded from practical learning activities and will not be able to satisfactorily complete relevant units of study and/or progress in their course more generally.

Please refer to the University’s website here for more information on student vaccinations.

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

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Alignment with Competency standards

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Work, health and safety

Disclaimer

On this page

Useful links

VETS6203: Research and Enquiry 2A

Semester 1, 2026 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Alignment with Competency standards

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Work, health and safety

Disclaimer

On this page

Useful links