Outline

Overview

In this unit of study you delve deeper into the methods used in health research, building on your knowledge from previous years (see the prerequisites). You will attend lectures and interactive workshops, and complete online study modules. After the common foundations, the unit will be split in streams so that each student will learn either quantitative or qualitative data analysis in depth (not both), depending on their prior learning. As part of quantitative methods, we cover experimental and observational (survey, casecontrol, cohort) study designs, and linear model and logistic regression for data analysis. Qualitative approaches include ethnography, grounded theory, phenomenology and narrative. Methods include interview, focus group and text based. The unit will help with your specific Honours project.

Unit details and rules

Academic unit	Health Sciences
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	48 credit points of 3000 level units of study
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Sophie Lewis, sophie.lewis@sydney.edu.au
Lecturer(s)	Tatjana Seizova-Cajic, tatjana.seizova-cajic@sydney.edu.au
	Maria Fiatarone Singh, maria.fiataronesingh@sydney.edu.au
	Justin McNab, justin.mcnab@sydney.edu.au
	Petra Avramovic, petra.avramovic@sydney.edu.au
	Sophie Lewis, sophie.lewis@sydney.edu.au
	Rachel Thompson, rachel.thompson@sydney.edu.au

Assessment

The census date for this unit availability is 31 March 2025

Details
Criteria

Type	Description	Weight	Due	Length
Assignment	Research proposal rejoinder video Research proposal rejoinder video.	20%	Formal exam period Due date: 10 Jun 2025 at 23:59	5-minute recorded video
Outcomes assessed:
Assignment	Research proposal Written research proposal and plan for research.	50%	Week 08 Due date: 17 Apr 2025 at 23:59	4000 words max
Outcomes assessed:
Small test	Research methods test Test on research concepts and methods.	30%	Week 13 Due date: 28 May 2025 at 11:00 Closing date: 28 May 2025	50 minutes
Outcomes assessed:
= AI allowed ?

Assessment summary

Assessment 1: Research proposal (50% of final grade). 4000 words max. Due Week 8.

Assessment 2: In class research methods test (30% of final grade). Due Week 13.

Assessment 3: Research proposal rejoinder video (20% of final grade). 5-minute recorded video. Due Tuesday 10 June 2025.

Detailed information for each asssessment 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	Exceptional standard of work, showing depth and sophistication
Distinction	75 - 84	A very high standard of work
Credit	65 - 74	A good standard of work
Pass	50 - 64	An acceptable standard of work
Fail	0 - 49	Not meeting the learning outcomes of the unit to a satisfactory standard.

For more information see guide to grades.

Use of generative artificial intelligence (AI) and automated writing tools

Except for supervised exams or in-semester tests, you may use generative AI and automated writing tools in assessments unless expressly prohibited by your unit coordinator.

For exams and in-semester tests, the use of AI and automated writing tools is not allowed unless expressly permitted in the assessment instructions.

The icons in the assessment table above indicate whether AI is allowed – whether full AI, or only some AI (the latter is referred to as “AI restricted”). If no icon is shown, AI use is not permitted at all for the task. Refer to Canvas for full instructions on assessment tasks for this unit.

Your final submission must be your own, original work. You must acknowledge any use of automated writing tools or generative AI, and any material generated that you include in your final submission must be properly referenced. You may be required to submit generative AI inputs and outputs that you used during your assessment process, or drafts of your original work. Inappropriate use of generative AI is considered a breach of the Academic Integrity Policy and penalties may apply.

The Current Students website provides information on artificial intelligence in assessments. For help on how to correctly acknowledge the use of AI, please refer to the  AI in Education Canvas site.

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 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.

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
Week 01	Introduction to the unit and Honours overview	Lecture (2 hr)
Week 01	Research professionalism, integrity and ethics	Tutorial (1 hr)
Week 02	Research foundations and concepts	Lecture and tutorial (3 hr)
Week 03	Experiments and quasi-experimental studies	Lecture (1 hr)
Week 03	Preparing a protocol I: overview	Lecture and tutorial (2 hr)
Week 04	Preparing a protocol II: literature review	Lecture and tutorial (3 hr)
Week 05	Preparing a protocol III: Sampling and recruitment	Lecture and tutorial (3 hr)
Week 06	Preparing a protocol IV: Data collection	Lecture and tutorial (3 hr)
Week 07	Preparing a protocol V: Data analysis	Lecture and tutorial (3 hr)
Week 08	Communicating research: from data to dissemination	Online class (3 hr)
Week 09	Quantitative analysis and reporting I	Lecture and tutorial (3 hr)
Week 09	Qualitative analysis and reporting	Lecture and tutorial (3 hr)
Week 10	Quantitative analysis and reporting II	Lecture and tutorial (3 hr)
Week 10	Qualitative analysis and reporting II	Lecture and tutorial (3 hr)
Week 11	Quantitative analysis and reporting III	Lecture and tutorial (3 hr)
Week 11	Qualitative analysis and reporting III	Lecture and tutorial (3 hr)
Week 12	Quantitative analysis and reporting IV	Lecture and tutorial (3 hr)
Week 12	Qualitative analysis and reporting IV	Lecture and tutorial (3 hr)
Week 13	In class test	Lecture and tutorial (2 hr)

Attendance and class requirements

Attendance: In Honours, students are expected to attend all scheduled classes (lectures and tutorials), and to participate in learning activities. Attendance of less than 80% of the scheduled seminar classes must be supported by written documentation. Please also keep up with online study modules.

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

See Canvas for weekly required and recommended readings.

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. study and work independently and in teams
LO2. manage schedules and resources
LO3. propose research that will increase knowledge in the area of interest
LO4. know the ethical principles of research and adhere to them
LO5. understand quantitative and qualitative approaches to research
LO6. investigate a topic under supervision, including data collection and analysis
LO7. demonstrate the ability to orally present ideas and research findings and respond to questions.

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.

Based on student feedback we have made changes to the number, timing and type of assessment. The unit content and assessment has been designed to support you to successfully complete your Honours research project. The weekly content and the assessments are designed to complement and support the work that you will be doing on your Honours research project with your supervisors.

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

Use of generative artificial intelligence (AI) and automated writing tools

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

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links

HSBH4101: Research Design and Analysis in Health

Semester 1, 2025 [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) and automated writing tools

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

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links