DENR3901: Intensive January - February, 2026

Units DENR3901 Intensive January - February 2026 [Block mode]

Unit outline_

DENR3901: Denison Research

Intensive January - February, 2026 [Block mode] - Westmead, Sydney

Overview

Enrolment into DENR3901 offers 2000- and 3000-level students the opportunity to work on real world scientific problems. This unit of study exposes students to a variety of research opportunities and provides an insight into research process while working alongside our leading scientific researchers. Research projects are available in most disciplines for a duration of 6 weeks and are awarded through a Scholarship selection process based on academic merit.

Unit details and rules

Academic unit	Science Faculty
Credit points	0
Prerequisites ?	Minimum 96 credit points
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Sanaa Zaki, sanaa.zaki@sydney.edu.au

Assessment

The census date for this unit availability is 30 January 2026

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Presentation	Project presentation Most supervisors will ask students to present a brief talk on their project	0%	Week 01	5-10 minutes minimum	AI allowed
Outcomes assessed:
Written work	Project report An alternative to an oral presentation, may be a brief written report	0%	Week 01	1 page minimum	AI allowed
Outcomes assessed:
Contribution	Attendance with research group Participate in the research project	0%	Weekly	6 weeks	AI allowed
Outcomes assessed:

Assessment summary

Attendance with research group: This is simply a requirement to work for the 6 week period, meeting reasonable attendance requirements set by the research group (e.g. public holidays off).
Project presentation: Most supervisors will ask their students to present a brief talk on their project to their research group. A minimum of 5-10 minutes is expected, although your supervisor may request a longer talk.
Project report: As an alternative to an oral presentation, a supervisor may request a brief written report. A minimum length of 1 page is expected, although your supervisor may request a longer report.

Further information for each assessment should be requested from your project supervisor.

Assessment criteria

A final result for the unit will be returned as a grade only - SR = satisfied requirements, or FR = failed requirements. These assessment requirements should be completed by the specified date very early in semester 1.

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.

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.

Weekly schedule

WK	Topic	Learning activity	Learning outcomes
Ongoing	6 week research project with the structure determined by the research group	Self-directed learning (210 hr)

Attendance and class requirements

You are required to attend the normal location(s) where the research is carried out for the period of the project (6 weeks), as ageed with your supervisor.

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.

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. apply scientific concepts and knowledge to develop models and solve qualitative and quantitative problems for a research group, using appropriate mathematical and computing techniques as necessary
LO2. find and analyse information and data necessary for a task and judge its reliability and significance
LO3. understand and apply the principles of scientific measurement necessary to gather data necessary for a task
LO4. organise and communicate scientific and technical information appropriately through day-to-day interactions and oral and written reporting
LO5. engage in team and group work in pursuing the objectives of research group
LO6. demonstrate a sense of responsibility, independence, cultural competence and ethical behaviour as a practising scientist in a work environment.

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.

The Science Summer Research Program is offered for 6 weeks during the Intensive February period.

Additional information

Site visit guidelines

There are no site visit guidelines for this unit, unless required for your project and specified by your supervisor.

Work, health and safety

We are governed by the Work Health and Safety Act 2011, Work Health and Safety Regulation 2011 and Codes of Practice. Penalties for non-compliance have increased. Everyone has a responsibility for health and safety at work. The University’s Work Health and Safety policy explains the responsibilities and expectations of workers and others, and the procedures for managing WHS risks associated with University activities.

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

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Site visit guidelines

Work, health and safety

Disclaimer

On this page

Useful links