Outline

Overview

Our ever-changing world requires knowledge that extends across multiple disciplines. This unit presents the opportunity to bring together the concepts and skills you have learnt in biochemistry and molecular biology and apply them to an authentic interdisciplinary project that blends biochemistry and molecular biology and a different discipline. In this unit, you will continue to understand, explore and apply disciplinary knowledge, while also meeting and collaborating with students from a different discipline in the University through project-based learning; identifying and solving problems, collecting and analysing data and communicating your findings to a diverse audience. All of these skills are highly valued by employers. This unit will foster the ability to work in interdisciplinary teams, and this is essential for both professional and research pathways in future.

Unit details and rules

Academic unit	Life and Environmental Sciences Academic Operations
Credit points	6
Prerequisites ?	Completion of 96 credit points including 6 credit points from [BCMB2X01 or MEDS2003] and 6 credit points from BCMB2X02
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	2000 level biochemistry and molecular biology. 3000 level biochemistry and molecular biology is strongly recommended.
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Matthew Clemson, matthew.clemson@sydney.edu.au

Assessment

The census date for this unit availability is 31 August 2026

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Portfolio or journal	Practical & Workshop Reports LabArchives report write-up following each workshop or practical session.	30%	Multiple weeks	Variable	AI allowed
Outcomes assessed:
Evaluation	Individual contribution to group project Documenting individual contributions to group project.	10%	Multiple weeks	200-300 words for each team meeting	AI allowed
Outcomes assessed:
Presentation	Project Prospoal Powerpoint (or equivalent), oral presentation plus supporting slides.	0%	Week 04 Due date: 28 Aug 2026 at 10:00	5 min talk + Preparation Time	AI allowed
Outcomes assessed:
Q&A following presentation, submission or placement	Q&A following presentation Q&A to assess individual contributions to the group portfolio and project presentation	5%	Week 12 Due date: 30 Oct 2026 at 10:00	10-15 mins per group of 6	AI prohibited
Outcomes assessed:
Presentation	Final Project Presentation Presentation of final project	10%	Week 12 Due date: 30 Oct 2026 at 10:00	12 min talk + preparation time	AI allowed
Outcomes assessed:
Written work	Final Group Project Portfolio Group project - documentation (including enriched presentation)	25%	Week 12 Due date: 01 Nov 2026 at 23:59 Closing date: 29 Nov 2026	Equivalent to a 20 min presentation	AI allowed
Outcomes assessed:
Written work	Individual project report Discipline specific, individual project report.	20%	Week 13 Due date: 08 Nov 2026 at 23:59 Closing date: 06 Dec 2026	2000 words	AI allowed
Outcomes assessed:
= hurdle task ? = group assignment ?

Assessment summary

Project Proposal Presentation 鈥撎齭tudents will work in their interdisciplinary group to prepare and present a research proposal topic (for more details see Canvas).
Meeting Minutes/Team Work Evaluation 鈥撎齭tudents will document their role and their peers roles in the group project progress regularly throughout semester.
Group Project 鈥� Students will work consistently throughout the semester on their project in mentored groups, and prepare an enriched presentation document for a general audience.
Project Final听Presentation 鈥撎齭tudents will work in their interdisciplinary group to prepare and present a presentation of their group project for a general (BCMB and MATH) audience.
Workshop Reports 鈥撎齭tudents will submit their LabArchives notebooks reporting听workshops/laboratory sessions (most can be completed during听class).听
Individual Report 鈥撎齭tudents will prepare a discipline specific detailed report of an aspect of the group project that they were responsible for.

Assessment criteria

The University awards common result grades, set out in the听听(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	At HD level, a student demonstrates a flair for the subject as well as a detailed and comprehensive understanding of the unit material. A 鈥楬igh Distinction鈥� reflects exceptional achievement and is awarded to a student who demonstrates the ability to apply their subject knowledge and understanding to produce original solutions for novel or highly complex problems and/or comprehensive critical discussions of theoretical concepts.
Distinction	75 - 84	At DI level, a student demonstrates an aptitude for the subject and a well-developed understanding of the unit material. A 鈥楧istinction鈥� reflects excellent achievement and is awarded to a student who demonstrates an ability to apply their subject knowledge and understanding of the subject to produce good solutions for challenging problems and/or a reasonably well-developed critical analysis of theoretical concepts.
Credit	65 - 74	At CR level, a student demonstrates a good command and knowledge of the unit material. A 鈥楥redit鈥� reflects solid achievement and is awarded to a student who has a broad general understanding of the unit material and can solve routine problems and/or identify and superficially discuss theoretical concepts.
Pass	50 - 64	At PS level, a student demonstrates proficiency in the unit material. A 鈥楶ass鈥� reflects satisfactory achievement and is awarded to a student who has threshold knowledge.
Fail	0 - 49	When you don鈥檛 meet the learning outcomes of the unit to a satisfactory standard.

For more information see听.

听

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听Academic Integrity Policy.

Visit the听Current Students website听for more information on AI in assessments, including听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:

5% per day or part thereof up to 50%, thereafter 0 marks

Academic integrity

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

Our website听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听Academic Honesty Education Module (AHEM)听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听Current Students website听for more information on AI in assessments, including听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听simple extension.鈥� 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鈥檛 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听special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students,听听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听reflects the University鈥檚 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	Practical Laboratory Experiments	Practical (21 hr)
Multiple weeks	Mentored Groups Project Development	Tutorial (9 hr)
Week 01	UoS Introduction	Lecture (2 hr)
Week 01	Yeast as a Model Organism	Tutorial (1 hr)
Week 02	Teamwork and Group Contracts	Tutorial (1 hr)
Week 02	Bioinformatics Workshop	Workshop (3 hr)
Week 03	Experimental Design Workshop	Workshop (3 hr)
Week 04	Project Pitch Presentations	Assessment (3 hr)
Week 12	Final Project presentations	Assessment (3 hr)

Attendance and class requirements

Unless otherwise stated, students are expected to attend at least 80% of timetabled activities as defined in the unit of study outline. A student may fail this unit of study because of inadequate attendance.听

Students with permitted clashes with other units of study will need to make special arrangements with the unit coordinator. 80% attendance at group meetings (2pm Fridays) is compulsory for all students.

Use of AI must be reported according to University Policy.

Group feedback, performance in Q&A aspects of assessments, as well as supervised sessions will be used to moderate group marks to reflect individual contributions to group tasks.

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. 鈥婣pply disciplinary knowledge to solve problems in an interdisciplinary context
LO2. 鈥婩ind, define and delimit authentic problems in order to address them.听鈥�
LO3. 鈥婥reate an investigation strategy, explore solutions, discuss approaches and predict outcomes.鈥�
LO4. 鈥婣nalyse data using modern information technology and digital skills.鈥�
LO5. 鈥嬧€婦emonstrate integrity, confidence, personal resilience and the capacity to manage challenges, both individually and in teams.鈥�
LO6. 鈥婥ollaborate with diverse groups and across cultural and disciplinary boundaries to develop solution(s) to the project problems.听鈥�
LO7. 鈥婥ommunicate project outcomes effectively to a broad audience.鈥�

Graduate qualities

The graduate qualities are the qualities and skills that all 爆料王 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鈥檚 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.

In response to student feedback we are running BCMB-only and interdisciplinary mentored group sessions in alternate weeks. The Q&A has been added to further improve equity in assessment for the group project and final presentations.

Additional information

All activities will be face-to-face.听

Details of face-to-face workshops, practicals and tutorial sessions will be provided via regular weekly updates on Canvas.听

Disclaimer

Important: the 爆料王 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 .

爆料王

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

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Disclaimer

On this page

Useful links

BCMB3888: Biochemistry and Molecular Biology Project

Semester 2, 2026 [Normal day] - Camperdown/Darlington, Sydney

Overview

Unit details and rules

Teaching staff

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Attendance and class requirements

Study commitment

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Additional information

Disclaimer

On this page

Useful links