Outline

Overview

Paradigm shifts in biology have changed the emphasis from single biomolecule studies to complex systems of biomolecules, cells and their interrelationships in ecosystems of life. Such an integrated understanding of cells, biomolecules and ecosystems is key to innovations in biology. Life relies on organisation, communication, responsiveness and regulation at every level. Understanding biological mechanisms, improving human health and addressing the impact of human activity are the great challenges of the 21st century. This unit will investigate life at levels ranging from cells, and biomolecule ecosystems, through to complex natural and human ecosystems. You will explore the importance of homeostasis in health and the triggers that lead to disease and death. You will learn the methods of cellular, biomolecular, microbial and ecological investigation that allow us to understand life and intervene in ecosystems to improve health. The same theory will be covered as in the advanced stream but in this Special Studies Unit, the practical component is a research project. The research will be a synthetic biology project investigating genetically engineered organisms. Students will have the opportunity to develop higher level generic skills in computing, communication, critical analysis, problem solving, data analysis and experimental design.

Unit details and rules

Academic unit	Life and Environmental Sciences Academic Operations
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	BIOL1007 or BIOL1907
Assumed knowledge ?	90 or above in HSC Biology or equivalent
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Ann Kwan, ann.kwan@sydney.edu.au
Lecturer(s)	Claudia Keitel, claudia.keitel@sydney.edu.au
	Osu Lilje, osu.lilje@sydney.edu.au
	Murray Thomson, murray.thomson@sydney.edu.au
	Charles Warren, charles.warren@sydney.edu.au
	Jacqueline Matthews, jacqueline.matthews@sydney.edu.au
	Michael Widjaja, michael.widjaja@sydney.edu.au
	Hong Dao Nguyen, hongdao.nguyen@sydney.edu.au
	Timothy Lee, t.lee@sydney.edu.au
	Fran Van Den Berg, francesca.vandenberg@sydney.edu.au
	Ann Kwan, ann.kwan@sydney.edu.au
	Matthew Pye, matthew.pye@sydney.edu.au

Type	Description	Weight	Due	Length
Supervised exam ?	Final Exam Short answer (SA) and multiple choice questions (MCQ)	40%	Formal exam period	2 hours
Outcomes assessed:
Small test	Post module quizzes Lecture-related MCQ after each module	6%	Multiple weeks	No more than 15 min each
Outcomes assessed:
Small continuous assessment	Electronic notebook (ELN) recording experimental data and interpretation	8%	Ongoing	4 lab write-ups at 2% each
Outcomes assessed:
Assignment	Synthetic biology project - Stage 1: Infographics slide Final molecular scene	7%	Week 05 Due date: 31 Aug 2023 at 23:59	Details on CANVAS
Outcomes assessed:
Skills-based evaluation	Calculation skills Calculations	7%	Week 07	40 mins during online lab
Outcomes assessed:
Assignment	Synthetic biology project - Stage 2: Poster Poster	7%	Week 10 Due date: 12 Oct 2023 at 23:59	Details on CANVAS
Outcomes assessed:
Skills-based evaluation	Laboratory skills Laboratory skills including equipment operation and data interpretation	10%	Week 12	40 mins during online lab
Outcomes assessed:
Assignment	Synthetic biology project - Stage 3: Grant application Synthetic biology grant application	15%	Week 13 Due date: 02 Nov 2023 at 23:59	Details on CANVAS
Outcomes assessed:
= group assignment ?

Assessment summary

Synthetic biology project: This is a 13-week project where you will have the chance to explore and contribute to current cutting-edge research on SARS-CoV2, while learning fundamentals of biology, microbiology, biochemistry and biotechnology. Results will be presented in an infographics slide (Stage 1), a poster (Stage 2) and a grant proposal (Stage 3).
Calculation skills assessment: This assessment will cover basic calculations commonly used in moleclar biology, biology and biochemistry.
Labratory skills assessment: This assessment has three parts: data processing (including calculations), interpretation and lab techniques.
Electronic Lab Notebook (ELN): Four of the lab session write up in ELN, including all experimental data, your analysis and conclusions, will be assessed.
Post Module Quizzes (PMQ): A short quiz will follow each of the lecture modules. The best three marks from the four modules will be used in the final mark.
Final exam: The exam will cover all material in the unit from both lectures and practical classes. The exam will have a mixture of multiple choice questions and short answer questions. If a second replacement exam is required, this exam may be delivered via an alternative assessment method, such as 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.

Detailed information for each assessment can be found on Canvas.

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.

Result name	Mark range	Description
High distinction	85 - 100	factual information of an outstanding standard with a sophisticated grasp of the principles and interpretation clear evidence of critical analysis, understanding of experimental design and statistical analysis, integration of knowledge and application to the experimental situation; evidence of originality of thought
Distinction	75 - 84	factual information is of a superior standard, with excellent grasp of the principles and interpretation good evidence of critical analysis understanding of experimental design and statistical analysis, and integration of knowledge; good understanding of the application of knowledge; some evidence of application to the experimental situation
Credit	65 - 74	factual information is of a high standard, but some information may be incorrect or missing, with sound grasp of the principles and interpretation critical analysis is mainly superficial and relevance of knowledge not always clear, understanding of experimental design and statistical analysis is sufficient and applied to the experimental situation
Pass	50 - 64	factual information is of an acceptable standard but basic and contains gaps, errors or inconsistencies/contradictions critical analysis is relatively poor, material may be correct but not entirely relevant; surface understanding of experimental design and statistical analysis with limited application to the experimental situation and limited interpretation.
Fail	0 - 49	a significant amount of factual information is incorrect misses the point, fundamental misunderstandings evident evidence of plagiarism

sydney.edu.au/students/guide-to-grade

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.

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:

Please see Canvas.

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
Weekly	Two to three content lectures per week (choice of in-person or pre-recorded), plus a Q&A session after each lecturer has presented. Details of lectures and content are provided on Canvas.	Lecture (30 hr)
Weekly	Weekly 3 hr practicals (except Wk 9 which will be a short online module due to Labour Day). More details are available on Canvas.	Practical (36 hr)

Attendance and class requirements

Study load: You are expected to dedicate at least 5 hours per week face to face on campus for 13 weeks of this unit and at least another 5 hours off campus.
Attendance: Unless otherwise indicated, students are expected to attend a minimum of 80% of timetabled practicals for a unit of study, unless granted exemption by the Associate Dean.

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

There is no prescribed textbook for this unit.

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. demonstrate an understanding of biology: (i) value the diverse range of biological sub-disciplines and the complexity, variability and unpredictability of living systems (ii) appreciate the importance of sustainability and the impact of biology within the broader economic, social and environmental context
LO2. demonstrate depth and breadth of biological knowledge: (i) describe and explain broad biological concepts with relevant examples (ii) explain the biological organisation from molecules to cells and to ecosystems which integrate to form a dynamic network (iii) describe how structure and function are interrelated from the level of molecules to organisms
LO3. demonstrate inquiry and problem-solving abilities: (i) propose and test hypotheses to explain biological phenomena (ii) identify and use appropriate technical and analytical skills to collect data (iii) analyse quantitative data to critically evaluate evidence for biological explanations
LO4. demonstrate appropriate and effective communication: (i) produce written, visual, and oral explanations to communicate to a scientific audience and to the general public (ii) contribute to both independent and group tasks
LO5. demonstrate development in personal and professional responsibility: (i) evaluate and debate arguments on biological phenomena in a respectful and ethical manner (ii) reflect on your development as a student and the responsibility you have to find and apply information and work ethically, responsibly and safely

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.

This course is face-to-face only and received excellent students' feedback last year so only minor adjustments to assignments and assessments have been made. The lecture assessments are the same as BIOL1X07.

Additional information

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

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

Required readings

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

Media

Student links

About us

Connect

Current students

BIOL1997: From Molecules to Ecosystems (SSP)

Semester 2, 2023 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

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

Required readings

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

Media

Student links

About us

Connect