Outline

Overview

The ability to work across interdisciplinary boundaries is a crucial skill for tackling problems in our modern world. With quantitative modelling becoming widespread across industry and traditionally qualitative sciences, physicists have a crucial role to play in applying their expertise broadly. In this unit, you will gain an appreciation for the unique skills and ways of thinking that have allowed physicists to contribute to a wide range of real-world problems. This unit contains two components: (i) a lecture and interactive problem-based group-tutorial component on interdisciplinary physics, complex systems, and artificial intelligence, and (ii) an interdisciplinary project-based component. For the project component you will work in small interdisciplinary groups, including students from other 3888 units, to tackle a real-world interdisciplinary problem. For example, students may build a real-time brain-machine interface that use machine-learning techniques to extract meaningful patterns from live physiological measurements (e.g., human brain activity that is used to control computer software (e.g., a simple game). Through project-based learning, you will learn to leverage the diverse skills represented in your team, and develop skills in experimental measurement, numerical processing, and statistical modelling. Skills in identifying and solving problems, collecting and analysing data, and communicating your findings to diverse audiences are highly valued in modern research and by employers.

Unit details and rules

Academic unit	Physics Academic Operations
Credit points	6
Prerequisites ?	(PHYS2011 OR PHYS2911 OR PHYS2921) AND (PHYS2012 OR PHYS2912 OR PHYS2922)
Corequisites ?	None
Prohibitions ?	PHYS3941 or PHYS3991
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Ben Fulcher, ben.fulcher@sydney.edu.au
Project supervisor(s)	Alessandro Tuniz, alessandro.tuniz@sydney.edu.au

Type	Description	Weight	Due	Length
Assignment	Reflection tasks Reflections on interdisciplinarity	5%	-	Quiz questions
Outcomes assessed:
Assignment	Computational assignment Tests numerical modeling skills on interdisciplinary computational problems	10%	Multiple weeks	5-10 quiz questions
Outcomes assessed:
Presentation	Online Project design presentation Proposal	5%	Week 08	10 minutes
Outcomes assessed:
Assignment	Research assignment Written assessment summarizing an interdisciplinary physics research paper	10%	Week 08	Maximum 1500 words
Outcomes assessed:
In-semester test	Computer exam Examination of theoretical understanding and numerical skills	30%	Week 11	2 hours
Outcomes assessed:
Presentation	Group presentation and mini-conference Group presentation of research project	15%	Week 13	15 minutes
Outcomes assessed:
Assignment	Meeting notes and peer assessment Meeting notes and peer assessment	5%	Week 13	Notes from all meetings
Outcomes assessed:
Assignment	Project report Project report in the style of a physics journal article	15%	Week 13	Maximum 4000 words
Outcomes assessed:
Assignment	Individual discussion An individual discussion of the project outcomes	5%	Week 13	Maximum 1000 words
Outcomes assessed:
= group assignment ?

Assessment summary

Computational assignments: Students must submit completed versions of the computer tutorials run in weeks 2–6. Students have up to one week following each computational tutorial to submit their completed work.
Research assignment: Students must submit a report summarising a published scientific paper from a module of their choice that includes a discussion by the student about the role of physics in contributing quantitative or mechanistic understanding to real-world phenomena.
Computer exam: In this exam, run online, and will need to perform basic simulations to demonstrate their ability of numerical skills to solve real-world problems.
Project design presentation: Students must present their proposed design for the interdisciplinary project as a group.
Group presentation and mini-conference: Students must present and demonstrate their project as a group in a miniconference format online.
Final project report: The group report summarises the outcomes from the group interdisciplinary project.
Reflection tasks: This series of reflection tasks is in the form of blog posts, assessing the student’s interaction and insight into interdisciplinary project work.

Detailed information for each assessment can be found on Canvas.

Note:

Students are to work together on the project remotely, with one student being responsible for measuring data. In exceptional circumstances, students will be provided with pre-recorded data and emulate real-time data acquisition.All assessments based on group presentations will take place on Zoom, in a virtual classroom/seminar format, with no changes to the dates or weight.

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	At High-distinction level, a student demonstrates a flair for the subject as well as a detailed and comprehensive understanding of the unit material. A ‘High Distinction’ 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 Distinction level, a student demonstrates an aptitude for the subject and a welldeveloped understanding of the unit material. A ‘Distinction’ 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 ‘Credit’ 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 ‘Pass’ reflects satisfactory achievement and is awarded to a student who has threshold knowledge.
Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

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.

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
Week 01	What is interdisciplinary physics?	Lecture (1 hr)
	Introduction to Phys3888 Project Component	Science laboratory (3 hr)
	Working as a Group	Science laboratory (3 hr)
Week 02	Representing complex systems as networks	Lecture (2 hr)
Week 02	Analysing complex networks	Computer laboratory (2 hr)
Week 03	Formulating and simulating complex interactions as dynamical systems	Lecture (2 hr)
	Simulating dynamical systems	Computer laboratory (2 hr)
	Introduction to the EEG hardware and software	Science laboratory (3 hr)
	Measuring Brain Signals - Part 1	Science laboratory (3 hr)
Week 04	Criticality in nature	Lecture (2 hr)
	Measuring, simulating and analysing critical behaviour	Computer laboratory (2 hr)
	Measuring Brain Signals - Part 2	Science laboratory (3 hr)
Week 05	Building learning machines	Lecture (2 hr)
	Simulating learning machines	Computer laboratory (2 hr)
	Real-time signals from brains and machines	Science laboratory (3 hr)
Week 06	Algorithms for artificial intelligence	Lecture (1 hr)
	Statistical learning from data	Computer laboratory (2 hr)
	Optimizing real-time data quality	Science laboratory (3 hr)
Week 07	Group forming and project plan	Science laboratory (3 hr)
Week 08	Project plan presentation	Science laboratory (3 hr)
Week 09	Brain-machine prototype development	Science laboratory (3 hr)
Week 10	Brain-machine prototype development	Science laboratory (3 hr)
Week 11	Brain-machine prototype development	Science laboratory (3 hr)
Week 12	Finalize brain-machine prototype	Science laboratory (3 hr)
Week 13	Brain-machine prototype showcase	Science laboratory (3 hr)

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. understand how physics knowledge and techniques can be used to solve interdisciplinary problems
LO2. analyse, simulate, and model real-world data using statistical and numerical modelling techniques
LO3. collaborate in groups, both within and across disciplinary boundaries, to design and implement a solution to a real-world problem
LO4. demonstrate integrity, confidence, accountability, and resilience in managing challenges, both individually and in teams
LO5. communicate project outcomes effectively to a broad audience.

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.

We have added tutor support for the project component and adjusted the structure of these sessions, to ensure more regular supervision of all project teams. We have provided more examples of questions to test understanding of each module to aid exam preparation. Computer tutorials have been modified to ensure students get the most out of the session, including improved quiz questions and prework.

Additional information

The School of Physics recognises that biases and discrimination, including but not limited to those based on gender, race, sexual orientation, gender identity, religion and age, continue to impact parts of our community disproportionately. Consequently, the School is strongly committed to taking effective steps to make our environment supportive and inclusive and one that provides equity of access and opportunity for everyone.

The School has three Equity Officers as a point of contact for students and staff who may have a query or concern about any issues relating to equity, access and diversity. If you feel you have been treated unfairly, bullied, discriminated against or disadvantaged in any way, you are encouraged to talk to one of the Equity Officers or any member of the Physics staff.

More information can be found at https://sydney.edu.au/science/schools/school-of-physics/equity-access-diversity.html

Any student who feels they may need a special accommodation based on the impact of a disability should contact Disability Services:

http://sydney.edu.au/current_students/disability/ who can help arrange support.

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.

General Laboratory Safety Rules

No eating or drinking is allowed in any laboratory under any circumstances
A laboratory coat and closed-toe shoes are mandatory
Follow safety instructions in your manual and posted in laboratories
In case of fire, follow instructions posted outside the laboratory door
First aid kits, eye wash and fire extinguishers are located in or immediately outside each laboratory
As a precautionary measure, it is recommended that you have a current tetanus immunisation. This can be obtained from University Health Service: unihealth.usyd.edu.au/

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

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Work, health and safety

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect

Current students

PHYS3888: Physics Interdisciplinary Project

Semester 1, 2020 [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

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Work, health and safety

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect