BMET4010: Semester 1, 2022

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Units BMET4010 Semester 1 2022 [Supervision]

Unit outline_

BMET4010: Major Industrial Project

Semester 1, 2022 [Supervision] - Remote

Overview

Students spend 6 months at an industrial placement working on a major engineering project relevant to their engineering stream. This is a 24 credit point unit, which may be undertaken as an alternative to BMET4111/4112 Thesis A and B, and two recommended electives. This unit of study gives students experience in carrying out a major project within an industrial environment, and in preparing and presenting detailed technical reports (both oral and written) on their work. The project is carried out under joint University/industry supervision, with the student essentially being engaged fulltime on the project at the industrial site.

Unit details and rules

Academic unit	Biomedical Engineering
Credit points	24
Prerequisites ?	[36 credits of 3000 level units of study] and WAM >= 70
Corequisites ?	None
Prohibitions ?	BMET4111 or BMET4112 or ENGG4000 or MECH4601 or AMME4111 or AMME4112 or AMME4010
Assumed knowledge ?	None
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Gregg Suaning, gregg.suaning@sydney.edu.au

Type	Description	Weight	Due	Length
Creative assessment / demonstration	Exit Seminar Thesis presentation to company - date to be advised.	10%	Progressive	Company specific
Outcomes assessed:
Assignment	Progress Report Literature review and report on progress - submission date to be advised.	10%	Progressive	Variable
Outcomes assessed:
Honours thesis	Thesis Report Thesis report - date to be advised.	80%	Progressive	Refer to Canvas guidelines
Outcomes assessed:

Assessment summary

10% Progress Report
10% Thesis Exit Seminar
80% Thesis Report

Assessment criteria

Refer to Canvas for guidelines.

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:

5% per day

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
Multiple weeks	Independent research (planning, designing experiments, performing experiments, analysis and reporting)	Independent study (35 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 24 credit point unit, this equates to roughly 480-600 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. Ability to document and report research work undertaken in a format appropriate for academic literature with correct referencing.
LO2. Ability to deliver a research presentation that is clear, confident and engaging to an academic audience.
LO3. Ability to formulate and plan a personal research project.
LO4. Originality, ingenuity and initiative in dealing with critical research issues.
LO5. In-depth knowledge of a specialised area within the discipline.
LO6. Ability to formulate an appropriate method for investigating a specific research question.
LO7. Ability to analyse data, draw appropriate conclusions and present those conclusions in context, with due consideration of methods and assumptions involved.

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 program is reviewed and reivsed as required each year.

Additional information

Work, health and safety

All research work must be completed in accordance with Company, School, Faculty and University WHS policies. This includes:
- Completing appropriate lab inductions before commencing lab-based work
- Where applicable, completing a risk assessment before commencing experimental work
Ensure that you discuss all WHS-specific aspects of your project with your supervisor at the outset.

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

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