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Unit of study_

ENGG2112: Multi-disciplinary Engineering

Semester 2, 2022 [Normal day] - Remote

ENGG2112 provides an introduction to the context of engineering practice and how engineers engage with other professions in concept development, analysis, and planning. Students are introduced to basic concepts in data science used by engineers to understand problems, support decision making, and run systems. Students will then work within teams to address components of a complex multi-disciplinary project relevant to their chosen engineering stream. In the process, students will consider the influence of contextual factors such as regulatory frameworks, economics, and societal expectations. In doing so, student teams will draw from various fields such as economics, law, business, and the social sciences as they complete the project.

Unit details and rules

Unit code ENGG2112
Academic unit Engineering
Credit points 6
Prohibitions
? 
ENGG1111
Prerequisites
? 
Minimum of 42 cp of engineering foundation/project/stream units of study including one of (AERO1560 or BMET1960 or CHNG1108 or CIVL1900 or ELEC1004 or ELEC1005 or MECH1560 or MTRX1701)
Corequisites
? 
None
Assumed knowledge
? 

None

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator Teng Joon Lim, tj.lim@sydney.edu.au
Type Description Weight Due Length
Presentation Progress updates
Weekly updates in weeks 10, 11, 12
10% Multiple weeks 5 minutes
Outcomes assessed: LO1 LO2
Assignment Reflection
Reflection on what was learned and how it can be applied.
10% STUVAC
Due date: 11 Nov 2022 at 23:00

Closing date: 17 Nov 2022
500 words
Outcomes assessed: LO7
Small continuous assessment Quiz 1
Formative weekly assessment
2.5% Week 03 15 minutes
Outcomes assessed: LO2 LO6 LO5
Small continuous assessment Quiz 2
Formative weekly assessment
2.5% Week 04 15 minutes
Outcomes assessed: LO2 LO6 LO5
Small continuous assessment Quiz 3
Formative weekly assessment
2.5% Week 05 15 minutes
Outcomes assessed: LO2 LO6 LO5
Small continuous assessment Quiz 4
Formative weekly assessment
2.5% Week 06 15 minutes
Outcomes assessed: LO2 LO6 LO5
Assignment group assignment Proposal
Description of project workplan, objectives and deliverables.
10% Week 06
Due date: 09 Sep 2022 at 23:00

Closing date: 16 Sep 2022
500 words
Outcomes assessed: LO1 LO3 LO5 LO7
Assignment Coding assignment
Coding assignment to test ability to code algorithms just introduced.
20% Week 08
Due date: 23 Sep 2022 at 23:00

Closing date: 30 Sep 2022
2 weeks
Outcomes assessed: LO2 LO6 LO4
Presentation group assignment Final presentation
Presentation of key takeaways of the project in tutorials.
10% Week 13 15 minutes
Outcomes assessed: LO1
Assignment group assignment Final report
Final report on project. Requirements will be discussed in class.
30% Week 13
Due date: 04 Nov 2022 at 23:00

Closing date: 11 Nov 2022
4000 words
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7
group assignment = group assignment ?
Group assignment with individually assessed component = group assignment with individually assessed component ?

Assessment summary

Quizzes: Low weightage multiple-choice Canvas quizzes to encourage students to work at a regular pace throughout the first half of the semester.

Presentations: Allow students opportunities to practice the art of succinct and informative oral delivery of information.

Reports: Give students practice in writing clear and concise reports for the knowledgeable layperson.

Coding Assignment: Low weightage assignment to ensure students have ability to use Python to solve basic data science problems.

Assessment criteria

Result Name Mark Range Description

High Distinction

85 – 100 When you have surpassed the required learning outcomes and shown initiative/effort well beyond what was expected
Distinction 75 – 84 When you show that you have achieved the learning outcomes to a very high level
Credit 65 – 74 When you demonstrate a more than adequate achievement of the learning outcomes
Pass 50 – 64 When you barely demonstrate achievement of the learning outcomes
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.

You may only use artificial intelligence and writing assistance tools in assessment tasks if you are permitted to by your unit coordinator, and if you do use them, you must also acknowledge this in your work, either in a footnote or an acknowledgement section.

Studiosity is permitted for postgraduate units unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission.

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.

WK Topic Learning activity Learning outcomes
Ongoing Group project with topics ranging across multiple streams of engineering. Project (60 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7
Weekly Statistics, machine learning, project management Lecture (26 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7
Theory/algorithms of machine learning, implementing ML in Python, project consultations Tutorial (24 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7

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 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.

At the completion of this unit, you should be able to:

  • LO1. Articulate reasoning and justify creative solutions to complex engineering problems/opportunities for a knowledgeable audience.
  • LO2. Find and interpret information autonomously and demonstrate capacity for independent learning.
  • LO3. Apply basic project management techniques to manage self and others in a team, and to plan an engineering solution.
  • LO4. Analyze and manipulate medium-scale datasets to extract meaningful messages.
  • LO5. Under guidance, identify and apply appropriate fundamental concepts and methods to develop an engineering solution.
  • LO6. Understand how data is stored, interpreted and processed for engineering applications.
  • LO7. Appreciate the context of data-driven engineering solutions, including applicable regulatory frameworks, standards and community expectations.

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
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

Alignment with Competency standards

Outcomes Competency standards
LO1
Engineers Australia Curriculum Performance Indicators - EAPI
3.1. An ability to communicate with the engineering team and the community at large.
3.2. Information literacy and the ability to manage information and documentation.
4.5. An ability to undertake problem solving, design and project work within a broad contextual framework accommodating social, cultural, ethical, legal, political, economic and environmental responsibilities as well as within the principles of sustainable development and health and safety imperatives.
5.9. Skills in documenting results, analysing credibility of outcomes, critical reflection, developing robust conclusions, reporting outcomes.
LO2
Engineers Australia Curriculum Performance Indicators - EAPI
3.2. Information literacy and the ability to manage information and documentation.
3.7. A capacity for lifelong learning and professional development and appropriate professional attitudes.
LO3
Engineers Australia Curriculum Performance Indicators - EAPI
3.1. An ability to communicate with the engineering team and the community at large.
3.6. An ability to function as an individual and as a team leader and member in multi-disciplinary and multi-cultural teams.
4.1. Advanced level skills in the structured solution of complex and often ill defined problems.
4.4. Skills in implementing and managing engineering projects within the bounds of time, budget, performance and quality assurance requirements.
4.5. An ability to undertake problem solving, design and project work within a broad contextual framework accommodating social, cultural, ethical, legal, political, economic and environmental responsibilities as well as within the principles of sustainable development and health and safety imperatives.
5.9. Skills in documenting results, analysing credibility of outcomes, critical reflection, developing robust conclusions, reporting outcomes.
LO4
Engineers Australia Curriculum Performance Indicators - EAPI
2.2. Application of enabling skills and knowledge to problem solution in these technical domains.
4.2. Ability to use a systems approach to complex problems, and to design and operational performance.
5.5. Skills in the development and application of mathematical, physical and conceptual models, understanding of applicability and shortcomings.
5.8. Skills in recognising unsuccessful outcomes, sources of error, diagnosis, fault-finding and re-engineering.
LO5
Engineers Australia Curriculum Performance Indicators - EAPI
1.1. Developing underpinning capabilities in mathematics, physical, life and information sciences and engineering sciences, as appropriate to the designated field of practice.
1.2. Tackling technically challenging problems from first principles.
2.2. Application of enabling skills and knowledge to problem solution in these technical domains.
4.1. Advanced level skills in the structured solution of complex and often ill defined problems.
5.5. Skills in the development and application of mathematical, physical and conceptual models, understanding of applicability and shortcomings.
LO6
Engineers Australia Curriculum Performance Indicators - EAPI
2.4. Advanced knowledge and capability development in one or more specialist areas through engagement with: (a) specific body of knowledge and emerging developments and (b) problems and situations of significant technical complexity.
3.2. Information literacy and the ability to manage information and documentation.
5.4. Skills in the selection and application of appropriate engineering resources tools and techniques, appreciation of accuracy and limitations;.
5.8. Skills in recognising unsuccessful outcomes, sources of error, diagnosis, fault-finding and re-engineering.
LO7
Engineers Australia Curriculum Performance Indicators - EAPI
2.1. Appropriate range and depth of learning in the technical domains comprising the field of practice informed by national and international benchmarks.
2.3. Meaningful engagement with current technical and professional practices and issues in the designated field.
3.4. An understanding of and commitment to ethical and professional responsibilities.

This section outlines changes made to this unit following staff and student reviews.

This is the first time this unit has been offered.

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