• Class Number 7411
  • Term Code 3360
  • Class Info
  • Unit Value 6 units
  • Mode of Delivery In Person
    • Marnie Shaw
  • Class Dates
  • Class Start Date 24/07/2023
  • Class End Date 27/10/2023
  • Census Date 31/08/2023
  • Last Date to Enrol 31/07/2023
    • Markus Mannheim
    • Patricia Wang-Zhao
    • Benjamin Hofmann
    • Charlotte Fell
    • Andre Vumbaca
    • Catie Travers
    • Tim Rock
SELT Survey Results

Engineering Design 3: Systems Approaches for Analysis will develop your skills to undertake formal testing and evaluation of an engineering design as a technical process in the life-cycle of a system. ED3 is the third course in the interdisciplinary engineering design core, which situates design within the life-cycle of a system. You will learn how to design and execute engineering testing and analysis processes to improve design outcomes. These techniques build on concepts covered in ED2, and are applicable to all areas of engineering.

During the early stages of the course, you will learn tools and approaches for analysing and testing engineering systems. This includes designing models and experiments to predict the behaviour of engineering designs, and working with data to make evidence-based decisions. You will apply techniques to analyse a system from a range of perspectives, from understanding human factors through to optimisation. You will undertake independent study modules on approaches useful for interpreting data and analysing a large range of engineering systems.

Design Project
The major project in this course will be around a real-world engineering problem. You will be challenged in small teams to design the testing processes enabling you to evaluate an engineering design. You will apply research and analysis techniques to optimise or improve an engineering design. During the project, you will develop design outcomes justified through project documentation. Finally, you will develop skills in critical reflection as a part of professional practice by connecting your experiences and learning in your project to engineering and research practice.

Engineering Design @ ANU
At ANU, students are challenged to think of engineering design at a systems-level. Over the degree, you will learn how engineering design can be used to make a positive impact on society through five domains: design, analysis, research, professional practice and teamwork. In ED3, you will connect with your learning in the foundation courses, and develop skills to design tests and undertake analysis essential for justifying engineering design decisions.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

  1. Evaluate an engineering system through the design of engineering tests
  2. Navigate constraints and balance multiple design factors
  3. Make predictions about the performance of a system based on engineering models
  4. Construct clear justifications for design based on data and analysis
  5. Operate as an effective member of an engineering team for an external stakeholder
  6. Provide and act on feedback in a professional environment
  7. Reflect on taking a systems approach to engineering testing in the context of professional engineering

Research-Led Teaching

This course implements research-led teaching using the following approaches to influence, motivate and inspire students to learn:

  • Primer Content - students will be introduced to engineering Analysis tools and approaches via a series of project tools workshops. These will be delivered in flipped classroom mode and interactive workshops. Learning will be assessed via quizzes. Feedback will be provided on workshop outcomes and artefacts.
  • Statistics learning module - This module will be delivered in a flipped classroom mode with interactive tutorials. Learning will be assessed via two quizzes and an individual assignment.
  • Project work - students apply learning from the primer and module to an open-ended authentic design project within a project hub. Projects will be undertaken in small groups as be assessed through a combination of reports and a group interview.

Examination Material or equipment

There is no exam in this course.

Whether you are on campus or studying online, there are a variety of online platforms you will use to participate in your study program. These could include videos for lectures and other instruction, two-way video conferencing for interactive learning, email and other messaging tools for communication, interactive web apps for formative and collaborative activities, print and/or photo/scan for handwritten work and drawings, and home-based assessment.

ANU outlines recommended student system requirements to ensure you are able to participate fully in your learning. Other information is also available about the various Learning Platforms you may use.

Staff Feedback

Students will be given feedback in the following forms in this course:

  • written comments
  • verbal comments
  • feedback to whole class, groups, individuals, focus group etc

Student Feedback

ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). Feedback can also be provided to Course Conveners and teachers via the Student Experience of Learning & Teaching (SELT) feedback program. SELT surveys are confidential and also provide the Colleges and ANU Executive with opportunities to recognise excellent teaching, and opportunities for improvement.

Class Schedule

Week/Session Summary of Activities Assessment
1 Project Tools Workshop: Introduction to Systems AnalysisStatistics Tutorial 1 Statistics quiz 5%
2 Project Tools Workshop: Systems Analysis - TechnicalStatistics Tutorial 2 Workshop quiz 5%
3 Project Tools Workshop: Systems Analysis - EnvironmentalStatistics Tutorial 3 Statistics quiz 5%
4 Project Tools Workshop: Systems Analysis - Social & culturalStatistics Tutorial 4 Workshop quiz 5%
5 Project Tools Workshop: Systems Analysis - EconomicStatistics Tutorial 5 Statistics quiz 5%
6 Project Tools Workshop: Scoping your Analysis Project, getting dataStatistics Tutorial 6 Workshop quiz 5%
7 Project Workshop Project Framing and Analysis Plan Report 20%
8 Project Workshop Statistics Assignment 20%
9 Project Workshop
10 Project Workshop
11 Project Workshop
12 Project Workshop Group Project Presentation and Interview 20%Individual Reflection 10%

Tutorial Registration

Students should sign-up for a project workshop and a Statistics tutorial. Sign-up for workshops and tutorials will be via MyTimetable.

Workshops from week 6, students will work towards their group analysis project in project themes. Information on project themes for each workshop will be available in MyTimetable. Select your workshop and project based on your timetable as well as your interests. Your project team will be formed by the teaching team.

Assessment Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
Analysis Tools Workshop Entry Quizzes (x 3) 15 % * * 1, 2, 4
Statistics Quiz (x 3) 15 % * * 3, 4
Project Framing and Analysis Plan Report 20 % 18/09/2023 02/10/2023 1, 3, 5
Statistics Assignment 20 % 22/09/2023 06/10/2023 3, 4
Project Presentation and Interview 20 % * * 1, 2, 3, 4, 5, 6, 7
Reflection 10 % 27/10/2023 * 6, 7

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details


ANU has educational policies, procedures and guidelines , which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Integrity Rule before the commencement of their course. Other key policies and guidelines include:

Assessment Requirements

The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the Academic Skills website. In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Wattle’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.

Moderation of Assessment

Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.


There is no exam in this course.

Assessment Task 1

Value: 15 %
Learning Outcomes: 1, 2, 4

Analysis Tools Workshop Entry Quizzes (x 3)

Three Wattle quizzes that will assess student understanding of the Analysis Tools Workshop pre-material as well as the learning from the workshop (each worth 5%).

Assessment Task 2

Value: 15 %
Learning Outcomes: 3, 4

Statistics Quiz (x 3)

Three Wattle quizzes that will assess student understanding of the statistics module (each worth 5%).

Assessment Task 3

Value: 20 %
Due Date: 18/09/2023
Return of Assessment: 02/10/2023
Learning Outcomes: 1, 3, 5

Project Framing and Analysis Plan Report

The Project Framing and Analysis Plan Report finalises a teams interpretation of the project brief and project scope. It details assumptions made, constraints identified and the key stakeholders for the project. It also details the analysis tools the team will use to analyse the project, who will be responsible for each tool and how the tool or tools will be adapted to contribute to the overall analysis of the project.

The submission will be a report with an individual component (60%) and group component (40%) submitted via Turnitin.

For marking rubrics, see Wattle.

Assessment Task 4

Value: 20 %
Due Date: 22/09/2023
Return of Assessment: 06/10/2023
Learning Outcomes: 3, 4

Statistics Assignment

Understanding data and applying statistical methods is an essential skill for modern engineers. This assignment will provide an opportunity for students to showcase the data analytic skills they have learnt across six tutorials on data and statistics.

The report will be submitted via Turnitin and the code will be submitted via Wattle.

Assessment Task 5

Value: 20 %
Learning Outcomes: 1, 2, 3, 4, 5, 6, 7

Project Presentation and Interview

The major project in this course will involve analysing a real-world engineering problem. You will be challenged in small teams to analyse and evaluate an engineering design using a systems approach, taking into consideration the requirements of project stakeholders. 

The findings of this analysis will be submitted as a group presentation and interview with the teaching team and key project stakeholder.

The presentation and interview will take place in week 12 and be worth 20% of the course total. Supporting material for the presentation and interview will be submitted via Turnitin.

Assessment Task 6

Value: 10 %
Due Date: 27/10/2023
Learning Outcomes: 6, 7


For this assignment, completed individually, you should reflect on how your team applied a systems approach for analysis to address your project brief.

Students can choose between submission of a report (including appendices) via Turnitin or an in-person interview. Students must also submit a reflection logbook via Wattle.

Academic Integrity

Academic integrity is a core part of the ANU culture as a community of scholars. The University’s students are an integral part of that community. The academic integrity principle commits all students to engage in academic work in ways that are consistent with, and actively support, academic integrity, and to uphold this commitment by behaving honestly, responsibly and ethically, and with respect and fairness, in scholarly practice.

The University expects all staff and students to be familiar with the academic integrity principle, the Academic Integrity Rule 2021, the Policy: Student Academic Integrity and Procedure: Student Academic Integrity, and to uphold high standards of academic integrity to ensure the quality and value of our qualifications.

The Academic Integrity Rule 2021 is a legal document that the University uses to promote academic integrity, and manage breaches of the academic integrity principle. The Policy and Procedure support the Rule by outlining overarching principles, responsibilities and processes. The Academic Integrity Rule 2021 commences on 1 December 2021 and applies to courses commencing on or after that date, as well as to research conduct occurring on or after that date. Prior to this, the Academic Misconduct Rule 2015 applies.


The University commits to assisting all students to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. All coursework students must complete the online Academic Integrity Module (Epigeum), and Higher Degree Research (HDR) students are required to complete research integrity training. The Academic Integrity website provides information about services available to assist students with their assignments, examinations and other learning activities, as well as understanding and upholding academic integrity.

Online Submission

You will be required to electronically sign a declaration as part of the submission of your assignment. Please keep a copy of the assignment for your records. Unless an exemption has been approved by the Associate Dean (Education) submission must be through Turnitin.

Hardcopy Submission

For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.

Late Submission

Individual assessment tasks may or may not allow for late submission. Policy regarding late submission is detailed below:

  • Late submission not permitted. If submission of assessment tasks without an extension after the due date is not permitted, a mark of 0 will be awarded.
  • Late submission permitted. Late submission of assessment tasks without an extension are penalised at the rate of 5% of the possible marks available per working day or part thereof. Late submission of assessment tasks is not accepted after 10 working days after the due date, or on or after the date specified in the course outline for the return of the assessment item. Late submission is not accepted for take-home examinations.

Referencing Requirements

The Academic Skills website has information to assist you with your writing and assessments. The website includes information about Academic Integrity including referencing requirements for different disciplines. There is also information on Plagiarism and different ways to use source material.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. Extensions may be granted for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.

Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information.
In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service – including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy.
If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

Distribution of grades policy

Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes.

Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.

Support for students

The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).

Marnie Shaw

Research Interests

Data Analytics, Machine Learning, Renewable Energy, Brain imaging

Marnie Shaw

By Appointment
Markus Mannheim

Research Interests

Markus Mannheim

Patricia Wang-Zhao

Research Interests

Data Analytics, Machine Learning, Renewable Energy, Brain imaging

Patricia Wang-Zhao

Benjamin Hofmann

Research Interests

Data Analytics, Machine Learning, Renewable Energy, Brain imaging

Benjamin Hofmann

Charlotte Fell

Research Interests

Data Analytics, Machine Learning, Renewable Energy, Brain imaging

Charlotte Fell

Andre Vumbaca

Research Interests

Data Analytics, Machine Learning, Renewable Energy, Brain imaging

Andre Vumbaca

Catie Travers

Research Interests

Data Analytics, Machine Learning, Renewable Energy, Brain imaging

Catie Travers

Tim Rock

Research Interests

Data Analytics, Machine Learning, Renewable Energy, Brain imaging

Tim Rock


Responsible Officer: Registrar, Student Administration / Page Contact: Website Administrator / Frequently Asked Questions