Unit Outline

This unit introduces students to computer-based tools for solving engineering problems. Students will engage with key concepts such as mathematical programming, artificial intelligence, and computer-aided design (CAD). They will develop practical skills in data analysis, software design, CAD modeling, and report writing through hands-on lab work and projects. The unit emphasizes the correctness and efficiency of solutions, preparing students for advanced studies in computer-aided engineering and problem-solving. Learning experiences include individual and group projects, where students will apply programming techniques to analyze climate change and embedded carbon data.

Intended Learning Outcomes

As per the Assessment and Results Policy 1.3, your results will reflect your achievement against specified learning outcomes.

On completion of this unit, you will be able to:


1	Develop structured programs relevant to engineering problems in a high level language.
2	Solve fundamental engineering problems using artificial intelligence based tools.
3	Design engineering solutions using models, flow charts and algorithms.
4	Use computer aided design tools and hand drawing techniques to represent physical models.
5	Analyse data from an engineering experiment using programming techniques with application to climate change and embedded carbon data.

Alterations as a result of student feedback

How will I be Assessed?

For more detailed assessment information please see MyLO.

Assessment schedule


ASSESSMENT TASK #	ASSESSMENT TASK NAME	DATE DUE	WEIGHT	LINKS TO INTENDED LEARNING OUTCOMES
Assessment Task 1:	Data Analysis Assignment	Week 8	30 %	LO2, LO5
Assessment Task 2:	Arduino Project	Week 10	30 %	LO3
Assessment Task 3:	CAD Assignments	Week 13	25 %	LO4
Assessment Task 4:	Programming Exercises	Refer to Assessment Description	15 %	LO1, LO2

Assessment details

Assessment Task 1: Data Analysis Assignment

Task Description:

This data analysis assignment assesses student ability to extend rudiments of programming knowledge and problem-solving skills to read, process and present results of experimental data.
Students will be given a dataset and must use a combination of AI-generated and manual programming scripts to answer questions about the data. Questions asked about the data may include unfamiliar concepts and require as yet untaught techniques to answer, and as such students will be required to independently gain new knowledge. Where AI has been used to gain knowledge or generate scripts, documentation of the questions asked of the AI and how the answers were used must be provided.
Students will be assessed through an interview where the programme and AI use will be presented and technical questions relating to these must be answered.
This assignment will prepare students for data processing requirements in future units as well as AI use where it is permitted or required. Generative AI use is required and must be acknowledged.

Task Length:

10 hours

Due Date:

Week 8

Weight:

30 %

CRITERION #

CRITERION

MEASURES INTENDED

LEARNING OUTCOME(S)


1	Analyse climate change data and make scenario predictions using programming techniques	LO5
2	Use programming techniques for embedded and embodied calculations.	LO5
3	Analyse AI produced solutions with a focus on correctness and efficiency.	LO2

Assessment Task 2: Arduino Project

Task Description:

In this programming project students will work both individually and in a team to solve more complex and integrated problems by programming a robotic vehicle.
Students will develop a solution to a given problem, first individually through use of simulation tools, and then in a group through development of a program on a physical vehicle.
These tasks will introduce students to basic design processes and teamwork, preparing them for future programming and team-based projects. Peer review will be part of this assessment. Generative AI use is permitted but must be acknowledged.

Task Length:

Presentation 10-20 min, Report 10-20 pages

Due Date:

Week 10

Weight:

30 %

CRITERION #

CRITERION

MEASURES INTENDED

LEARNING OUTCOME(S)


1	Implement a programming solution in a team environment.	LO3
2	Apply computational thinking to solution design.	LO3
3	Identify the components of an engineering problem.	LO3
4	Draw models that represent the components of an engineering solution.	LO3
5	Identify the processes required to solve an engineering problem.	LO3
6	Draw flow charts that represent the processes of an engineering solution.	LO3
7	Write an algorithm that represents the process of an engineering solution.	LO3

Assessment Task 3: CAD Assignments

Task Description:

During the CAD module of the course, students will complete weekly assignments to demonstrate the development of CAD and drawing skills.
Students will develop skills in 2D and 3D modelling, parametric and constrained based modelling, component based modelling, modelling for manufacture and presentation of a model according to Australian standards. The CAD module will run between weeks 7 and 12, and four submissions will be required. Generative AI use is permitted but must be acknowledged.

Task Length:

2 hours per week for 4 weeks

Due Date:

Week 13

Weight:

25 %

CRITERION #

CRITERION

MEASURES INTENDED

LEARNING OUTCOME(S)


1	Sketch 3D models in a variety of projections using hand drawing techniques.	LO4
2	Sketch 3D models in a variety of projections using a computer aided design tool.	LO4
3	Output various 2D representations from a 3D CAD model.	LO4
4	Present 3D CAD models according to the Australian standard.	LO4

Assessment Task 4: Programming Exercises

Task Description:

During the programming module, students will complete a series of theoretical problems to be solved weekly and assessed periodically during semester.
The earlier exercises will require students to solve basic problems using standard procedural programming techniques. Later exercises will require students to resolve the same problems using AI tools and critically compare the results for correctness and efficiency.
Skills developed during these exercises will prepare students for the application of programming, AI and problem-solving skills to the practical Engineering problems in the project and future units that require the use of these tools.
The programming module will run between weeks 1 to 7 and four submissions will be required.

Week due: 2-5

Task Length:

1.5 hours per week over 4 weeks

Due Date:

Refer to Assessment Description

Weight:

15 %

CRITERION #

CRITERION

MEASURES INTENDED

LEARNING OUTCOME(S)


1	Identify methods for solving engineering problems using a high level language.	LO1
2	Compare different methods for solving engineering problems using a high level language.	LO1
3	Solve engineering problems using a high level language.	LO1
4	Classify aspects of engineering problems that can be solved with an AI tool.	LO2
5	Solve engineering problems using AI tools.	LO2
6	Analyse AI produced solutions with a focus on correctness and efficiency.	LO2

How your final result is determined

To pass this unit, you need to demonstrate your attainment of each of the Intended Learning Outcomes, achieve a final unit grade of 50% or greater, and pass any hurdle tasks.

Academic progress review

The results for this unit may be included in a review of your academic progress. For information about progress reviews and what they mean for all students, see Academic Progress Review in the Student Portal.

Submission of assignments

Where practicable, assignments should be submitted to an assignment submission folder in MYLO. You must submit assignments by the due date or receive a penalty (unless an extension of time has been approved by the Unit Coordinator). Students submitting any assignment in hard copy, or because of a practicum finalisation, must attach a student cover sheet and signed declaration for the submission to be accepted for marking.

Academic integrity

Academic integrity is about acting responsibly, honestly, ethically, and collegially when using, producing, and communicating information with other students and staff members.

In written work, you must correctly reference the work of others to maintain academic integrity. To find out the referencing style for this unit, see the assessment information in the MyLO site, or contact your teaching staff. For more detail about Academic Integrity, see Important Guidelines & Support.

Requests for extensions

If you are unable to submit an assessment task by the due date, you should apply for an extension.

A request for an extension should first be discussed with your Unit Coordinator or teaching support team where possible. A request for an extension must be submitted by the assessment due date, except where you can provide evidence it was not possible to do so. Typically, an application for an extension will be supported by documentary evidence: however, where it is not possible for you to provide evidence please contact your Unit Coordinator.

The Unit Coordinator must notify you of the outcome of an extension request within 3 working days of receiving the request.

Late penalties

Assignments submitted after the deadline will receive a late penalty of 5% of the original available mark for each calendar day (or part day) that the assignment is late. Late submissions will not be accepted more than 10 calendar days after the due date, or after assignments have been returned to other students on a scheduled date, whichever occurs first. Further information on Late Penalties can be found on the Assessments and Results Procedure.