Computing for Engineers | ENGG1811 26T1

General Course Information

Description

Computing is an integral part of modern engineering. Computing is used in design, automation, experimentation, monitoring, diagnosis, data collection, data analysis, visualisation and many other aspects of engineering. A very important skill for engineers is to be able to use computers to help them to solve problems efficiently. The aim of this course is to give an introduction to computing for engineers with an emphasis on computational problem solving. In order to realise this aim, the students will learn to use the Python programming language and some its many packages to solve problems. Since this course is designed primarily for engineers, the computing examples are often presented together with an engineering context to help the students to appreciate the applications of computing in engineering. This course also includes a minor component in MATLAB and spreadsheets.

Aims

Computational thinking is an important tool that all modern engineers need. This course aims to equip students with the skills required to use programming and computational thinking to solve problems in engineering and related areas, and to assists students in developing familiarity with tools they will use within their own disciplines in later courses.

Learning Outcomes

1. Be able to design algorithms for solving computational problems.
2. Be able to implement algorithms using the Python programming language.
3. Be able to write Python programs to automate many different tasks.
4. Use, at a simple level, the numerical computation packages of MATLAB and Excel.

Assessments

All assessments are individual, i.e. non-group tasks and are designed for you to complete without the use of any generative AI.

You are not permitted to use any generative AI tools, software or service to search for or generate information or answers.

Labs and Self-Directed Labs

There are two types of labs: weekly labs on Python and two self-directed labs.

The weekly Python labs require you to work on some exercises on Python to solve some computation problems. You are asked to demonstrate your completed work to your tutor for marking during your lab timeslot. The marking is based on correctness and completeness of your work. Tutors will also provide feedback of your work. You will also need to answer one multiple choice question during your lab time.

The two self-directed labs are on spreadsheets and MATLAB. You are asked to watch a number of videos on the topic and to complete exercises which you will need to submit for marking. The marking of the self-directed lab is based on the correctness of your submitted work. For the self-directed lab on spreadsheets, a marking report will be provided. For the self-directed lab on MATLAB, the online platform indicates whether you have successfully completed the questions.

The lab marks are weighted as follows:

• Each lab is marked out of 3: 1 mark for an online multiple choice question, and 2 marks for satisfactorily demonstrating your lab work during the respective lab (16% for 8 labs, 2% each lab). Your mark out of 3 is then scaled to a mark out of 2.
• Each self-directed lab (a.k.a. virtual lab) is scaled to a mark out of 2. There are two virtual labs (4% for two self-directed labs).

Assignments

The aim of assignments is to give you an opportunity to develop your Python programming and computational thinking skills by solving an extended computational problem. For this, the assignment specifications will ask you to write a number of Python programs which you will need to submit for marking. The assignment should take 15-20 hours to complete.

Your programs will be marked according to two criteria: correctness and style. Here, correctness means that your programs can successfully perform the tasks required in the assignment specification. The style requirements are given in the assignment specification and a style guide is provided. The weighting for the correctness and style marks are provided in the assignment specification.

You will be provided with a report after the assignment has been marked. The report will indicate which tests the program code has passed, the marks, and any feedback from their tutor on style.

Final Exam

The final exam will be an invigilated practical exam in the laboratory. The exam will take place in the university exam period. The expected duration is 3 hours.

You must obtain at least 40% in the final exam in order to pass the course.

Schedule

The course lecture schedule is subject to change. Laboratory exercises will be based on content presented in previous weeks.

Attendance Requirements

Students are strongly encouraged to attend all classes and review lecture recordings.

Resources

Lecture notes, sample programs and lab exercises will be available on the course website.

This course is designed for engineering students to learn problem solving and programming in an engineering context. It also introduces some computer science concepts. While there is no textbook that covers all of these topics, below is a selection of some general references:

• John Zelle's Python Programming: An Introduction to Computer Science, 3rd Edition
• How To Think Like a Computer Scientist
• Think Python

Evaluation and Development

This course is evaluated each session using the myExperience system. Every term, student feedback is requested in a survey using UNSW's myExperience online survey system where the feedback will be used to make improvements to the course.

You are also encouraged to provide informal feedback during the session, and to let course staff know of any problems as soon as they arise. Suggestions will be listened to openly, positively, constructively, and thankfully, and every reasonable effort will be made to address them.

Special Consideration and Supplementary Assessment

If you have experienced an illness or misadventure beyond your control that will interfere with your assessment performance, you are eligible to apply for Special Consideration prior to, or within 3 working days of, submitting an assessment or sitting an exam.

Please note that UNSW has a Fit to Sit rule, which means that if you sit an exam, you are declaring yourself fit enough to do so and cannot later apply for Special Consideration.

For details of applying for Special Consideration and conditions for the award of supplementary assessment, please see the information on UNSW's Special Consideration page.

Admistrative Matters and Links

All students are expected to read and be familiar with UNSW guidelines and polices. In particular, students should be familiar with the following:

• Attendance
• UNSW email
• Special Consideration
• Exams
• Approved Calculators
• Academic Honesty and Plagiarism
• Equitable Learning Services

Equity and Diversity

Those students who have a disability that requires some adjustment in their teaching or learning environment are encouraged to discuss their study needs with the course convener prior to, or at the commencement of, their course, or with the Equity Officer (Disability) in the Equitable Learning Services. Issues to be discussed may include access to materials, signers or note-takers, the provision of services and additional exam and assessment arrangements. Early notification is essential to enable any necessary adjustments to be made.

Academic Honesty and Plagiarism

UNSW has an ongoing commitment to fostering a culture of learning informed by academic integrity. All UNSW students have a responsibility to adhere to this principle of academic integrity. Plagiarism undermines academic integrity and is not tolerated at UNSW. Plagiarism at UNSW is defined as using the words or ideas of others and passing them off as your own.

Plagiarism is a type of intellectual theft. It can take many forms, from deliberate cheating to accidentally copying from a source without acknowledgement. UNSW has produced a website with a wealth of resources to support students to understand and avoid plagiarism, visit: student.unsw.edu.au/plagiarism. The Learning Centre assists students with understanding academic integrity and how not to plagiarise. They also hold workshops and can help students one-on-one.

You are also reminded that careful time management is an important part of study and one of the identified causes of plagiarism is poor time management. Students should allow sufficient time for research, drafting and the proper referencing of sources in preparing all assessment tasks.

Repeated plagiarism (even in first year), plagiarism after first year, or serious instances, may also be investigated under the Student Misconduct Procedures. The penalties under the procedures can include a reduction in marks, failing a course or for the most serious matters (like plagiarism in an honours thesis or contract cheating) even suspension from the university. The Student Misconduct Procedures are available here.

Submission of Assessment Tasks

Work submitted late without an approved extension by the course coordinator or delegated authority is subject to a late penalty of five percent (5%) for that assessment item.

The late penalty is applied per calendar day (including weekends and public holidays) that the assessment is overdue. There is no pro-rata of the late penalty for submissions made part way through a day. This is for all assessments where a penalty applies.

Work submitted after five days (120 hours) will not be accepted and a mark of zero will be awarded for that assessment item.

For some assessment items, a late penalty may not be appropriate. These will be clearly indicated in the course outline, and such assessments will receive a mark of zero if not completed by the specified date. Examples include:

• Weekly online tests or laboratory work worth a small proportion of the subject mark;
• Exams, peer feedback and team evaluation surveys;
• Online quizzes where answers are released to students on completion;
• Professional assessment tasks, where the intention is to create an authentic assessment that has an absolute submission date; and,
• Pass/Fail assessment tasks.

Faculty-specific Information

• Engineering Student Support Services, for enrolment, progression checks, clash requests, course issues or program-related enquiries.
• Engineering Industrial Training at eng.wil@unsw.edu.au, for industrial training questions.
• UNSW Study Abroad at studyabroad@unsw.edu.au, for study abroad student enquiries (inbound students).
• UNSW Exchange at exchange@unsw.edu.au, for student exchange inquiries (inbound students).
• UNSW Future Students, for potential student enquiries (e.g. admission, fees, programs, credit transfers).

School Contact Information

• CSE Help! on the ground floor of K17, for assistance with coursework assessments.
• The Nucleus Student Hub online or on level 2 of the Main Library, for course enrolment enquiries.
• Grievance Officers at grievance-officer@cse.unsw.edu.au, for if a course convenor gives an inadequate response to a query or when the course convenor does not respond to a query about assessment.
• Student Representatives at stureps@cse.unsw.edu.au, for if some aspect of a course needs urgent improvement (e.g. nobody responds to forum queries or cannot understand the lecturer).

You should never contact any of the following people directly:

• Vice Chancellor,
• Pro-Vice Chancellor Education (PVCE),
• Head of School,
• CSE administrative staff, or
• CSE teaching support staff.

They will forward your email to the student hub, thereby creating an unnecessary level of indirection and a delay in the response.