Course coordinator
Dr Chamith Wijenayake
Consultation hours will be added on course Blackboard site.
Course overview
- Study period
- Semester 1, 2025 (24/02/2025 - 21/06/2025)
- Study level
- Undergraduate
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Elec Engineering & Comp Science School
Introduction to digital logic and digital systems; machine level representation of data; computer organization; memory system organization and architecture; interfacing and communication; microcontroller architecture and usage; programming of microcontroller based systems.
CSSE2010 is an introduction to how computers work at the lowest levels and will cover topics from binary number representations, logic gates, combinational and sequential logic circuits, low-levelﾠassembly language and basic (embedded) C programming. After this course you'll have a basic understanding of how computers work and you'll be able to develop programs for a microcontroller based computer system.
Course requirements
Assumed background
Programming experience is expected prior to this course - you should have successfully completed CSSE1001/ENGG1001 or have equivalent experience.
Prerequisites
You'll need to complete the following courses before enrolling in this one:
CSSE1001 or ENGG1001
Incompatible
You can't enrol in this course if you've already completed the following:
COMP1300 or COMP2303 or COMP2302 or CSSE1000 or CSSE7035 or CSSE7201 or ELEC2002
Jointly taught details
This course is jointly-taught with:
- CSSE7201
All learning activities are jointly taught.
Course contact
Course staff
Lecturer
Dr Chamith Wijenayake
Dr Martin Ploschner
Timetable
The timetable for this course is available on the UQ Public Timetable.
Aims and outcomes
The general aim of this course is for students to understand how computers and software work at the lowest levels (binary numbers, logic gates, memory, assembly language etc.) and be able to program a microcontroller based system using both assembly language and the C programming language. (Such systems make up the vast majority of computing systems in the world.)
A low level understanding of computer hardware helps students to understand the implications (e.g. performance) of software design and implementation decisions. The course also prepares students for various possible follow-on courses, including CSSE2310 (Computer Systems Principles and Programming), ENGG2800/METR2800 (Engineering Team Project 1), CSSE3010 (Embedded Systems Design & Interfacing) and CSSE4010 (Digital System Design).
Learning outcomes
After successfully completing this course you should be able to:
LO1.
convert unsigned integers, signed integers and floating point numbers to and from various binary number representations and perform operations on those binary numbers
LO2.
express logic functions in various representations (gates, expressions, truth-tables, timing diagrams) and be able to convert those functions between representations
LO3.
design, analyse, simulate and build combinational circuits and simple sequential circuits
LO4.
explain the operation of a CPU with respect to its major components, and instruction set architecture, with specific emphasis on the AVR microcontroller
LO5.
demonstrate your knowledge of flow-of-control and the use of a stack in a CPU and be able to write procedures and interrupt service routines in both AVR assembly language and C
LO6.
describe the major components of a computer system and how they communicate and be able to perform calculations on their characteristics
LO7.
simulate the processes of assembly and linking on sample code
LO8.
modify, write, simulate, debug, assemble/compile and download assembly language and C programs targeted to the AVR microcontroller and be able to construct associated AVR hardware and peripherals
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Quiz |
Weekly online quizzes
|
10% |
Quiz 1 28/02/2025 4:00 pm Quiz 2 14/03/2025 4:00 pm Quiz 3 21/03/2025 4:00 pm Quiz 4 28/03/2025 4:00 pm Quiz 5 4/04/2025 4:00 pm Quiz 6 11/04/2025 4:00 pm Quiz 7 2/05/2025 4:00 pm Quiz 8 9/05/2025 4:00 pm Quiz 9 16/05/2025 4:00 pm Quiz 10 23/05/2025 4:00 pm |
| Paper/ Report/ Annotation, Practical/ Demonstration |
Assignment 1 (Digital Logic Design)
|
20% |
17/04/2025 4:00 pm |
| Computer Code, Practical/ Demonstration, Project |
Assignment 2 (AVR Programming)
|
20% |
30/05/2025 4:00 pm |
| Examination |
Final Examination
|
50% |
End of Semester Exam Period 7/06/2025 - 21/06/2025 |
A hurdle is an assessment requirement that must be satisfied in order to receive a specific grade for the course. Check the assessment details for more information about hurdle requirements.
Assessment details
Weekly online quizzes
- Online
- Mode
- Activity/ Performance
- Category
- Quiz
- Weight
- 10%
- Due date
Quiz 1 28/02/2025 4:00 pm
Quiz 2 14/03/2025 4:00 pm
Quiz 3 21/03/2025 4:00 pm
Quiz 4 28/03/2025 4:00 pm
Quiz 5 4/04/2025 4:00 pm
Quiz 6 11/04/2025 4:00 pm
Quiz 7 2/05/2025 4:00 pm
Quiz 8 9/05/2025 4:00 pm
Quiz 9 16/05/2025 4:00 pm
Quiz 10 23/05/2025 4:00 pm
- Learning outcomes
- L01, L02, L03, L04, L05, L06, L07
Task description
Ten weekly quizzes will be used with the specific submission due dates as indicated. Quizzes will open at least 3 days prior to the due date.
Quizzes will usually cover topics from the previous week or two of classes, but may cover topics from any previous week and/or may require students to do some research or reading beyond the class notes. Students are expected to take the quiz individually and on their own time and these weekly quizzes are designed to keep students up to date with the week by week teaching material. Each quiz must be explicitly submitted by the due date (i.e. quizzes are not auto-submitted) and there is only one attempt for each quiz.
This assessment item is open-book and students may use whichever resources they think appropriate when answering them. These resources may include course notes, books, data sheets, manuals and tools including calculators, assemblers, compilers, search engines and AI tools. You do not need to reference the source of your answers. You must not communicate with other people when attempting the quizzes.
Submission guidelines
Submission via Blackboard.
Deferral or extension
You cannot defer or apply for an extension for this assessment.
No extensions available and 100% Late penalty applied for the online quizzes as results and feedback are released immediately after the due date. To accommodate unforeseen circumstances such as illness, your mark will be based on the best 8 out of the 10 submissions, each worth 1.25%.
If a student misses more than two quizzes due to exceptional circumstances (supported by documentation) then they may seek an exemption from the third (and subsequent) missed quizzes. If N such exemptions are granted, the student's result will be calculated using their best 8-N quiz results, weighted 1.25% each, with the final exam weight being increased by 1.25*N%.
Late submission
You will receive a mark of 0 if this assessment is submitted late.
No late submissions are possible as solutions and feedback are released immediately after the due time.
Assignment 1 (Digital Logic Design)
- In-person
- Online
- Mode
- Activity/ Performance, Written
- Category
- Paper/ Report/ Annotation, Practical/ Demonstration
- Weight
- 20%
- Due date
17/04/2025 4:00 pm
- Learning outcomes
- L01, L02, L03, L04
Task description
Students will be required to provide worked solutions to a set of problems based on Digital Logic Design concepts and demonstrate a working solution for a selected problem on hardware. This is an individual assignment. The scope and complexity of the problems will be based on lectures and lab activities from week 1-5 (inclusive). Students are required to submit their assignment on Blackboard by the due date (Thursday of week 8, 17/4/25, 4:00pm AEST).
This assessment item has been designed to be challenging, authentic and complex. Whilst students may use AI technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance. A failure to reference AI use may constitute student misconduct under the Student Code of Conduct. To pass this assessment, students will be required to demonstrate detailed comprehension of their written submission independent of AI tools.
Submission guidelines
Online submission on Blackboard by the due date (Thursday of week 8, 17/4/25, 4:00pm AEST).
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 7 days. Extensions are given in multiples of 24 hours.
This course uses a progressive assessment approach where feedback and/or detailed solutions will be released to students within 14 days.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Assignment 2 (AVR Programming)
- Hurdle
- Mode
- Activity/ Performance
- Category
- Computer Code, Practical/ Demonstration, Project
- Weight
- 20%
- Due date
30/05/2025 4:00 pm
- Learning outcomes
- L08
Task description
Students will undertake a programming task for the AVR microcontroller (may contain a number of sub-tasks) which implements a system for a given set of specifications. You may be asked to attend a subsequent oral assessment (interview) if the course coordinator has any doubts about the origin of your submission. Invitations for such oral assessments will be issued by email to your student email account at any time up until the end of week one of the exam period. Failure to respond to an interview invitation by the deadline stated in the invitation (which will be at least 3 days after the invitation is sent) or failure to attend a scheduled interview will result in zero marks for the assignment unless exceptional circumstances can be demonstrated with supporting evidence.
This assessment item has been designed to be challenging, authentic and complex. Whilst students may use AI technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance. A failure to reference AI use may constitute student misconduct under the Student Code of Conduct. To pass this assessment, students will be required to demonstrate detailed comprehension of their written submission independent of AI tools.
Hurdle requirements
You must achieve at least 10% on this item to pass the course.Submission guidelines
Submit via Blackboard
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 7 days. Extensions are given in multiples of 24 hours.
This course uses a progressive assessment approach where feedback and/or detailed solutions will be released to students within 14 days.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Final Examination
- Hurdle
- Identity Verified
- In-person
- Mode
- Written
- Category
- Examination
- Weight
- 50%
- Due date
End of Semester Exam Period
7/06/2025 - 21/06/2025
- Other conditions
- Time limited.
- Learning outcomes
- L01, L02, L03, L04, L05, L06, L07, L08
Task description
An on campus, open-book, invigilated exam will be held during the final examination period. This exam can contain multiple-choice, short-answer, numerical and code-writing type questions. Open-book means that you may bring any written or printed material (including books) into the examination room.
This assessment item is to be completed in-person. The use of Artificial Intelligence (AI) tools will not be permitted. Any attempted use of AI may constitute student misconduct under the Student Code of Conduct.
Hurdle requirements
You must achieve at least 40% on this item to pass the course.Exam details
| Planning time | 10 minutes |
|---|---|
| Duration | 120 minutes |
| Calculator options | (In person) Casio FX82 series only or UQ approved and labelled calculator |
| Open/closed book | Open Book examination |
| Exam platform | Paper based |
| Invigilation | Invigilated in person |
Submission guidelines
Deferral or extension
You may be able to defer this exam.
Course grading
Full criteria for each grade is available in the Assessment Procedure.
| Grade | Description |
|---|---|
| 1 (Low Fail) |
Absence of evidence of achievement of course learning outcomes. Course grade description: At least one item of work submitted or exam/test attempted but cumulative percentage (see below) is less than 20. |
| 2 (Fail) |
Minimal evidence of achievement of course learning outcomes. Course grade description: Cumulative Percentage (see below) is in the range 20 to 46 inclusive. |
| 3 (Marginal Fail) |
Demonstrated evidence of developing achievement of course learning outcomes Course grade description: Cumulative Percentage (see below) is in the range of 47 to 49 inclusive. |
| 4 (Pass) |
Demonstrated evidence of functional achievement of course learning outcomes. Course grade description: Cumulative Percentage (see below) is in the range of 50 to 64 inclusive. |
| 5 (Credit) |
Demonstrated evidence of proficient achievement of course learning outcomes. Course grade description: Cumulative Percentage (see below) is in the range of 65 to 74 inclusive. |
| 6 (Distinction) |
Demonstrated evidence of advanced achievement of course learning outcomes. Course grade description: Cumulative Percentage (see below) is in the range of 75 to 84 inclusive |
| 7 (High Distinction) |
Demonstrated evidence of exceptional achievement of course learning outcomes. Course grade description: Cumulative Percentage (see below) is greater than or equal to 85. |
Additional course grading information
Your cumulative percentage will be the sum out of 100 of your overall assessment marks which is then rounded to the nearest whole percent and then possibly capped as described below.
Your cumulative percentage will be capped as described in the following situations. If more than one scenario applies to you, then the cap will be the lowest specified in the applicable scenarios:
- If your final exam mark is less than 40% OR your Assignment 2 (AVR programming) mark is less than 10% then your cumulative percentage will be capped at 49 and your maximum possible grade is a 3.
- If your Assignment 2 (AVR programming) mark is less than 50% then your cumulative percentage will be capped at 74 and your maximum possible grade is a 5.
- If your final exam mark is less than 75% then your cumulative percentage will be capped at 84 and your maximum possible grade is a 6.
A summary of these hurdles are given below as requirements to achieve a certain grade:
- To obtain a grade of 4 or better (i.e. to pass the course) you must achieve 40% or better on the final exam AND 10% or better on Assignment 2 (AVR programming) ANDﾠ50% or better overall.
- To obtain a grade of 5 or better, in addition, you must achieve 65% or better overall
- To obtain a grade of 6 or better, in addition, you must achieve 50% or better on Assignment 2 (AVR programming) AND 75% or better overall
- To obtain a grade of 7, in addition, you must achieve 75% or better in the final exam AND 85% or better overall
Supplementary assessment
Supplementary assessment is available for this course.
If you are awarded a supplementary assessment, then your supplementary assessment can take the form of a supplementary exam or a supplementary assignment or an oral assessment or a combination of these. The course coordinator will determine the form of the supplementary assessment based on your performance in the assessment items of the course. In all cases, you must achieve at least 50% of the supplementary assessment to pass the course (i.e., to receive a grade of 3S4).
Additional assessment information
Having Troubles?
If you are having difficulties with any aspect of the course material, you should seek help. Speak to the course teaching staff.
If external circumstances are affecting your ability to work on the course, you should seek help as soon as possible. The University and UQ Union have organisations and staff who are able to help, for example, UQ Student Services are able to help with study and exam skills, tertiary learning skills, writing skills, financial assistance, personal issues, and disability services (among other things).
Complaints and criticisms should be directed in the first instance to the course coordinator via CSSE2010@eecs.uq.edu.au. If you are not satisfied with the outcome, you may bring the matter to the attention of the School of EECS Director of Teaching and Learning.
Learning resources
You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.
Library resources
Find the required and recommended resources for this course on the UQ Library website.
Other course materials
If we've listed something under further requirement, you'll need to provide your own.
Required
| Item | Description | Further Requirement |
|---|---|---|
| Lab kit | A lab kit will be loaned to students during weeks 1 to 4. The kit must be returned at the end of the semester. |
Learning activities
The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.
Filter activity type by
Please select
| Learning period | Activity type | Topic |
|---|---|---|
Multiple weeks From Week 1 To Week 13 |
Lecture |
Weekly Lecture There are two 1-hour weekly lectures (Mon 10-11am and Wed 5-6pm). Refer to detailed teaching outline on Blackboard for more information about public holidays and refer to student timetable for any updates on the venues/times. Lectures are expected to be recorded and made available on the course Blackboard site, although there is no guarantee that recordings will always work. Lectures provide an introduction to the course material and present examples to help students understand the principles and techniques. There may be recommended reading or other activities which should be undertaken before a lecture. Please note that the lecture slides in the course notes may NOT be a complete record of the lecture. Examples will be worked through and exercises undertaken which may not be shown on the slides. Interactive polls may be used to assess understanding and get feedback from students. It is strongly suggested that you attend the lectures or watch the recording each week to maintain progressive learning. Learning outcomes: L01, L02, L03, L04, L05, L06, L07, L08 |
Practical |
Learning Lab Sessions You must sign-up for a pair of prac sessions out of the 6 pairs available (PRA-x-P2, PRA-x-P1), where x=1,2,...,6. All prac sessions will be held in the Axon Building Computer Laboratory (building 47, room 104) in face-to-face mode. These lab classes will start with their P1 sessions from Wed-Fri of Week 1. No P2 sessions are held during Mon-Wed of week 1. From week 2 to week 13 both P2 and P1 sessions will be held (refer to the detailed teaching outline on Blackboard for more information about public holidays). Students will be loaned a kit during their lab classes in weeks 1-4, which must be returned by the end of the semester. You must have a lab kit with you in order to complete and pass the course. Lab kits must be collected in-person during lab classes in weeks 1-4. If you borrow a lab kit and drop the course then you must return the kit within 3 business days to EECS school office at building 78 room 425 (penalties apply otherwise). Learning outcomes: L01, L02, L03, L05, L08 |
Additional learning activity information
Attendance
Attendance is not compulsory for lectures and learning lab sessions (except those in which an assessment activity is taking place), however, you are strongly encouraged to attend all the lectures and learning labs each week. The lectures and learning lab sessions have been specifically designed and sequenced to aid your progressive learning of the course material. Failure to attend a session may result in you being disadvantaged. It is up to you to find out what happened at any class session that you miss and make yourself up to date prior to attending the next lecture/lab.
Should you miss a learning lab session due to extenuating circumstances, you may be able to attend an alternative session if space permits. Contact the course coordinator. You should be prepared to provide documentary evidence of extenuating circumstances (e.g., medical certificate).
Expected time commitment
The minimum expected time commitment required to be successful in this course is 10 hours per week from week 1 till the end of the semester, with a recommended breakdown as: 2 hours of lectures, 4 hours of lab classes, 3 hours of self-study, 1 hour for exercises and quizzes. It is up to individual students to manage their time effectively.
Policies and procedures
University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:
- Student Code of Conduct Policy
- Student Integrity and Misconduct Policy and Procedure
- Assessment Procedure
- Examinations Procedure
- Reasonable Adjustments - Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.
School guidelines
Your school has additional guidelines you'll need to follow for this course: