Unit outline_

ELEC1601: Introduction to Computer Systems

Semester 1, 2026 [Normal day] - Camperdown/Darlington, Sydney

This unit of study introduces the fundamental digital concepts upon which the design and operation of modern digital computers are based. A prime aim of the unit is to develop a professional view of, and a capacity for inquiry into, the field of computing. Topics covered include: data representation, basic computer organisation, the CPU, elementary gates and logic, machine language, assembly language and high level programming constructs.

Unit details and rules

Academic unit School of Electrical and Computer Engineering
Credit points 6
Prerequisites
? 
None
Corequisites
? 
None
Prohibitions
? 
None
Assumed knowledge
? 

HSC Mathematics extension 1 or 2

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator Sridevan Parameswaran, sri.parameswaran@sydney.edu.au
The census date for this unit availability is 31 March 2026
Type Description Weight Due Length Use of AI
Written exam Final exam
End of semester exam. Advanced grades awarded
30% Formal exam period 2 hours AI prohibited
Outcomes assessed: LO3 LO2 LO1
In-person written or creative task Extensions Quizzes
Test extension knowledge. 3 quizzes.
10% Multiple weeks 30 AI prohibited
Outcomes assessed: LO3 LO2 LO1
In-person written or creative task hurdle task Fundamentals quizzes
Test essential knowledge. Four quizzes, each worth 2.5%
25% Multiple weeks 30 mins AI prohibited
Outcomes assessed: LO2 LO1
Q&A following presentation, submission or placement hurdle task group assignment Lab Completion (Essential)
Lab completion marked. Groups of 2 AI Allowed in implementation, but must be able to fully explain everything in oral to demonstrator without AI
15% Multiple weeks During lab AI limited - refer to Canvas
Outcomes assessed: LO3 LO7 LO4
Practical skill hurdle task group assignment Early Feedback Task Laboratory Attendance
Lab attendance, group sign-up and participation. #earlyfeedbacktask
0% Week 03 N/A AI allowed
Outcomes assessed: LO7 LO4 LO2 LO1
Q&A following presentation, submission or placement group assignment Project (Advanced)
Rubric to be announced. Marks may be awarded to differentiate group/individual performance AI Allowed in implementation, but must be able to fully explain everything in oral to demonstrator without AI
5% Week 13 N/A AI limited - refer to Canvas
Outcomes assessed: LO6 LO7 LO4 LO5
Q&A following presentation, submission or placement group assignment Project (Extension)
Rubric to be announced. Marks may be awarded to differentiate group/individual performance AI Allowed in implementation, but must be able to fully explain everything in oral to demonstrator without AI
5% Week 13 N/A AI limited - refer to Canvas
Outcomes assessed: LO6 LO7 LO4 LO5
Q&A following presentation, submission or placement hurdle task group assignment Project (Essential)
Assessed in lab over multiple weeks. Rubric to be specified. Groups of 3 AI Allowed in implementation, but must be able to fully explain everything in oral to demonstrator without AI
10% Week 13 N/A AI limited - refer to Canvas
Outcomes assessed: LO6 LO7 LO4 LO5
hurdle task = hurdle task ?
group assignment = group assignment ?
early feedback task = early feedback task ?

Early feedback task

This unit includes an early feedback task, designed to give you feedback prior to the census date for this unit. Details are provided in the Canvas site and your result will be recorded in your Marks page. It is important that you actively engage with this task so that the University can support you to be successful in this unit.

Assessment summary

  • This unit is has split the assessment into 3 levels 

    • Essentials - The foundational knowledge and application required to move beyond ELEC1601/ELEC9601, achieving ‘competent’ in this represents a ‘50 Pass’ standard. 

    • Extension – Concepts and applications that builds on what has been introduced in essentials. Competent in this represents between a P and C level. 

    • Advanced – Concepts and application that represents a D/HD level of understanding. 

     

    You must demonstrate competence (what is called ‘passed’ in other units) in the assessment tasks associated with a level before you are permitted to move onto a higher level. 

     Details regarding assessments

  • Lab Completion (Essential): Demonstrate all group members complete and understand work. Must complete to pass the course.
  • Fundamentals quizzes (Essential): Quizzes consisting of short questions assessed in tutorials testing essential knowledge from lectures/labs. Must achieve a threshold score to complete the task and pass the course
  • Extensions Quizzes (Extension): Quizzes consisting of short questions assessed in tutorials testing more advanced knowledge from lectures/labs. 
  • Project demonstration (Essential/Extension/Advanced): Demonstrate project meets essential/extension/advanced rubric during a lab session. Mark may be moderated based on individual contribution.
  • Final exam (Advanced only): End of semester exam testing advanced knowledge.
    Exam attendance is not mandatory.
    Regardless of exam performance, all essential assessments must be passed to pass this unit.
    NOTE: The exam will be HARD. Due to the weight of continuous assessments getting up to potentially 70%, this is testing to what extent Distinction/High Distinction students have mastered the advanced subject content

 

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard (mastering advanced), a distinction a very high standard (exploring advanced), a credit a good standard (mastering extension), and a pass an acceptable standard (mastering essentials).

 

For more information see sydney.edu.au/students/guide-to-grades.

For more information see guide to grades.

Use of generative artificial intelligence (AI)

You can use generative AI tools for open assessments. Restrictions on AI use apply to secure, supervised assessments used to confirm if students have met specific learning outcomes.

Refer to the assessment table above to see if AI is allowed, for assessments in this unit and check Canvas for full instructions on assessment tasks and AI use.

If you use AI, you must always acknowledge it. Misusing AI may lead to a breach of the Academic Integrity Policy.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

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 University expects students to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

Our website provides information on academic integrity and the resources available to all students. This includes advice on how to avoid common breaches of academic integrity. Ensure that you have completed the Academic Honesty Education Module (AHEM) which is mandatory for all commencing coursework students

Penalties for serious breaches can significantly impact your studies and your career after graduation. It is important that you speak with your unit coordinator if you need help with completing assessments.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

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.

Support for students

The Support for Students Policy reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

WK Topic Learning activity Learning outcomes
Week 01 Course Organisation, Policies and Strategy Lecture (2 hr) LO1
Week 02 Loops, Polling, Interrupts, Introduction to Binary Lecture (2 hr) LO2 LO1
Exercise 1 in Simulation Practical (3 hr) LO6 LO7 LO4
Week 03 More coding, numbers and encoding Lecture (2 hr) LO2 LO1
Exercise 1 using Physical Equipment Practical (3 hr) LO7 LO4 LO3
Encoding and Binary Number Systems Tutorial (2 hr) LO2 LO1
Week 04 Encoding Lecture (2 hr) LO2 LO1
Exercise 2 in Simulation Practical (3 hr) LO7 LO4
Fixed and Floating Point Tutorial (2 hr) LO2 LO1
Week 05 Floating Point Lecture (2 hr) LO2 LO1
Exercise 2 using Physical Equipment Practical (3 hr) LO7 LO4 LO3
Assembly Basics Tutorial (2 hr) LO2 LO1
Week 06 Introduction to Assembly Lecture (2 hr) LO2 LO1
Exercise 3 in Simulation Practical (3 hr) LO7 LO4
Computer Architecture and Memory Tutorial (2 hr) LO2 LO1
Week 07 Memory Lecture (2 hr) LO2 LO1
Exercise 3 using Physical Equipment Practical (3 hr) LO7 LO4 LO3
Running basic instructions on a Computer Tutorial (2 hr) LO2 LO1
Week 08 Subroutines Lecture (2 hr) LO2 LO1
Project Practical (3 hr) LO6 LO7 LO5 LO3
Running advanced instructions on a Computer Tutorial (2 hr) LO2 LO1
Week 09 Subroutines Lecture (2 hr) LO2 LO1
Project Practical (3 hr) LO6 LO7 LO5 LO3
Subroutines Tutorial (2 hr) LO2 LO1
Week 10 Compilers Lecture (2 hr) LO2 LO1
Project Practical (3 hr) LO6 LO7 LO5 LO3
Using the stack Tutorial (2 hr) LO1
Week 11 Compilers Lecture (2 hr) LO3 LO2 LO1
Project Practical (3 hr) LO6 LO7 LO5 LO3
Compilers and writing more efficient assembly Tutorial (2 hr) LO3 LO2 LO1
Week 12 Open Session. Catch-up Lecture (2 hr) LO3 LO2 LO1
Project Practical (3 hr) LO6 LO7 LO5 LO3
Compilers and writing more efficient assembly Tutorial (2 hr) LO3 LO2 LO1
Week 13 Finish up and revision Lecture (2 hr) LO2 LO1
Project Demo Practical (3 hr) LO6 LO5
Finish up and revision Tutorial (2 hr) LO3 LO2 LO1

Attendance and class requirements

You must participate in the lab (can be done online)

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.

Required readings

Course textbook available through Canvas

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. Demonstrate fundamental knowledge of computer engineering basics.
  • LO2. Demonstrate understanding of the concepts and principles of computer architecture, programming and microprocessor assembly language
  • LO3. Understand the differences between hardware implementation and software simulation by practice
  • LO4. Apply concept, principles and techniques to configure a basic system
  • LO5. Scope, build and test an engineering artefact
  • LO6. Engage in team-based design, drawing on the knowledge, skills and creative talent of all members to deliver a solution to a particular engineering problem
  • LO7. Appreciate the professional practice, standards and responsibilities in working with hardware and software to the limit afforded by lab sessions and exercises

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

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

Additional guidance to be offered for project

Disclaimer

Important: the University of Sydney regularly reviews units of study and reserves the right to change the units of study available annually. To stay up to date on available study options, including unit of study details and availability, refer to the relevant handbook.

To help you understand common terms that we use at the University, we offer an online glossary.