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Unit of study_

COMP5427: Usability Engineering

Semester 1, 2022 [Normal day] - Remote

Usability engineering is the systematic process of designing and evaluating user interfaces so that they are usable. This means that people can readily learn to use them efficiently, can later remember how to use them and find it pleasant to use them. The wide use of computers in many aspects of people's lives means that usability engineering is of the utmost importance. There is a substantial body of knowledge about how to elicit usability requirements, identify the tasks that a system needs to support, design interfaces and then evaluate them. This makes for systematic ways to go about the creation and evaluation of interfaces to be usable for the target users, where this may include people with special needs. The field is extremely dynamic with the fast emergence of new ways to interact, ranging from conventional WIMP interfaces, to touch and gesture interaction, and involving mobile, portable, embedded and desktop computers. This unit will enable students to learn the fundamental concepts, methods and techniques of usability engineering. Students will practice these in small classroom activities. They will then draw them together to complete a major usability evaluation assignment in which they will design the usability testing process, recruit participants, conduct the evaluation study, analyse these and report the results.

Unit details and rules

Unit code COMP5427
Academic unit Computer Science
Credit points 6
Assumed knowledge

Skills with modelling as covered in ISYS2110 or ISYS2120 or COMP9110 or COMP9201 (or equivalent UoS from different institutions)

Available to study abroad and exchange students


Teaching staff

Coordinator Judy Kay,
Type Description Weight Due Length
Final exam (Open book) Type C final exam Final exam
Students must earn 40% on exam to pass unit.
50% Formal exam period 1.5 hours
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
Small continuous assessment In-class lecture participation activities
Weekly mark /3 and cap at 30.
10% Multiple weeks At various times across classes.
Outcomes assessed: LO1 LO11 LO10 LO9 LO8 LO7 LO6 LO5 LO4 LO3 LO2
Assignment hurdle task Weekly tutorial preparation and participation
Individual work that includes * required for eligibility for group mark
10% Multiple weeks n/a
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
Presentation group assignment Presentation
Group Presentation.
10% Week 06 Details as in specification.
Outcomes assessed: LO3 LO4 LO5 LO7 LO11 LO2 LO9
Assignment group assignment Design and usability evaluation
Group demonstration.
10% Week 11 Details as in specification.
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO8 LO9 LO10 LO11
Assignment group assignment Report
Group Report
10% Week 13 Details in specification
Outcomes assessed: LO3 LO11
hurdle task = hurdle task ?
group assignment = group assignment ?
Type C final exam = Type C final exam ?

Assessment summary

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, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name

Mark range


High distinction

85 - 100



75 - 84



65 - 74



50 - 64



0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard. It is a policy of the School of Computer Science that in order to pass this unit, a student must achieve at least 40% in the final examination. For subjects without a final exam, the 40% minimum requirement applies to the corresponding major assessment component specified by the lecturer. A student must also achieve an overall final mark of 50 or more. Any student not meeting these requirements may be given a maximum final mark of no more than 45 regardless of their average.

For more information see

For more information see guide to grades.

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 Current Student website  provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.  

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

You may only use artificial intelligence and writing assistance tools in assessment tasks if you are permitted to by your unit coordinator, and if you do use them, you must also acknowledge this in your work, either in a footnote or an acknowledgement section.

Studiosity is permitted for postgraduate units unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission.

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.

WK Topic Learning activity Learning outcomes
Week 01 Week 1: Introductions, Pragmatics Lecture and tutorial (2 hr) LO4
Week 02 Week 2: Contextual Enquiry and hierarchical task analysis. Introducing excellent concrete tasks for usability testing Lecture and tutorial (3 hr) LO1
Week 03 Week 3: Empirical studies, think-aloud, ethics Lecture and tutorial (3 hr) LO2 LO3 LO4 LO6
Week 04 Week 4: Reading, heuristic evaluation Lecture and tutorial (3 hr) LO1 LO5
Week 05 Week 5: Assignment 1 review, new terms, Heuristics revisited. Lecture and tutorial (3 hr) LO5
Week 06 Week 6: Assignment 2, Design 1: Personas and Design with Colour Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4 LO9 LO10 LO11
Week 07 Week 7: Prototypes. mental models, understanding people, implications for usability engineering Lecture and tutorial (3 hr) LO1 LO7 LO11
Week 08 Week 8: Need finding by asking and observing users, standard questionnaires Lecture and tutorial (3 hr) LO1 LO7 LO9 LO10
Week 09 Week 9: Reading, Cognitive Walkthrough Lecture and tutorial (3 hr) LO5
Week 10 Week 10: Reading, Cognitive Walkthrough revisited,  Laws Lecture and tutorial (3 hr) LO1 LO7
Week 11 Week 11: Guest lecture, GOMS Lecture and tutorial (3 hr) LO9 LO10
Week 12 Week 12: Guest lecture, Accessibility Lecture and tutorial (3 hr) LO1 LO8 LO9 LO10 LO11
Week 13 Week 13: Statistics for usability engineers, A/B testing, Final review and future directions Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8

Attendance and class requirements

All classes are compulsory

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

All readings for this unit can be accessed through the Library eReserve, available on Canvas.

  • Hartson, Rex, and Pardha S. Pyla., The UX Book: Process and Guidelines for Ensuring a Quality User Experience. ( Elsevier, 2012.

This is the version of the textbook used in Assignment 1.

The more recent version can also be used.

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. Explain the applicability of design techniques learnt for different contexts
  • LO2. Design materials for conducting a user study, including recruitment forms, study protocol, address ethical considerations
  • LO3. Conduct a user study in a professional and ethical manner
  • LO4. Design, perform and analyse results of a think-aloud evaluation
  • LO5. Conduct usability evaluations using key no-user techniques
  • LO6. Describe how to conduct comprehensive summative usability evaluation experiments and how they differ from formative ones
  • LO7. Assess and explain the relative strengths and weaknesses key usability evaluation techniques for a new context
  • LO8. Explain the merits and trade-offs of key usability evaluation techniques for particular context
  • LO9. Report a usability study systematically, assessing the strengths and limitations
  • LO10. Work in a team to conduct usability evaluations
  • LO11. Work in a team to perform parallel iterative prototyping.

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

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

This subject was well received last year. Each year, the materials are updated and refined, in light of the range of sources of information: student surveys and in-class activities, tutor feedback, quality of learning as seen in the assessments and discussions with a team of top students from previous years.

MPORTANT: School policy relating to Academic Dishonesty and Plagiarism. In assessing a piece of submitted work, the School of Computer Science may reproduce it entirely, may provide a copy to another member of faculty, and/or to an external plagiarism checking service or in-house computer program and may also maintain a copy of the assignment for future checking purposes and/or allow an external service to do so.

Computer programming assignments may be checked by specialist code similarity detection software. The Faculty of Engineering currently uses the similarity report available in ED ( This program works in a similar way to TurnItIn in that they check for similarity against a database of previously submitted assignments and code available on the internet, but they have added functionality to detect cases of similarity of holistic code structure in cases such as global search and replace of variable names, reordering of lines, changing of comment lines, and the use of white space.


The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

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