Outline

Overview

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

Academic unit	Computer Science
Credit points	6
Prerequisites ?	None
Corequisites ?	Enrolment in a thesis unit. INFO4001 or INFO4911 or INFO4991 or INFO4992 or AMME4111 or BMET4111 or CHNG4811 or CIVL4022 or ELEC4712 or COMP4103 or SOFT4103 or DATA4103 or ISYS4103
Prohibitions ?	COMP5427
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Judy Kay, judy.kay@sydney.edu.au
Lecturer(s)	Zhanna Sarsenbayeva, zhanna.sarsenbayeva@sydney.edu.au

Type	Description	Weight	Due	Length
Supervised exam ?	Final exam Students must earn 40% on exam to pass unit.	50%	Formal exam period	1.5 hours
Outcomes assessed:
Online task	In-class lecture participation activities Weekly mark /3 and cap at 30.	10%	Multiple weeks	At various times across classes.
Outcomes assessed:
Online task	Weekly tutorial preparation and participation Individual work that includes * required for eligibility for group mark	10%	Multiple weeks	n/a
Outcomes assessed:
Presentation	Presentation. Group Presentation	10%	Week 06 Due date: 26 Mar 2023 at 23:59	Details as in specification.
Outcomes assessed:
Assignment	Design and usability evaluation Group demonstration.	10%	Week 11 Due date: 07 May 2023 at 23:59	Details as in specification.
Outcomes assessed:
Assignment	Report Group Report	10%	Week 13 Due date: 21 May 2023 at 23:59	Details in specification
Outcomes assessed:
= group assignment ?

Assessment summary

The main page of the COMP4/5427 Canvas site has links to all the specifications of the assessment for each of the above.

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	Description
High distinction	85 - 100
Distinction	75 - 84
Credit	65 - 74
Pass	50 - 64
Fail	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 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.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

Tutorial Preparation and Participation (TPP) can only earn a mark if completed ontime since tutors grade it in preparation for the class. In-class assessment activities must be completed in the lecture class unless otherwise specified.

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.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

Learning support

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.

Weekly schedule

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

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. (http://www.theuxbook.net/). Elsevier, 2012.

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

The more recent version can also be used.

Learning outcomes

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.

Outcomes
Graduate qualities

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
Learning outcomes

Responding to student feedback

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

See COMP5427

Additional information

Additional costs

N/A

Site visit guidelines

N/A

Work, health and safety

N/A

Disclaimer

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.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Additional costs

Site visit guidelines

Work, health and safety

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect

Current students

COMP4427: Usability Engineering

Semester 1, 2023 [Normal day] - Remote

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Additional costs

Site visit guidelines

Work, health and safety

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect