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Unit of study_

INFO3315: Human-Computer Interaction

Semester 2, 2022 [Normal day] - Remote

This is a first subject in HCI, Human Computer Interaction. It is designed for students who want to be involved in one of the many roles required to create future technology. There are three main parts: the human foundations from psychology and physiology; HCI methods for design and evaluation of interfaces; leading edge directions for technologies. This subject is highly multi-disciplinary. At the core, it is a mix of Computer Science and Software Engineering combined with the design discipline, UX - User Experience. It draws on psychology, both for relevant theories and user study methods. The practical work is a human-centred group project that motivates the formal curriculum.

Unit details and rules

Unit code INFO3315
Academic unit Computer Science
Credit points 6
6 credit points of 1000-level programming units (INFO1110 or INFO1910 or INFO1113 or ENGG1810) and 12 credit points of 2000-level units from BAdvComp Table A
Assumed knowledge


Available to study abroad and exchange students


Teaching staff

Coordinator Sue Chng,
Lecturer(s) Sue Chng,
Type Description Weight Due Length
Final exam (Open book) Type C final exam hurdle task (Open Book) Essay
Covers theory and a design situation.
45% Formal exam period 2 hours
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO7 LO8
Assignment Reflective Summary 1
Reflective Essay
5% Week 04
Due date: 22 Aug 2022 at 23:59
400 words
Outcomes assessed: LO4 LO7
Assignment Reflective Summary 2
Reflective Essay
5% Week 07
Due date: 12 Sep 2022 at 23:59
400 words
Outcomes assessed: LO1 LO2
Assignment group assignment Project Part 1
Requirements report.
10% Week 08
Due date: 19 Sep 2022 at 23:59
Report:4000 words.
Outcomes assessed: LO1 LO8 LO5 LO2
Assignment Reflective Summary 3
Reflective essay
5% Week 11
Due date: 17 Oct 2022 at 23:59
500 words
Outcomes assessed: LO5
Assignment group assignment Project Part 2
Final Report and Demonstration. Journey Video.
20% Week 12
Due date: 24 Oct 2022 at 23:59
Report: 4000 words. Video: 5 mins.
Outcomes assessed: LO2 LO8 LO6 LO3
Tutorial quiz Weekly Quizzes
Canvas quizzes must be completed before Week 13.
10% Week 13
Closing date: 06 Nov 2022
10-20 minutes.
Outcomes assessed: LO1 LO7 LO5 LO4 LO3
Assignment hurdle task group assignment Meeting Minutes
Weekly submission by midnight of Workshop day starting from Week 5.
0% Weekly max 1000 words
Outcomes assessed: LO8
hurdle task = hurdle task ?
group assignment = group assignment ?
Type C final exam = Type C final exam ?

Assessment summary

  • Weekly Quizzes. These are online quizzes to test understanding of content from each week. Questions are MCQs and can be attempted multiple times before the last day on Week 13 (6th November 2022, 11.59pm). It is recommended to complete them on the week of release to keep up with the contents.
  • Reflective summary: A diagram summarizing theoretical concepts and techniques. A concise description explaining how you use these in your own practice. Description must be supported by evidence of work. 
  • Group Project: Students work in groups; 4 to 5 students per group, to design the interface for a solution. Each student will be required to review their own performance and that of each team members. Individual marks for group assessments will be  determined using these reviews and Meeting Minutes. 
  • Meeting Minutes: Records of the group’s weekly discussion. It should include work presented by each member during the meeting. Performance ratings (individual and peer) stated in reviews must be supported by records during the meeting. Each student must contribute and participate in the group project in order to pass the unit. 
  • Final exam: The final exam will assess all contents covered in the semester. Students must score at least 40% in the final exam to pass the unit (see Pass requirements).

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.

For more information see

For detailed description of grading criteria used for submitted work (Reflective Summary and Project), refer to rubrics on Canvas.

Where possible in-class quizes will be automatically graded (e.g. MCQs). 

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 written 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:

Standard late penalties apply for assessments with a deadline.

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 1. Introduction to HCI; 2. Importance of Interface Design; 3. Design Goals and Rules. Lecture and tutorial (2 hr) LO4
1. Review of learning resources for Week 1; 2. Preparation for contact sessions; Independent study (6 hr) LO4
Week 02 1. Human Perception and Cognition; 2. Cognitive Frameworks; 3. Emotion and Motivation. Lecture and tutorial (2 hr) LO4
1. Perceiving structure; 2. Designing motivation. Workshop (2 hr) LO4
1. Review of learning resources for Week 2; 2. Preparation for contact sessions; Independent study (6 hr) LO4
Week 03 1. Individual Differences; 2. Interaction Design in Practice; 3. Group Project. Lecture and tutorial (2 hr) LO8
1. Requirements, expectations and reality; 2. My way of designing. Workshop (2 hr) LO8
1. Review of learning resources for Week 3; 2. Preparation for contact sessions; 3. Preparation of reflective summary #1 submission Independent study (6 hr) LO4 LO7 LO8
Week 04 1. Establishing user groups and their requirements; 2. Data gathering techniques. Lecture and tutorial (2 hr) LO1
1. Analyze a problem; 2. Identify suitable data gathering techniques. Workshop (2 hr) LO1
1. Review of learning resources for Week 4; 2. Preparation for contact sessions; 3. Work on Project. Independent study (8 hr) LO1
Week 05 1. Data analysis, interpretation and presentation; 2. Bringing requirements to life. Lecture and tutorial (2 hr) LO1 LO8
1. Basic quantitative and qualitative data analysis; 2. Persona, scenarios and use-cases. Workshop (2 hr) LO1 LO2 LO8
1. Review of learning resources for Week 5; 2. Preparation for contact sessions; 3. Work on Project Independent study (8 hr) LO1 LO2 LO8
Week 06 1. Conceptual Design; 2. Low-fidelity Prototypes; 3. Video Prototype. Lecture and tutorial (2 hr) LO2 LO6 LO8
1. Q&A for project 2. Work time for project Workshop (2 hr) LO2 LO5 LO6 LO8
1. Review of learning resources for Week 6; 2. Preparation for contact sessions; 3. Work on Project 4. Prepare Reflective Summary #2 submission Independent study (8 hr) LO2 LO5 LO6 LO8
Week 07 1. Hi-fidelity prototyping; 2. Physical prototypes. Lecture and tutorial (2 hr) LO2 LO5 LO8
1. Figma basics 2. Q&A for project Workshop (2 hr) LO5 LO6 LO8
1. Review of learning resources for Week 7 ; 2. Preparation for contact sessions ; 3. Work on Project Independent study (8 hr) LO5 LO6 LO8
Week 08 1. Evaluation basics; 2. Planning evaluation. Lecture and tutorial (2 hr) LO3 LO5 LO8
1. Usability Test; 2. Prototype presentation. Workshop (2 hr) LO3 LO5 LO8
1. Review of learning resources for Week 8; 2. Preparation for Zoom sessions; 3. Work on Project. Independent study (8 hr) LO3 LO5 LO8
Week 09 1. Project Q&A; 2. Prototype presentation. Workshop (2 hr) LO5 LO6 LO8
1. Work on Project. 2. Prepare Reflective Summary 3 submission Independent study (8 hr) LO3 LO5 LO6 LO8
Week 10 Experiment designs Lecture and tutorial (2 hr) LO3 LO5 LO8
1. Project prototyping; 2. Project study design. Workshop (2 hr) LO3 LO5 LO6 LO8
1. Review of learning resources for Week 10. 2. Preparation for contact sessions. 3. Work on Project. Independent study (8 hr) LO3 LO5 LO6 LO8
Week 11 Revision - Design Journey Lecture and tutorial (2 hr) LO8
Project Work and Demonstration. Workshop (2 hr) LO8
1. Preparation for contact sessions. 2. Preparation for project submission Independent study (6 hr) LO3 LO6 LO8
Week 12 1. Social interfaces; 2. Computer supported collaborative work (CSCW); 3. Emotional and affective interfaces. Lecture and tutorial (2 hr) LO7
1. Research in CSCW and Ubicomp. 2. AR/VR trend Workshop (2 hr) LO7
1. Review of learning resources for Week 12. 2. Preparation for contact sessions. Independent study (6 hr) LO7
Week 13 1. Syllabus summary. 2. Revision - final exam. Lecture and tutorial (2 hr) LO1 LO2 LO3 LO5 LO7
Revision Q&A Workshop (2 hr) LO1 LO2 LO3 LO4 LO7
Preparation for final exam. Independent study (6 hr) LO3 LO4 LO7

Attendance and class requirements

Each week, students must:

  • Do own independent study by reviewing provided materials, read the required sections of literature, researching and completing assesment tasks.
  • Be prepared (completed task/research/background reading) for all online face-to-face sessions inclusive of group meetings for Project.
  • Attend and participate in all online face-to-face sessions (as timetabled).

Workshop and Q&A sessions will NOT be recorded. 

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.

  • Interaction Design: Beyond Human-Computer Interaction, 5th Edition by Sharp, Preece, and Rogers.
  • The UX Book: Process and Guidelines for Ensuring a Quality User Experience. by Hartson, and Pyla.

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. Select suitable techniques for establishing user groups and their requirements for an interface, including the usability requirements, and be able to make use of these techniques
  • LO2. Apply standard design approaches to creating a user interface
  • LO3. Evaluate interfaces, based upon both discount and user-based techniques, and be able to select the most appropriate technique for a particular situation and to justify this
  • LO4. Explain how human factors influence aspects of design of interfaces
  • LO5. Demonstrate knowledge of the main methods of interface design and evaluation and the relative strengths and weaknesses of each and their most appropriate uses
  • LO6. Use a prototyping tool to create low fidelity prototypes
  • LO7. Demonstrate knowledge of the broad range of interfaces, such as social, NUI, emotion-aware interfaces, ubiquitous devices that are carried, work or embedded in the environment
  • LO8. Present the design and evaluation of a prototype interface, defining the requirements, describing the design processes and evaluation and use the evidence gathered in established methods to draw conclusions about it's strengths, and weaknesses of the interface.

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.

Changes to assessment structure, particularly deadlines have been changed to avoid multiple concurrent deadlines.

IMPORTANT: 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.

All written assignments submitted in this unit of study will be submitted to the similarity detecting software program known as Turnitin. Turnitin searches for matches between text in your written assessment task and text sourced from the Internet, published works and assignments that have previously been submitted to Turnitin for analysis.

There will always be some degree of text-matching when using Turnitin. Text-matching may occur in use of direct quotations, technical terms and phrases, or the listing of bibliographic material. This does not mean you will automatically be accused of academic dishonesty or plagiarism, although Turnitin reports may be used as evidence in academic dishonesty and plagiarism decision-making processes.



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.