Note: This unit is an archived version! See Overview tab for delivered versions.

COMP5047: Pervasive Computing (2011 - Semester 2)

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Unit: COMP5047: Pervasive Computing (6 CP)
Mode: Normal-Day
On Offer: Yes
Level: Postgraduate
Faculty/School: School of Computer Science
Unit Coordinator/s: Professor Kay, Judy
Session options: Semester 2
Versions for this Unit:
Site(s) for this Unit: http://sydney.edu.au/engineering/it/~comp5047/
Campus: Camperdown/Darlington
Pre-Requisites: None.
Brief Handbook Description: This is an advanced course in HCI, Human Computer Interaction, with a focus on Pervasive Computing. It introduces the key aspects of HCI and explores these in terms of the new research towards creating user interfaces that disappear into the environment and are available pervasively, for example in homes, workplaces, cars and carried or work.
Assumed Knowledge: Background in programming and operating systems that is sufficient for the student to independently learn new programming tools from standard online technical materials. Ability to conduct a literature search. Ability to write reports of work done.
Lecturer/s: Professor Kay, Judy
Timetable: COMP5047 Timetable
Time Commitment:
# Activity Name Hours per Week Sessions per Week Weeks per Semester
1 Lecture 2.00 1 13
2 Laboratory 2.00 1 13
T&L Activities: Laboratory: The weekly laboratory class will enable students to consolidate the key ideas for the week. Depending upon the topic, this laboratory session will involve small experimental activities, discussions or technical work.

Attributes listed here represent the key course goals (see Course Map tab) designated for this unit. The list below describes how these attributes are developed through practice in the unit. See Learning Outcomes and Assessment tabs for details of how these attributes are assessed.

Attribute Development Method Attribute Developed
The essence of the course is to learn how to design pervasive computing systems, where this includes learning the relevant theory, its application, the techniques and their use. Design and Problem Solving Skills (Level 5)
The lectures and all practical and project work will build discipline specific expertise in the area of building pervasive computing systems. Discipline Specific Expertise (Level 5)
The assessment of the group project is based on a poster, a report and a demonstration. These will develop written and spoken communication skills. The practical class activities and the final examination will include short answers questions that will require good written communication skills. Professional Communication (Level 4)
The major project involves working in a team. Teamwork and Project Management (Level 4)

For explanation of attributes and levels see Engineering/IT Graduate Attribute Matrix 2009.

Learning outcomes are the key abilities and knowledge that will be assessed in this unit. They are listed according to the course goal supported by each. See Assessment Tab for details how each outcome is assessed.

Design and Problem Solving Skills (Level 5)
1. Ability to analyse a context to define the overall goals of a new pervasive system
2. Ability to select suitable techniques for establishing requirements for a pervasive computing system, including the usability requirements. Ability to make use of these techniques.
3. Ability to apply standard design approaches to creating a user interface, and to adapt these to the particular emerging demands of pervasive computing systems.
4. Ability to evaluate interfaces, based upon both discount and user-based techniques. Ability to select the most appropriate technique for a particular situation and to justify this.
5. Ability to explain how human factors influence aspects of design of interfaces.
6. Ability to bring together design and evaluation techniques to create a prototype interface that is designed to address a defined user need.
Professional Communication (Level 4)
7. Write a report on the prototype system created.
Assessment Methods:
# Name Group Weight Due Week Outcomes
1 Workshop Skills No 0.00 Multiple Weeks 1, 2, 3, 4, 5, 6, 7,
2 Project Yes 25.00 Multiple Weeks 1, 2, 3, 4, 5, 6, 7,
3 Project No 35.00 Multiple Weeks 1, 2, 3, 4, 5, 6, 7,
4 Final Exam No 40.00 Exam Period 1, 2, 3, 4, 5, 6, 7,
Assessment Description: Workshop Skills: Lab mark. This is primarily a formative mark, with grades and feedback intended to inform the student about the quality of their work and area for improvement. There will be graded tasks during labs.

Project: Project to create a prototype pervasive computing system, evaluate it and report on the approaches used for the design and evaluation.

Final Exam: Final examination. This assessed the full content of the lectures, labs and project work. The exam mark, expressed as a percentage + 10% is a cap on the final grade. (So, for example, a pass on the unit requires an exam mark of at least 40%; a final mark of 60 requires an exam mark of at least 50%).
Assessment Feedback: Weekly reports on readings, seminar and studio activities are graded on a scale A, B, C, D. This is purely as formative feedback and is otherwise judged as a pass/fail part of the participation mark. To pass the unit, students must earn 80% on this participation mark.
Grading:
Grade Type Description
Standards Based Assessment Final grades in this unit are awarded at levels of HD for High Distinction, DI (previously D) for Distinction, CR for Credit, PS (previously P) for Pass and FA (previously F) for Fail as defined by University of Sydney Assessment Policy. Details of the Assessment Policy are available on the Policies website at http://sydney.edu.au/policies . Standards for grades in individual assessment tasks and the summative method for obtaining a final mark in the unit will be set out in a marking guide supplied by the unit coordinator.
Special Conditions to Pass UoS The exam mark, expressed as a percentage + 10% is a cap on the final grade. (So, for example, a pass on the unit requires an exam mark of at least 40%; a final mark of 60 requires an exam mark of at least 50%).
Policies & Procedures: IMPORTANT: School policy relating to Academic Dishonesty and Plagiarism.

In assessing a piece of submitted work, the School of IT 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.

Other policies

Faculty policies regarding academic honesty and plagiarism, special consideration and appeals in Engineering and Information Technologies can be found on the Faculty's policy page at http://www.eng.usyd.edu.au/policies"> http://www.eng.usyd.edu.au/policies. School and Faculty policies are governed by Academic Board resolutions whose details can be found on the Central Policy Online site at http://www.usyd.edu.au/policy/"> http://www.usyd.edu.au/policy/.

Policies regarding assessment formatting, submission methods, late submission penalties and assessment feedback depend on the unit of study. Details of these policies, where applicable, should be found above with other assessment details.
Online Course Content: http://sydney.edu.au/engineering/it/~comp5047/
Note on Resources: There will be additional online readings linked from the unit website.

Note that the "Weeks" referred to in this Schedule are those of the official university semester calendar https://web.timetable.usyd.edu.au/calendar.jsp

Week Description
Week 1 Introduction to HCI and Pervasive Computing, Overview of course, Overview of main project
Week 2 User Centred Design - Eliciting user requirements
Week 3 Design
Week 4 Appliance computing and Ambient displays
Week 5 Technical - Android
Week 6 Technical - Android
Week 7 Mobile web
Week 8 Testing
Week 9 Testing
Week 10 Cognitive and physiological design drivers
Week 11 Tabletop and embedded shared devices
Week 12 Sensors and related technology, sample exam tasks
Week 13 Future Pervasive Systems, discussion of exam
Exam Period Assessment Due: Final Exam

Course Relations

The following is a list of courses which have added this Unit to their structure.

Course Year(s) Offered
Master of Professional Engineering (Accelerated) (Software) 2019, 2020, 2021, 2022, 2023, 2024
Master of Professional Engineering (Software) 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024
Advanced Computing / Science 2018, 2019, 2020, 2021, 2022
Advanced Computing / Science (Medical Science) 2018, 2019, 2020, 2021, 2022
Bachelor of Advanced Computing (Computational Data Science) 2018, 2019, 2020
Advanced Computing / Commerce 2018, 2019, 2020, 2021, 2022
Bachelor of Advanced Computing (Computer Science) 2018, 2019, 2020
Bachelor of Advanced Computing (Information Systems) (not offered from 2022+) 2018, 2019, 2020, 2021
Bachelor of Advanced Computing (Software Development) 2018, 2019, 2020
Bachelor of Computer Science and Technology (Honours) 2015, 2016, 2017, 2025
Software Engineering (mid-year) 2016, 2017, 2018, 2019, 2020, 2021, 2022
Software / Project Management 2019+ 2019
Software Engineering 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022
Software / Arts (2022 and earlier) 2016, 2017, 2018, 2019
Software / Commerce 2016, 2017, 2018, 2019
Software / Project Management 2016, 2017, 2018
Software / Science 2016, 2017, 2018, 2019
Software / Science (Health) 2018, 2019
Software / Law 2016, 2017, 2018, 2019
Software Engineering / Arts 2011, 2012, 2013, 2014
Software Engineering / Commerce 2010, 2011, 2012, 2013, 2014
Software Engineering / Medical Science 2011, 2012, 2013, 2014
Software Engineering / Science 2011, 2012, 2013, 2014
Graduate Diploma in Computing 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023
Graduate Diploma in Computer Science 2024, 2025
Graduate Diploma in Cybersecurity 2023, 2024, 2025
Graduate Diploma in Data Science 2023, 2024, 2025
Graduate Diploma in Information Technology 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023
Master of Computer Science (advanced entry) (Capstone Pathway) 2024, 2025
Master of Computer Science (advanced entry) (Research Pathway) 2024, 2025
Master of Computer Science (advanced entry) (Work Integrated Pathway) 2024, 2025
Master of Computer Science (Capstone Pathway) 2024, 2025
Master of Computer Science (Research Pathway) 2024, 2025
Master of Computer Science (Work Integrated Pathway) 2024, 2025
Master of Cybersecurity 2023, 2024, 2025
Master of Data Science 2023, 2024, 2025
Master of Engineering (Electrical Engineering) 2025+ 2025
Master of Engineering (2024 and earlier) 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024
Master of Engineering (Software Engineering) 2025+ 2025
Master of Information Technology 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023
Master of Information Technology Management 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023
Master of IT / Master of IT Management 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023
Master of Professional Engineering (Accelerated) (Electrical) 2019, 2020, 2021, 2022, 2023, 2024
Master of Professional Engineering (Accelerated) (Electrical) 2025+ 2025
Master of Professional Engineering (Accelerated) (Software) 2025+ 2025
Master of Professional Engineering (Electrical) 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024
Master of Professional Engineering (Electrical) 2025+ 2025
Master of Professional Engineering (Software) 2025+ 2025
Software / Science (Medical Science Stream) 2018, 2019

Course Goals

This unit contributes to the achievement of the following course goals:

Attribute Practiced Assessed
Design and Problem Solving Skills (Level 5) Yes 83.73%
Discipline Specific Expertise (Level 5) Yes 0%
Professional Communication (Level 4) Yes 16.29%
Teamwork and Project Management (Level 4) Yes 0%

These goals are selected from Engineering/IT Graduate Attribute Matrix 2009 which defines overall goals for courses where this unit is primarily offered. See Engineering/IT Graduate Attribute Matrix 2009 for details of the attributes and levels to be developed in the course as a whole. Percentage figures alongside each course goal provide a rough indication of their relative weighting in assessment for this unit. Note that not all goals are necessarily part of assessment. Some may be more about practice activity. See Learning outcomes for details of what is assessed in relation to each goal and Assessment for details of how the outcome is assessed. See Attributes for details of practice provided for each goal.