Course coordinator
Professor Tim Miller
Course overview
- Study period
- Semester 1, 2026 (23/02/2026 - 20/06/2026)
- Study level
- Undergraduate
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Elec Engineering & Comp Science School
Introduction to innovation using computer science and information technology through a discipline-specific team project. Students will learn what innovation is, processes that innovators follow, how innovation teams work together, how to make decisions in technology projects, how to use prototyping in the innovation process and the tools required to successfully deliver and communicate an innovation project.
This is the third offering of the course. There are no specific changes to this course compared to the course description or previous offerings of this course.
Course requirements
Prerequisites
You'll need to complete the following courses before enrolling in this one:
CSSE1001 or DECO1400
Incompatible
You can't enrol in this course if you've already completed the following:
COMP7110
Course contact
Course staff
Lecturer
Professor Tim Miller
Mr Ian Clough
Timetable
The timetable for this course is available on the UQ Public Timetable.
Aims and outcomes
This course aims to introduce the fundamentals of innovation in computer science and information technology through a discipline-specific team project. Students will learn what innovation is, processes that innovators follow, how innovation teams work together, how to make decisions in technology projects, how to use prototyping in the innovation process and the tools required to successfully deliver and communicate an innovation project. This course provides the foundations to further courses in computer science and information technology programs.
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Work independently as part of a team with diverse backgrounds towards authentic IT innovation solutions
LO2.
Apply innovation processes to open ended problems
LO3.
Collect and analyse data about people and problems
LO4.
Design and prototype innovation solutions to identified open ended problems
LO5.
Communicate problems and solutions to technical and non-technical stakeholders
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Participation/ Student contribution, Practical/ Demonstration, Presentation, Role play/ Simulation |
Studio participation
|
Pass/fail |
Week 3 - Week 5 Week 6 - Week 13 |
| Paper/ Report/ Annotation, Product/ Design, Reflection |
Business model canvas iteration 1
|
Pass/fail |
2/04/2026 4:00 pm |
| Paper/ Report/ Annotation, Product/ Design, Reflection |
Business model canvas iteration 2
|
Pass/fail |
30/04/2026 4:00 pm |
| Computer Code, Paper/ Report/ Annotation, Practical/ Demonstration, Presentation, Product/ Design, Reflection |
Code submission and business model canvas iteration 3
|
Pass/fail |
11/06/2026 4:00 pm |
A hurdle is an assessment requirement that must be satisfied in order to receive a specific grade for the course. Check the assessment details for more information about hurdle requirements.
Assessment details
Studio participation
- Hurdle
- Identity Verified
- Team or group-based
- In-person
- Mode
- Activity/ Performance, Oral, Product/ Artefact/ Multimedia
- Category
- Participation/ Student contribution, Practical/ Demonstration, Presentation, Role play/ Simulation
- Weight
- Pass/fail
- Due date
Week 3 - Week 5
Week 6 - Week 13
- Other conditions
- Secure.
- Learning outcomes
- L01, L02, L05
Task description
Participation in the weekly seminar and studios, including presentation and practice sessions.
This task has been designed to be challenging, authentic and complex. Whilst students may use AI and/or MT technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance.
A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
To pass this assessment, students will be required to demonstrate detailed comprehension of their submission independent of AI and MT tools.
Hurdle requirements
To pass the hurdle, students must attend and participate in the studio for each of the weeks listed above.Submission guidelines
Deferral or extension
You cannot defer or apply for an extension for this assessment.
You cannot defer or apply for extensions for studio participation. Participation must be during scheduled studio timeslots to be assessed by course staff.
If you are unable to attend, you must inform your team and your supervisor before the studio that you will be unable to attend, and provide relevant evidence to your supervisor. The course coordinator will work with you and your supervisor to determine alternative assessment to demonstrate learning outcomes.
Late submission
You will receive a mark of 0 if this assessment is submitted late.
Business model canvas iteration 1
- Hurdle
- Identity Verified
- Team or group-based
- Mode
- Written
- Category
- Paper/ Report/ Annotation, Product/ Design, Reflection
- Weight
- Pass/fail
- Due date
2/04/2026 4:00 pm
- Other conditions
- Secure.
- Learning outcomes
- L01, L02, L03
Task description
A team report outlining the customer discovery findings from the first iteration of the process.
A short individual reflection from each student.
This task has been designed to be challenging, authentic and complex. Whilst students may use AI and/or MT technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance.
A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
To pass this assessment, students will be required to demonstrate detailed comprehension of their submission independent of AI and MT tools.
Students will have one-on-one meetings with their supervisor to discuss their work throughout the semester.
Hurdle requirements
This submission has both a team component, as well as a short individual self reflection. Students must achieve a Pass on both items to be eligible to Pass the course. Individual student contribution to the team component is determined by the logs in the source code repository.Submission guidelines
In order for the work to be eligible for grading, it must be pushed to a branch on the team repository AND submitted as a .zip file to Blackboard
Deferral or extension
You cannot defer or apply for an extension for this assessment.
If a team encounters difficulties in meeting a deadline, they should contact the Course Coordinator in advance of the due date. Teams will be asked to meet with the Course Coordinator and be prepared to submit what work they have completed by the deadline. The Course Coordinator will work with individuals who are unable to complete their part, so that they can determine how that individual can demonstrate competence in other submissions.
Late submission
100% Late Penalty after 1 hour grace period. The one-hour grace period is recorded from the time the submission is due.
Business model canvas iteration 2
- Hurdle
- Identity Verified
- Team or group-based
- Mode
- Written
- Category
- Paper/ Report/ Annotation, Product/ Design, Reflection
- Weight
- Pass/fail
- Due date
30/04/2026 4:00 pm
- Other conditions
- Student specific, Secure.
- Learning outcomes
- L01, L02, L03, L04, L05
Task description
A team report outlining the customer discovery findings from the second iteration of the process.
A short individual reflection from each student.
Students will have one-on-one meetings with their supervisor to discuss their work throughout the semester.
This task has been designed to be challenging, authentic and complex. Whilst students may use AI and/or MT technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance.
A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
To pass this assessment, students will be required to demonstrate detailed comprehension of their submission independent of AI and MT tools.
Hurdle requirements
This submission has both a team component, as well as a short individual self reflection. Students must achieve a Pass on both items to be eligible to Pass the course. Individual student contribution to the team component is determined by the logs in the source code repository.Submission guidelines
In order for the work to be eligible for grading, it must be pushed to a branch on the team repository AND submitted as a .zip file to Blackboard
Deferral or extension
You cannot defer or apply for an extension for this assessment.
If a team encounters difficulties in meeting a deadline, they should contact the Course Coordinator in advance of the due date. Teams will be asked to meet with the Course Coordinator and be prepared to submit what work they have completed by the deadline. The Course Coordinator will work with individuals who are unable to complete their part, so that they can determine how that individual can demonstrate competence in other submissions.
Late submission
100% Late Penalty after 1 hour grace period. The one-hour grace period is recorded from the time the submission is due.
Code submission and business model canvas iteration 3
- Hurdle
- Identity Verified
- Team or group-based
- Mode
- Oral, Product/ Artefact/ Multimedia, Written
- Category
- Computer Code, Paper/ Report/ Annotation, Practical/ Demonstration, Presentation, Product/ Design, Reflection
- Weight
- Pass/fail
- Due date
11/06/2026 4:00 pm
- Learning outcomes
- L01, L02, L03, L04, L05
Task description
A team report outlining the customer discovery findings from the third iteration of the process.
An implemented conceptual prototype.
A short individual reflection from each student.
Students will have one-on-one meetings with their supervisor to discuss their work throughout the semester.
This task has been designed to be challenging, authentic and complex. Whilst students may use AI and/or MT technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance.
A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
To pass this assessment, students will be required to demonstrate detailed comprehension of their submission independent of AI and MT tools.
Hurdle requirements
This submission has both a team component, as well as a short individual self reflection. Students must achieve a Pass on both items to be eligible to Pass the course. Individual student contribution to the team component is determined by the logs in the source code repository.Submission guidelines
In order for the work to be eligible for grading, it must be pushed to a branch on the team repository AND submitted as a .zip file to Blackboard
Deferral or extension
You cannot defer or apply for an extension for this assessment.
If a team encounters difficulties in meeting a deadline, they should contact the Course Coordinator in advance of the due date. Teams will be asked to meet with the Course Coordinator and be prepared to submit what work they have completed by the deadline. The Course Coordinator will work with individuals who are unable to complete their part, so that they can determine how that individual can demonstrate competence in other submissions.
Late submission
100% Late Penalty after 1 hour grace period. The one-hour grace period is recorded from the time the submission is due.
Course grading
Full criteria for each grade is available in the Assessment Procedure.
| Pass/Fails | Description |
|---|---|
| Pass |
Course grade description: Pass all four hurdles |
| Fail |
Course grade description: Fail one or more hurdles. |
Additional course grading information
Grade calculation
For each submission (iteration 1, 2, 3), each student will receive one of the following grades for iteration:
- Pass (P): The student has met expectations in all of the competency criteria.
- Conceded (C): The student has not met expectations in all of the competency criteria, and if they continue at the current standard, they will fail a future iteration. However, they have met enough expectations to continue with the course. The competency of ‘Software implementation’ (coding the MVP) is only assessed in iteration 3.
- Fail (F): The student has failed this iteration, and therefore the course.
Grades are assigned based on the individual student's contribution to the project, not a team grade. Contribution is determined by the work the individual has committed to the team repository, and the work they present and discuss with their supervisor. At the discretion of the course coordinator, final grades may be moderated.
Students will receive consistent feedback from week 4 on their performance.
To pass the course, each student must:
- Pass the participation hurdle for the studios.
- Pass iteration 3.
- Received a Pass or Conceded on iterations 1-2.
Identity verified assessment
The studio teaching staff actively monitor individual participation throughout the semester during weekly studios, through fortnightly one-one meetings with students, and via scheduled participation activities both in person and through monitoring of various collaboration platforms. Based on this monitoring, teaching staff are aware of the degree to which students are actively participating and contributing to the team projects. If students have not actively participated throughout, further evidence may be requested to assess the level of active participation. Students who are unable to demonstrate their active participation and contribution to the team’s output risk failing this course with an overall grade capped at 2 by not meeting this requirement.
Supplementary assessment
Supplementary assessment is not available for this course.
Additional assessment information
Having troubles?
If you are having difficulties with any aspect of the course material, you should seek help and speak to the course teaching staff. In the first instance, approach your team legend (supervisor), who will raise it with course coordinators if required. If this does not resolve the issue, raise it with the course coordinators.
If external circumstances are affecting your ability to work on the course, you should seek help as soon as possible. The University and UQ Union have organisations and staff who are able to help; for example, UQ Student Services are able to help with study and exam skills, tertiary learning skills, writing skills, financial assistance, personal issues, and disability services (among other things).
Complaints and criticisms should be directed in the first instance to the course coordinator. If you are not satisfied with the outcome, you may bring the matter to the attention of the School of EECS Director of Teaching and Learning.
Learning resources
You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.
Library resources
Library resources are available on the UQ Library website.
Learning activities
The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.
Filter activity type by
Please select
| Learning period | Activity type | Topic |
|---|---|---|
Multiple weeks From Week 1 To Week 13 |
Studio |
Studio Weekly 2-3-hour studio. Learning outcomes: L01, L02, L03, L04, L05 |
Additional learning activity information
Weekly 3-4-hour studio.
This will be a combination of presentations from course staff, discussions, and teams working on their project.
Policies and procedures
University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:
- Student Code of Conduct Policy
- Student Integrity and Misconduct Policy and Procedure
- Assessment Procedure
- Examinations Procedure
- Reasonable Adjustments for Students Policy and Procedure
- AI for Assessment Guide
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.
School guidelines
Your school has additional guidelines you'll need to follow for this course: