Course coordinator
Dr Russell Manfield
Course overview
- Study period
- Semester 1, 2025 (24/02/2025 - 21/06/2025)
- Study level
- Undergraduate
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Business School
Learn how innovators and entrepreneurs use digital technologies to design, create and offer new products and services, acquire and retain customers, and to grow and potentially scale ventures rapidly. Students will gain an understanding of how digital technologies as enablers allow innovators and entrepreneurs to evaluate and realise novel business ideas, how innovators and entrepreneurs can realise digital technology products that can continuously evolve with customer needs and potentially scale rapidly, and how the increasingly digital business environment creates opportunities for innovators and entrepreneurs to create novel value propositions. Given that digital products and services are becoming the new normal, this course provides students with a critical understanding of how to survive and thrive in today's world. Among other things, students will learn about the unique modular-layered architecture of digital products and services; digital platforms and their potential for network effects; data analytics and their application for growth-hacking; and the use of artificial intelligence to create innovative new products and services.
This course provides students with useful theory, strategy and tools to explore how digital technologies impact innovation developments thatﾠare are deployed to market through forming entrepreneurialﾠopportunities. It also provides students with knowledge and understanding of the game changing role of digital technologies in today’s business environment. Focuses on the role of digital technologies as enablers, products, and environments for innovation and entrepreneurship. Covers aspects such as the changing nature of competitive advantage, growth and scaling of business models, covering the foundations of digital innovation as well as the key challenges in harnessing this domain for stronger employment outcomes.
The course explored instances of emerging innovation across articifical intelligence, blockchain technologies, cybersecurity, internet of things and augmented reality with students mounting debates across each of these topic clusters to challenge hype, deepen understanding and explore entrepreneurial potentials.
Course requirements
Assumed background
Students are assumed to have some knowledge of innovation and entrepreneurship, either through their own experience or completion of TIMS1301 as part of their program of study.
Recommended companion or co-requisite courses
We recommend completing the following courses at the same time:
TIMS1301
Course contact
Course staff
Lecturer
Dr Russell Manfield
Timetable
The timetable for this course is available on the UQ Public Timetable.
Additional timetable information
Please note: Teaching staff do not have access to the timetabling system to help with class allocation. Therefore, should you need help with your timetable and/or allocation of classes, please email business.mytimetable@uq.edu.au from your UQ student email account with the following details:
- Full Name
- Student ID
- Course Code
Aims and outcomes
This course aims to:
- Create a holistic transdisciplinary framework of digital innovation;
- Create a generic model of digital innovation at the firm level;
- Create a generic model of digital innovation and associated empirical tools to study the proliferation of digital innovation at the industry level; and
- Overlay an entrepreneurial orientation in developing and deploying digital innovations.
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Understand the value of digital technologies for innovation and entrepreneurship.
LO2.
Develop a critical understanding of contemporary business environments.
LO3.
Apply research skills to organise and interpret discipline knowledge.
LO4.
Use information literacy and communication skills to professionally structure and present thinking.
LO5.
Function as an effective team member by constructively contributing to teamwork.
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Participation/ Student contribution, Practical/ Demonstration, Presentation |
A1 | inter-team debate
|
30% |
14/03/2025 - 23/05/2025
Teams lead their respective debates according to their chosen topic cluster | AI debate in week 3 | blockchain debate in week 5 | IoT debate in week 7 | AR debate in week 10 | cybersecurity debate in week 12 |
| Essay/ Critique, Participation/ Student contribution |
A2 | Analytical thinking
|
30% Create 1 resource & moderate 3 others, across each of the 5 topic clusters |
AI debate moderations 14/03/2025 Blockchain debate moderations 28/03/2025 IoT debate moderations 11/04/2025 AR debate moderations 9/05/2025 Cybersecurity debate moderations 23/05/2025 |
| Reflection | F1 | Week 4 checkpoint | Formative |
21/03/2025 2:00 pm
Complete the checkpoint form available on Blackboard |
| Reflection | F2 | Week 8 checkpoint | Formative |
14/03/2025 2:00 pm
Complete the checkpoint form available on Blackboard |
| Essay/ Critique | A3 | Investigate a real application | 40% |
30/05/2025 2:00 pm
formative checkpoints contribute to development of the final case chosen by each student |
Assessment details
A1 | inter-team debate
- Team or group-based
- In-person
- Mode
- Activity/ Performance
- Category
- Participation/ Student contribution, Practical/ Demonstration, Presentation
- Weight
- 30%
- Due date
14/03/2025 - 23/05/2025
Teams lead their respective debates according to their chosen topic cluster | AI debate in week 3 | blockchain debate in week 5 | IoT debate in week 7 | AR debate in week 10 | cybersecurity debate in week 12
- Learning outcomes
- L01, L02, L03, L04, L05
Task description
In teams of up to 4 people, students will select one of 5 topic clusters (AI, blockchain, IoT, AR or cybersecurity) to debate the innovation & entrepreneurial opportunities of the respective cluster with other teams, in class. Each topic will be introduced - usually by a guest specialist - in one week with the team debate occurring the following week. Each participating team will collaborate for their topic to devise & deliver a class exercise for others to dive deeper into that topic. Presentations will be assessed against the debate rubric linked in Blackboard.
AI Statement
Artificial Intelligence (AI) and Machine Translation (MT) are emerging tools that may support students in completing this assessment task. Students may appropriately use AI and/or MT in completing this assessment task. Students must clearly reference any use of AI or MT in each instance.
A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
Teams upload any slides & activity resources to Blackboard prior to debate delivery
Deferral or extension
You may be able to defer this exam.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
A2 | Analytical thinking
- Online
- Mode
- Written
- Category
- Essay/ Critique, Participation/ Student contribution
- Weight
- 30% Create 1 resource & moderate 3 others, across each of the 5 topic clusters
- Due date
AI debate moderations 14/03/2025
Blockchain debate moderations 28/03/2025
IoT debate moderations 11/04/2025
AR debate moderations 9/05/2025
Cybersecurity debate moderations 23/05/2025
- Other conditions
- Peer assessed.
- Learning outcomes
- L01, L02, L04
Task description
After each team debate, each student will craft ONE resource in RiPPLE to describe key elements of the debate as they observed and a key learning or application they derived from that discussion. Focus lies in actionable learning to share with the class
Each student will then moderate THREE resources in RiPPLE as created by other students, with a focus on critically analysing the insights of these resources and adding their own observations towards strengthening that resource.
Create 1 topic resource following each cluster debate and moderate 3 other resources to deepen topic understanding.
Rubric for resource creation & moderation available in Blackboard.
AI Statement
Artificial Intelligence (AI) and Machine Translation (MT) are emerging tools that may support students in completing this assessment task. Students may appropriately use AI and/or MT in completing this assessment task. Students must clearly reference any use of AI or MT in each instance.
A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
Use the RiPPLE platform, linked to Blackboard, to create 1 resource and moderate 3 others for each of the 5 topic clusters.
Deferral or extension
You cannot defer or apply for an extension for this assessment.
Late submission
You will receive a mark of 0 if this assessment is submitted late.
The RiPPLE platform enables shared student learning. Late submission means other students do not gain advantage from your resource (if created) nor from your moderation of the resources others have created.
F1 | Week 4 checkpoint
- Mode
- Written
- Category
- Reflection
- Weight
- Formative
- Due date
21/03/2025 2:00 pm
Complete the checkpoint form available on Blackboard
- Learning outcomes
- L03, L04
Task description
Identify a target case study and prepare a brief overview of the potential to illuminate rich digital innovation & entrepreneurship insights
Submission guidelines
Checkpoint upload to Blackboard
Deferral or extension
You cannot defer or apply for an extension for this assessment.
Late submission
No late penalty due to formative nature of this assessment.
F2 | Week 8 checkpoint
- Mode
- Written
- Category
- Reflection
- Weight
- Formative
- Due date
14/03/2025 2:00 pm
Complete the checkpoint form available on Blackboard
- Learning outcomes
- L03, L04
Task description
Complete the week 8 checkpoint reflection of progress in selecting a suitable case study and mapping data collection steps towards the final case study report
Submission guidelines
checkpoint upload to Blackboard
Deferral or extension
You cannot defer or apply for an extension for this assessment.
Late submission
No late penalty due to formative nature of this assessment.
A3 | Investigate a real application
- Mode
- Written
- Category
- Essay/ Critique
- Weight
- 40%
- Due date
30/05/2025 2:00 pm
formative checkpoints contribute to development of the final case chosen by each student
- Learning outcomes
- L01, L02, L03, L04
Task description
The case study allows you to explore & articulate the digital innovations utilised by a live venture and to analyse the entrepreneurial impacts in bringing those innovations to market. You develop your target case through the 2 formative reflection activities (week 4 & week 8 checkpoints) prior to completing this final asssignment.
AI Statement
Artificial Intelligence (AI) and Machine Translation (MT) are emerging tools that may support students in completing this assessment task. Students may appropriately use AI and/or MT in completing this assessment task. Students must clearly reference any use of AI or MT in each instance.
A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
upload case study report to Blackboard
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 7 days. Extensions are given in multiples of 24 hours.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Deduct 10% of the maximum mark per day (or part thereof) up to 5 days, after which NIL marks are awarded
Course grading
Full criteria for each grade is available in the Assessment Procedure.
| Grade | Cut off Percent | Description |
|---|---|---|
| 1 (Low Fail) | 0 - 29 |
Absence of evidence of achievement of course learning outcomes. |
| 2 (Fail) | 30 - 46 |
Minimal evidence of achievement of course learning outcomes. |
| 3 (Marginal Fail) | 47 - 49 |
Demonstrated evidence of developing achievement of course learning outcomes |
| 4 (Pass) | 50 - 64 |
Demonstrated evidence of functional achievement of course learning outcomes. |
| 5 (Credit) | 65 - 74 |
Demonstrated evidence of proficient achievement of course learning outcomes. |
| 6 (Distinction) | 75 - 84 |
Demonstrated evidence of advanced achievement of course learning outcomes. |
| 7 (High Distinction) | 85 - 100 |
Demonstrated evidence of exceptional achievement of course learning outcomes. |
Additional course grading information
Grades will be allocated according to University-wide standards of criterion-based assessment.
Supplementary assessment
Supplementary assessment is available for this course.
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
Find the required and recommended resources for this course 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 |
|---|---|---|
Week 1 |
Seminar |
S1 | Digital Innovation Foundations of digital in novation & entrepreneurship - introducing the arc of the course across Artificial Intelligence, blockchain, internet of things, augmented reality in healthcare & cybersecurity - assessment architecture with a transdisciplinary perspective Learning outcomes: L01, L04 |
Week 2 |
Seminar |
S2 | AI technologies Context for AI developments & opportunities for transformative value Learning outcomes: L01, L04, L05 |
Week 3 |
Team Based Learning |
S3 | AI debate exploring the AI landscape & the real opportunities for creating & harvesting value Learning outcomes: L01, L02, L05 |
Week 4 |
Seminar |
S4 | Blockchain & distributed technologies Decentralised decision algorithms & the role of blockchain approaches not only for cryptocurrencies | Value opportunities Learning outcomes: L01, L02, L03, L05 |
Week 5 |
Team Based Learning |
S5 | Blockchain debate exploring the blockchain landscape & the real opportunities for creating & harvesting value Learning outcomes: L01, L03, L04, L05 |
Week 6 |
Seminar |
S6 | IoT & connected eco-systems the pervasive internet of things (IoT) and opportunities for technical & business model development Learning outcomes: L01, L02, L05 |
Week 7 |
Team Based Learning |
S7 | IoT debate exploring the IoT landscape & the real opportunities for creating & harvesting value Learning outcomes: L01, L02, L04, L05 |
Week 8 |
No student involvement (Breaks, information) |
S8 | public holiday Use this break to complete the week 8 checkpoint as a formative exercise towards your final case study Learning outcomes: L01, L02, L04, L05 |
Mid-sem break |
No student involvement (Breaks, information) |
In-Semester Break review final case study assessment & upcoming book chapters |
Week 9 |
Seminar |
S9 | AR in healthcare the emerging role of augmented reality (AR) in improving medical diagnostics & delivering healthcare solutions Learning outcomes: L01, L02, L05 |
Week 10 |
Team Based Learning |
S10 | AR debate exploring the AR landscape & the real opportunities for creating & harvesting value Learning outcomes: L01, L02, L05 |
Week 11 |
Seminar |
S11 | Cybersecurity & digital resilience Cybersecurity with a particular focus on image forensics Learning outcomes: L01, L02, L05 |
Week 12 |
Team Based Learning |
S12 | Cybersecurity debate exploring the cybersecurity landscape & the real opportunities for creating & harvesting value Learning outcomes: L01, L02, L05 |
Week 13 |
Seminar |
S13 | Wild Innovation Identifying digital opportunities for innovation that deliver new value for socio-technical impact | leverage of final case study Learning outcomes: L01, L02, L05 |
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 - Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.