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CP2405 - Collective Intelligence and Entrepreneurship
| Credit points: | 3 |
| Year: | 2020 |
| Student Contribution Band: | Band 2 |
| Administered by: | College of Science and Engineering |
In this subject students analyse the social and business impact and applications collective intelligence has in a rapidly changing digital world. Students will explore the start-up lifecycle and related Web2.0/3.0 technologies with particular focus on entrepreneurship, e-marketing and human resource management. Technologies and new business models such as crowd sourcing, harnessing the crowd, linked data, etc., will be examined to evaluate how creative problem solvers can take advantage of a global collective intelligence through enhanced information sharing and online collaboration. Students gain skills and experience using emerging crowd platforms to pitch ideas, increase profit, manage well-being, enable business processes and functions and explore new business models
Learning Outcomes
- examine collective intelligence and social network technologies and applications;
- analyse business opportunities and challenges of collective intelligence and entrepreneurship;
- examine legal, ethical and social issues related to collective intelligence;
- develop and align appropriate collective intelligence technologies with entrepreneurship activities.
Subject Assessment
- Practicals - (30%)
- Assignment 1 - (25%)
- Assignment 2 - (30%)
- Presentation - (15%).
| Prerequisites: | MINIMUM OF 24 CREDIT POINTS |
| Inadmissible Subject Combinations: |
CP5635 |
Availabilities |
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| Townsville, Internal, Study Period 2 | |
| Census Date 27-Aug-2020 | |
| Coordinator: | Mr Randy Zhu |
| Lecturers: | Ms Melinda Kingsun, Assoc. Professor Trina Myers, Mr Randy Zhu. |
| Workload expectations: |
The student workload for this 3 credit point subject is approximately 130 hours.
|
| External, Study Period 2 | |
| Census Date 27-Aug-2020 | |
| Coordinator: | Mr Randy Zhu |
| Lecturers: | Ms Melinda Kingsun, Assoc. Professor Trina Myers. |
| Workload expectations: |
The student workload for this 3 credit point subject is approximately 130 hours.
|
| Method of Delivery: | WWW - LearnJCU |
| Cairns, Internal, Study Period 2 | |
| Census Date 27-Aug-2020 | |
| Coordinator: | Mr Randy Zhu |
| Lecturers: | Assoc. Professor Trina Myers, Dr Joanne Lee. |
| Workload expectations: |
The student workload for this 3 credit point subject is approximately 130 hours.
|
| JCU Singapore, Internal, Study Period 51 | |
| Census Date 09-Apr-2020 | |
| Lecturer: | Mr Michael Hansen. |
| Workload expectations: |
The student workload for this 3 credit point subject is approximately 130 hours.
|
| JCU Brisbane, Internal, Study Period 21 | |
| Census Date 09-Apr-2020 | |
| Lecturer: | Mrs Laura Antochi. |
| Workload expectations: |
The student workload for this 3 credit point subject is approximately 130 hours.
|
| JCU Brisbane, Internal, Study Period 22 | |
| Census Date 06-Aug-2020 | |
| Workload expectations: |
The student workload for this 3 credit point subject is approximately 130 hours.
|
| JCU Brisbane, Internal, Study Period 23 | |
| Census Date 03-Dec-2020 | |
| Workload expectations: |
The student workload for this 3 credit point subject is approximately 130 hours.
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Note: Minor variations might occur due to the continuous Subject quality improvement process, and in case of minor variation(s) in assessment details, the Subject Outline represents the latest official information.