Unit Synopsis
This advanced unit builds on the ethical and legal foundations introduced in the core units LAWS20063 Governance and Business Law and MGMT20130 Operations Management and Business Analytics. The emerging field of data science encompasses "big data" and "data analytics". In this unit you will analyse ethical considerations specific to study design, data collection methods, data analysis and the appropriate dissemination and application of findings. You will apply the ethical duties of researchers and analysts to ensure that ethical protocols have been respected and that the rights and consequences of participants and users have been acknowledged and respected. You will employ practical tools to help you to identify ethical dilemmas and develop strategies for ensuring ethical decision making and resulting behaviours. You will also examine the role of organisational and industry cultures in shaping ethical (or unethical) data analytic practices, thus addressing the United Nation's sustainability development goals with respect to responsible business operations, new business models, investment, innovation and technology and collaboration.
Details
| Level | Postgraduate |
|---|---|
| Unit Level | 9 |
| Credit Points | 6 |
| Student Contribution Band | SCA Band 4 |
| Fraction of Full-Time Student Load | 0.125 |
| Pre-requisites or Co-requisites |
Students enrolling in this unit must be undertaking the CL84 Master of Business Administration (International) or the CM45 Professional Certificate in Business (Data Science). Important note: Students enrolled in a subsequent unit who failed their pre-requisite unit, should drop the subsequent unit before the census date or within 10 working days of Fail grade notification. Students who do not drop the unit in this timeframe cannot later drop the unit without academic and financial liability. See details in the Assessment Policy and Procedure (Higher Education Coursework). |
| Class Timetable | View Unit Timetable |
| Residential School | No Residential School |
Unit Availabilities from Term 1 - 2026
Attendance Requirements
All on-campus students are expected to attend scheduled classes - in some units, these classes are identified as a mandatory (pass/fail) component and attendance is compulsory. International students, on a student visa, must maintain a full time study load and meet both attendance and academic progress requirements in each study period (satisfactory attendance for International students is defined as maintaining at least an 80% attendance record).
Recommended Student Time Commitment
Each 6-credit Postgraduate unit at CQUniversity requires an overall time commitment of an average of 12.5 hours of study per week, making a total of 150 hours for the unit.
Assessment Tasks
| Assessment Task | Weighting |
|---|---|
| 1. Written Assessment | 40% |
| 2. Presentation | 30% |
| 3. Reflective Practice Assignment | 30% |
This is a graded unit: your overall grade will be calculated from the marks or grades for each assessment task, based on the relative weightings shown in the table above. You must obtain an overall mark for the unit of at least 50%, or an overall grade of ‘pass’ in order to pass the unit. If any ‘pass/fail’ tasks are shown in the table above they must also be completed successfully (‘pass’ grade). You must also meet any minimum mark requirements specified for a particular assessment task, as detailed in the ‘assessment task’ section (note that in some instances, the minimum mark for a task may be greater than 50%).
Past Exams
All University policies are available on the Policy web site, however you may wish to directly view the following policies below.
This list is not an exhaustive list of all University policies. The full list of policies are available on the Policy web site .
No previous feedback available
Feedback, Recommendations and Responses
Every unit is reviewed for enhancement each year. At the most recent review, the following staff and student feedback items were identified and recommendations were made.
Source: Self-reflection
Need more discussion among students
Implement more interactive workshop activities to encourage students to participate in discussions.
Questions asked during the session, pause, and encourage them to make comments or feedback before continuing to the next topics. One or two students participated and made good comments.
Source: Self-reflection
Need more collection of available 'case studies'
Case studies (e.g. Harvard style) on the unit theme would be a good source for reference as well as for the final exam or group assessment.
This is an ongoing activity - some inroads have been made but more cases still need to be identified.
Source: Self-reflection.
The group assignment should have an individual component.
Incorporate an individual component within the group assignment, based on students' self- and peer-assessment of their group mates.
In Progress
On successful completion of this unit, you will be able to:
- Critically reflect on the ethical dimensions of the data science, its purpose, methods and impact in data-driven organisations
- Apply ethical techniques in auditing data-driven processes in organisational contexts
- Analyse established ethical techniques and strategies, independently and within teams, to identify and minimize potential harm associated with data driven organisational processes
- Demonstrate knowledge, skills and ideas related to ethical aspects of data, its collection, management and uses to a range of stakeholders.
| Assessment Tasks | Learning Outcomes | |||
|---|---|---|---|---|
| 1 | 2 | 3 | 4 | |
| 1 - Written Assessment | • | • | • | • |
| 2 - Presentation | • | • | ||
| 3 - Reflective Practice Assignment | • | • | ||
| Graduate Attributes | Learning Outcomes | |||
|---|---|---|---|---|
| 1 | 2 | 3 | 4 | |
| 1 - Knowledge | • | • | • | • |
| 2 - Communication | • | |||
| 3 - Cognitive, technical and creative skills | • | • | ||
| 4 - Research | • | • | • | |
| 5 - Self-management | • | • | ||
| 6 - Ethical and Professional Responsibility | • | • | • | |
| 7 - Leadership | • | |||
| Assessment Tasks | Graduate Attributes | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 8 | |