CQUniversity Unit Profile

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MGMT29005 Data and Ethics
Data and Ethics
All details in this unit profile for MGMT29005 have been officially approved by CQUniversity and represent a learning partnership between the University and you (our student).
The information will not be changed unless absolutely necessary and any change will be clearly indicated by an approved correction included in the profile.
General Information

Overview

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

Career Level: Postgraduate
Unit Level: Level 9
Credit Points: 6
Student Contribution Band: 10
Fraction of Full-Time Student Load: 0.125

Pre-requisites or Co-requisites

Students must have completed, or have been granted credit for MGMT29009 Operations Management and Business Analytics and LAWS29001 Governance and Business Law to undertake this unit. Students enrolling in this unit must be undertaking the CL84 Master of Business Administration (International).

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).

Offerings For Semester 1 - 2021

Jakarta

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).

Class and Assessment Overview

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 Overview

Assessment Grading

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%). Consult the University’s Grades and Results Policy for more details of interim results and final grades.

Unit Learning Outcomes
On successful completion of this unit, you will be able to:
  1. Critically reflect on the ethical dimensions of the data science, its purpose, methods and impact in data-driven organisations
  2. Apply ethical techniques in auditing data-driven processes in organisational contexts
  3. Analyse established ethical techniques and strategies, independently and within teams, to identify and minimize potential harm associated with data driven organisational processes
  4. Demonstrate knowledge, skills and ideas related to ethical aspects of data, its collection, management and uses to a range of stakeholders.
Alignment of Learning Outcomes, Assessment and Graduate Attributes
N/A Level
Introductory Level
Intermediate Level
Graduate Level
Professional Level
Advanced Level

Alignment of Assessment Tasks to Learning Outcomes

Assessment Tasks Learning Outcomes
1 2 3 4
1 - Written Assessment - 40%
2 - Presentation - 30%
3 - Reflective Practice Assignment - 30%

Alignment of Graduate Attributes to Learning Outcomes

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
8 - Aboriginal and Torres Strait Islander Cultures

Alignment of Assessment Tasks to Graduate Attributes

Assessment Tasks Graduate Attributes
1 2 3 4 5 6 7 8
1 - Written Assessment - 40%
2 - Presentation - 30%
3 - Reflective Practice Assignment - 30%
Textbooks and Resources

Textbooks

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The textbooks have not yet been finalised.

IT Resources

You will need access to the following IT resources:
Referencing Style

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Teaching Contacts

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Schedule

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Assessment Tasks

Information for Assessment Tasks has not been released yet.

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Academic Integrity Statement

Information for Academic Integrity Statement has not been released yet.

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