Unit Synopsis
In this unit, you will examine contemporary issues in human resource management (HRM) and explore the impact that new developments in people analytics have on an organisation's ability to strategically attract, recruit, retain and manage its human resources in a competitive environment. In addition, this unit will raise your awareness of the relevance of Aboriginal and Torres Strait Islander cultures in good business practices, as well as apply lessons from those cultures for good ethical, social, and governance outcomes in HRM contexts.
Details
| Level | Postgraduate |
|---|---|
| Unit Level | 8 |
| Credit Points | 6 |
| Student Contribution Band | SCA Band 4 |
| Fraction of Full-Time Student Load | 0.125 |
| Pre-requisites or Co-requisites |
There are no pre-requisites for the unit.
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. Presentation | 15% |
| 2. Group Work | 35% |
| 3. Written Assessment | 50% |
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 .
Term 2 - 2025 : The overall satisfaction for students in the last offering of this course was 57.14% (`Agree` and `Strongly Agree` responses), based on a 31.82% response rate.
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: Unit coordinator self reflection
Continue to enhance new unit contents - People Analytics contents of the unit and Assessment 3
There is a need to appoint a new academic with a strong analytics background to manage this unit. This person should enhance teaching materials, including readings, case studies, statistics and new recordings on data analyses. These resources are to enhance students' understanding of statistics, predictive analysis, and decision-making. Ensure Assessment 3 is clear and easy to follow.
In response to the recommendation to appoint a new academic with expertise in analytics, a qualified academic with a strong background in data analysis and predictive modelling was successfully recruited to manage this unit. The following actions were implemented during this semester: • Enhanced Teaching Materials: The academic updated and expanded the learning resources, including readings, case studies, statistical examples, and newly recorded tutorials on data analysis techniques. These materials were designed to improve students' understanding of key concepts such as statistics, predictive analysis, and decision-making. • Improved Assessment 3: Assessment 3 was revised to ensure clarity and ease of understanding. Detailed instructions, step-by-step guidelines, and examples were provided to help students navigate the requirements effectively. • Focus on Practical Application: The updated resources and teaching approach emphasised practical applications of analytics, enabling students to apply theoretical knowledge to real-world scenarios. These updates were implemented to address the feedback received and to enhance the overall learning experience for students enrolled in the unit.
Source: Unit coordinator self reflection
New lecture recording are required
New lecture recordings and updated lecture slides should be done in T1 2025 to provide students with a more comprehensive and clear explanation of HR analytics.
In response to the recommendation to create new lecture recordings and update lecture slides for T1 2025, the following actions were implemented: • New Lecture Recordings: Comprehensive lecture recordings were developed, focusing on key HR analytics concepts. These recordings provided detailed explanations and practical examples to enhance students' understanding of the subject matter. • Supplementary Resources: Additional resources, including step-by-step guides, were created to support students in mastering complex HR analytics topics. These actions were taken to ensure that students receive a more thorough and clear understanding of HR analytics, addressing the feedback received from previous terms.
Source: Student Survey
Low response rates and lower satisfaction scores in T2-2025 suggest reduced student engagement and limited opportunities for feedback dialogue, particularly in smaller cohorts.
Increase structured opportunities for formative feedback and engagement, including targeted check-in activities prior to major assessments, and clearer promotion of student evaluation processes. Teaching staff should explicitly close the feedback loop by communicating how student feedback has informed unit improvements.
In Progress
Source: Unit Coordinator
some students required clearer guidance on assessment expectations, evaluation criteria, and performance standards, particularly for the analytics-focused components of the unit.
Implement explicit, structured in-class assessment activities across all cohorts from the early weeks of the term, including assessment walkthroughs, discussion of marking criteria and exemplars, and guided evaluation of sample responses during workshops.
In Progress
Source: Unit Coordinator
Lower engagement levels in some cohorts suggest that group formation and peer engagement may not have been sufficiently established early in the term, limiting collaboration and participation in workshops.
Introduce early, staff-supported group development activities within the first two weeks of the term. Teaching staff should actively facilitate group formation, clarify group roles and expectations, and encourage early collaboration through low-stakes, in-class activities. This approach should be supported by structured icebreaker tasks and early collaborative exercises to promote engagement and accountability from the outset.
In Progress
On successful completion of this unit, you will be able to:
- Identify key contemporary issues throughout the employment cycle and evaluate those which could affect HRM effectiveness.
- Critically analyse key contemporary HR issues and their implications for effective HRM.
- Evaluate approaches that could be used to address contemporary HRM issues.
- Develop an understanding of people analytics, its opportunities and risks in relation to HRM.
- Analyse and interpret organisation's data to make evidence-based HRM decisions.
None
| Assessment Tasks | Learning Outcomes | ||||
|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |
| 1 - Presentation | • | • | • | ||
| 2 - Group Work | • | • | • | ||
| 3 - Written Assessment | • | • | |||
| Graduate Attributes | Learning Outcomes | ||||
|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |
| 1 - Knowledge | • | • | • | • | • |
| 2 - Communication | • | • | • | ||
| 3 - Cognitive, technical and creative skills | • | • | • | • | • |
| 4 - Research | • | • | • | ||
| 8 - Aboriginal and Torres Strait Islander Cultures | • | ||||
| Assessment Tasks | Graduate Attributes | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 8 | |