Analysing Work-Life Balance Through AI-Assisted Research

School of Business

About this use case

This written assessment asks students to critically analyse work-life balance (WLB), including work-family balance (WFB) and work-health balance (WHB).

Students begin with the foundational article provided by educator, then extend their research using additional academic journal articles, news sources and company practices. Consensus AI and Research Rabbit may be used to support the search for relevant academic literature.

The resulting literature review should establish the significance of different aspects of work-life balance and critically engage with the research rather than merely summarising it.

Learning outcomes:

Critically evaluate management theory and research evidence.
Propose effective business solutions aligned with responsible management practices.

The assessment was designed to help students locate relevant academic journal literature and develop a broader, more nuanced understanding of work-life balance. AI-assisted research tools are incorporated to facilitate the literature-search process.
1. Introduce students to Consensus AI during a tutorial.
2. Demonstrate how the tool can support the search for relevant academic literature.
3. Ask students to discuss the benefits and limitations of using AI-assisted research tools.
4. Reinforce that AI tools supplement research conducted through academic articles, news sources and company practices.
Students may develop their ability to:
- locate relevant literature using AI-assisted research tools.
- examine work-life balance across work-family and work-health dimensions.
- establish the background and significance of different aspects of work-life balance.
- critically engage with management research and evidence.
- use research evidence to propose responsible business solutions.
- recognise the benefits and limitations of AI-assisted literature searching.

Try it out

This use case requires a medium level of effort to implement.

- Select a foundational academic article that introduces the main dimensions of the topic.
- Ask students to extend their investigation using additional academic journal articles, news sources and company practices.
- Introduce Consensus AI or Research Rabbit as optional tools for supplementing the literature search.
- Demonstrate the use of Consensus AI during a tutorial.
- Facilitate a discussion about the benefits and limitations of AI-assisted research.
- Require students to critically analyse and synthesise the literature rather than only summarising it.
- Start with one and give it a try. Developing an authentic case study for the first time may seem challenging, but the case does not need to be perfect. The experience gained from the first attempt will help you identify what works, what can be improved, and how to develop stronger and more engaging cases over time.
- Collaborate with colleagues across different units or disciplines. Case study development does not have to be an individual effort. Bringing together different areas of expertise can create a richer and more multidimensional business scenario.
- Think beyond a single topic or unit. One case can intentionally incorporate two or three business issues or themes, for example, management, marketing, sustainability, accounting, or strategy, allowing the same organisational story to be approached from different disciplinary perspectives.
Indirect observation through drafts and process documentation
This assessment builds on Assessment 3a, requiring students to revisit and refine their literature review, key findings, and preliminary recommendation. In Assessment 3b, students progress from developing an initial understanding of the case to critically evaluating a GenAI-generated recommendation against academic and organisational evidence, before developing and justifying their own evidence-based recommendation. This progression provides an opportunity to observe students’ development in research, critical evaluation, and evidence-based decision-making across the two assessment stages.

Supporting resources

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Sidebar

Unit: MGW1010	Condition: Individual
Class size: 500–600	Typology: Written
AI approach: Using and applying AI tools effectively	AI statement: Guided use
Visibility of Learning: Indirect observation through drafts and process documentation

About the educator

Validated by

Melissa Wong, Senior Education Designer, Education Excellence