7WBS2007-0901-2025 Human Resource Management Assignment 2 Brief 2025
| University | Singapore University of Social Science (SUSS) |
| Subject | Human Resource Management |
Assignment Brief
|
Module Title: |
Human Resource Management |
Module Code: |
7WBS2007-
0901-2025 |
| Assignment Format & Maximum Word count | AI vs Human Judgment in
Cross-Cultural HRM (3000 words) |
Assignment weighting |
70% |
| Coursework Submission: | Time:23:59pm
Date: 5th November 2025 |
Assessment Criteria |
| Learning Outcomes: Knowledge and Understanding assessed in this assignment:
• Assess the role and scope of people management practices and activities. • Appraise the main contextual factors impacting on people management. • Evaluate the main strategic approaches to people management. |
| Learning Outcomes: Skills and Attributes assessed in this assignment: |
| • Reflect upon the complexities and challenges of people management and intercultural working.
• Analyse a range of people management issues and make relevant proposals to address them, both individually and working collaboratively. |
| Transformational Opportunities:
E.g. Use LinkedIn Learning to improve skills |
| Feedback /Marking criteria for this Assignment |
| • Performance will be assessed using HBS Grading Criteria (Rubric) |
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Detailed Brief for Individual / Team Assignment
| Assignment Title: : AI vs Human Judgment in Cross-Cultural HRM Description of the assignment, task, content and structure:
Global businesses face people-management challenges across different cultural and institutional environments. Common problems include failed expatriate postings, complex global talent moves, and leading diverse international teams. These situations create tension between “one global HR way” and what actually works locally. In this assignment you will: • Use a country lens: Identify 1–2 HRM issues in your own country that make cross-border people management harder for international organisations. Examples: hiring in a highly regulated labour market, performance management that clashes with local norms, reward practices shaped by law or custom, expatriation/repatriation hurdles, or diversity and inclusion challenges. • Pick one cross-cultural HRM scenario: choose one of the following and link it to your country issues: 1. Expatriate assignment failure 2. Global talent mobility 3. Managing diverse international teams (including remote/hybrid) • Use AI tools (such as ChatGPT, Claude, or an HR simulator) to generate solutions such as training modules, onboarding materials, relocation policies, conflict-resolution approaches, or support systems. • Benchmark the AI against peer-reviewed research in cross-cultural HRM/international management and professional guidance (For instance, CIPD, SHRM, credible case studies). • Reflect on limits: Show where AI oversimplifies or misses cultural nuance, legal specifics, and ethical issues. • Propose a decision framework: Explain when AI-generated insights are helpful and when human expertise is essential. Why this matters
Suggested Scaffolded Structure1. Introduction (400 words) Introduce your chosen HRM scenario (for instance expatriate failure, global mobility, or managing diverse teams) remember you can include any HRM Scenario of your choice, but it is important you provide adequate evidence. • State your country focus and why it matters in cross-cultural HRM. • Outline the purpose: testing AI solutions against theory and human judgment. • why is this issue worth studying? Provide adequate Justification 2. Country HRM Issues (400 words) |
||||
| • Identify 1–2 HRM challenges in your country that affect global organisations. • Support with evidence (laws, statistics, reports, or real company examples).
• Show how these issues connect to your chosen scenario. • Reflective on; How do these issues play out in your context? What has worked or failed in practice? 3. AI-Generated Solutions (400 words) • Summarise AI’s suggested solutions • Comment on your first impressions: did AI provide practical, culturally aware ideas, or was it too generic? • Reflective thinking: How did you feel about using AI? Did it surprise you, or did it confirm expectations? 4. Evaluation: AI vs Theory and Practice (800 words) • Compare AI’s outputs with academic theories (for instance, Hofstede, Trompenaars, GLOBE, Institutional Theory, SHRM). • Contrast with professional guidance (CIPD, SHRM, case studies). • Identify alignments and gaps. • Evaluative thinking: Which approach is stronger, and why? Do AI’s outputs hold up against research and professional standards? 5. Reflection on AI’s Limits (400 words) • Show where AI fell short: cultural nuance, legal details, ethics, or bias. • Use examples from outputs to demonstrate oversimplification or error. • Reflective thinking: What did you learn about AI’s limitations through this task? How would this affect your own practice as an HR professional? 6. Framework for Practice (300 words) • Provide a clear, practical decision framework (table, diagram, or bullet list): • When AI can help? • When humans are essential? • Why does your framework make sense? What are its strengths and possible weaknesses? 7. Conclusion (300 words) • Summarise the main findings. • Re-state AI as a support tool, not a replacement. • Emphasise what this means for the future of HRM practice. • What is the “big lesson” for you and for organisations? Refences (Peer reviewed Journals, CIPD, Government, Business annual reports) 8. Appendix • Full AI prompts and outputs. • Short note on your process: what you learned about working with AI. Marking Criteria1. Use of Theory and Country Evidence (25%) • Identify 1–2 HRM challenges in your country clearly. • Apply at least two HRM theories/models to explain why those challenges matter in the chosen scenario. • Use country-specific evidence (e.g., legislation, data, reports, examples). 2. Critical Evaluation (25%) |
| • Compare AI’s suggested solutions with academic literature and professional HR guidance.
• Judge the quality of AI’s advice: Where is it useful? Where is it shallow or misleading? • Show clear reasoning when deciding which insights (AI, theory, or practice) are stronger. 3. Reflection and Framework (20%) • Reflect on what you learned by using AI. Be specific (e.g., “AI ignored gender norms in my country’s labour law”). • Build a simple, practical framework (e.g., a table, flowchart, or bullet list) that shows: ü When AI can help HR work. ü When human expertise must take over. 4. Writing and Referencing (10%) • Write in a clear, structured way using the scaffold • Use proper Harvard referencing for theories, articles, and professional guidance. 5. AI Use and Transparency (20%) • Where it shows up in your report: AI Outputs section + Appendix • Summarise AI outputs clearly in the main report. • Put full prompts and outputs in the appendix. • Reflect on how you used AI and how you checked its accuracy. Any specific instructions: The HBS Grading Criteria (rubric) will evidence how marks are awarded for individual parts of the assignment i.e. Presentation and Structure, Intellectual Curiosity and Referencing, Content, Analysis, Discussion |
Use of Generative AI |
| Your use of generative AI (genAI) tools in this assessment must follow one of the three categories below. Your Module Leader will indicate which category applies:
Category 1 – Authorised use of AI You are permitted to use genAI tools to create content for your work and to proofread your work. Alternatively, you may use a proofreader or non-genAI proofreading service. Category 2 – Proofreading only permitted You are permitted to use genAI tools (or a proofreader or proofreading service) to proofread your work, but you are not permitted to use AI tools to create content. This applies even if the assessment includes marks for English and grammar. Category 3 – AI use not permitted You are not permitted to use genAI tools for content creation or proofreading. This category applies where all or most marks are awarded for language proficiency (including spelling, punctuation, and grammar). For this assignment, you are allowed to use GenAI tools to create content. Students must comply with the category selected for this assessment. Improper or undeclared use of AI tools may be considered academic misconduct. |
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PG Grading Criteria for HBS Individual Report
Module Code: 7WBS2007-0901-2025
Lecturer: Dr Samaila Ado Tenebe
| REPORT | Presentation & structure | Intellectual Curiosity (Quality of academic sources)
Use & presentation of Harvard Referencing |
Content/ Terms/
Findings/ Definitions/ Calculations |
Business
Application & Integration of Data/Literature |
Discussion /Analysis
/Critical evaluation &/or Reflection |
| Task details lecturer to
amend to suit |
Follows report structure & keeps to word limit of The scaffolded structure in the brief is very clear
(introduction, country HRM issues, AI- generated solutions, evaluation, reflection, framework, conclusion, references, appendix). Students must stick to this layout, with word allocations already provided, otherwise coherence will collapse. Marks here will reward clear headings, logical flow, and observance of the 3,000-word limit. Good reports should signpost arguments (e.g., linking “country HRM issues” directly into the AI vs. theory section), and avoid padding. |
Follows Harvard style for in-text citation & Reference List
The brief demands strict application of Harvard style for both in-text citations and reference list. That means page numbers for direct quotes, consistent formatting of journal titles, italics for books, and correct ordering. Students should also reference AI use transparently in the appendix. Sloppy or inconsistent referencing (missing years, incorrect punctuation) will undermine marks in this section.
The brief explicitly requires peer- reviewed journals, CIPD/SHRM guidance, government reports, and credible business examples. Students cannot lean on generic websites or only AI outputs. Quality will be judged by range, depth, and recency of sources. A strong submission will integrate multiple theoretical lenses (e.g., Hofstede, GLOBE, institutional theory) and apply them critically to context. Weak submissions will only cite textbooks or rely on AI without triangulation.
Minimum of 20 peer-reviewed journals |
Content included – students must correctly define and apply HRM terms
(e.g., expatriate failure, global talent mobility). Content should demonstrate accurate understanding of cross-cultural HRM debates and how AI’s input aligns (or misaligns) with them. Findings must come not just from AI outputs but from comparison with practice and academic literature. |
Integration & application of information – Students must use national labour laws, HR practices,
or real corporate cases. Application means not just stating Hofstede’s dimensions but showing how they complicate, for instance, performance management in Japan vs. UK. Strong report will integrate theory, country evidence, and AI outputs seamlessly into a single discussion. Weak report will keep them in silos. |
Line of argument, development of discussion – Students are expected to interrogate AI’s usefulness, not just describe it. Reflection must be personal and professional (“what did I learn about AI’s blind spots?”). Critical evaluation means contrasting AI’s generalised answers
with specific, contextualised evidence from research and practice. The “framework for practice” is where reflection turns into a tangible outcome. |
| Marks | |||||
|
90 – 100
Outstanding |
Outstanding presentation & report structure,
with numbered paragraphs, list of contents/figures &appendices. Articulate & fluent academic writing style with ideas cross referenced. No grammatical / spelling errors. |
Outstanding selection of quality sources, well beyond core & recommended resources. Outstanding standard of Harvard referencing within text & consistent use of Harvard referencing system. Accuracy of in-text references & full details shown in Reference list. | Outstanding
exploration of topic showing excellent knowledge & understanding through thorough & appropriate research. Impressive choice and range of appropriate content. |
Outstanding business insight & application. Outstanding integration of literature/data into work. Very impressive breadth and depth. | Outstanding level of discussion/analysis/ critical evaluation &/or reflection.
Highly developed/ focused work, with thorough consideration of all possibilities and aspects of the topic. |
| 80 – 89
Excellent |
Excellent presentation & report structure, with numbered paragraphs, list of contents/figures, appendices & cross referencing. Articulate & fluent academic writing style. Only minor errors. | Excellent selection of quality sources. Evidence of independent searching beyond core & recommended resources.
Excellent standard of Harvard referencing within text & consistent use of Harvard referencing system. Accuracy of in-text references & full details shown in Reference list. |
Excellent level of knowledge & understanding demonstrated.
Evidence of appropriate reading. Covers all relevant points & issues. |
Excellent business insight & application. Excellent integration of literature/data into work. Impressive breadth and depth. | Excellent level of discussion/analysis/ critical evaluation &/or reflection. Clearly developed points all of which are relevant to the topic |
| 70 – 79
Very Good |
Very good presentation & report structure, paragraphing, use of numbering, list of contents/figures, appendices & cross referencing. Fluent academic writing style. Very few
grammatical errors & spelling mistakes. |
Very good selection of mostly quality sources beyond the recommended resources. Few irrelevant/poor quality sources used.
Very good standard of Harvard referencing within text & consistent use of Harvard referencing system. Accuracy of in-text references & full details shown in Reference list. |
Very good level of knowledge & understanding demonstrated. Covers most relevant points & issues. Few errors / omissions in content/calculations. | Very good business insight & application. Very good integration of literature/data into work. Very good use of literature/data with breadth and depth. | Very good level of discussion/analysis/ critical evaluation &/or reflection. A few less relevant ideas/points or would benefit from further development &/or evaluation/comparison. |
| 60 – 69
Good |
Good clear presentation & report structure, use of numbering & appendices. Writing is mainly good with some flow and spelling &/ or grammatical errors seldom impede understanding. | Good selection of quality sources but some irrelevant/poor quality sources used beyond the recommended reading. Good standard of Harvard referencing within text & consistent use of Harvard referencing system. Accuracy of in-text references & full details shown in Reference list. | Good grasp of the topic
& some of its implications presented. Good knowledge & understanding is demonstrated. Minor errors / omissions in content/ calculations. |
Good business insight & application.
Good integration of literature/data into work. Good use of literature/data with adequate breadth and depth. |
Good level of discussion/analysis/ critical evaluation &/or reflection but more ideas/points could be addressed or developed further. |
| 50 – 59 Clear Pass | Satisfactory basic report structure. Not always written clearly & has grammatical & / or spelling errors which impede understanding.
See CASE with feedback |
Satisfactory: Some quality sources used. Research did not go beyond the recommended sources.
Satisfactory referencing within text & consistent use of Harvard referencing system.
See CASE/ Information Managers (LRC) with feedback |
Satisfactory content / level of knowledge of the topic. Addresses most of the task. Some errors / omissions in content/ calculations. May benefit from further research. | Satisfactory business insight & application. Limited integration with literature/ data. Use of literature/data but limited in breadth or depth. | Satisfactory: basic evidence of discussion/analysis/ critical evaluation &/or reflection but some points irrelevant or superficially made so need further development. See CASE with feedback |
| 40 – 49
Marginal Fail |
Weak report format. Limited or poor structure. Muddled work with many spelling & / or grammatical errors.
Must see CASE with feedback |
Weak: Limited evidence of appropriate research. Some use made of recommended reading, but the majority of sources are irrelevant/of poor quality. Weak use of Harvard referencing system with errors & inconsistently applied.
Must see CASE/ Information Managers (LRC) with feedback |
Weak: limited content / knowledge/
calculations. Limited or muddled understanding of the topic/question. Does not meet all the learning outcomes. |
Weak:
unsatisfactory evidence of business application & insight Work needs to show better links between practical application and theory. |
Weak: limited evidence of discussion/analysis/ critical evaluation &/or reflection.
More development & comment needed. May need to do more than describe. Must see CASE with feedback |
| 20 – 39
Clear Fail |
Inadequate report format and poor paragraphing / signposting. Inappropriate writing style Poorly written &/or poor spelling & grammar. Must see CASE with feedback | Inadequate: Little evidence of appropriate research. Few quality sources used from recommended reading. Inadequate use of Harvard referencing with many errors &/or inconsistencies.
Must see CASE/ Information Managers (LRC) with feedback |
Inadequate: Lacking in relevant content/ knowledge/calculations. Content irrelevant / inaccurate. Does not meet all the learning outcomes. | Inadequate: Lacks evidence of business application & insight. Some literature missing or irrelevant to topic. | Inadequate: Lacking / inadequate level of discussion/ analysis/critical evaluation & /or reflection.
Descriptive.
Must see CASE with feedback |
| 0 – 19
Little or Nothing of merit |
Nothing of merit: Poorly written work, lacking structure, paragraphing / signposting. Many inaccuracies in spelling & grammar. Must see CASE with feedback | Nothing of merit: No evidence of research. No use made of recommended reading. Sources are
irrelevant & of poor quality. No or little attempt to use the recommended Harvard referencing system. Must see CASE/ Information Managers (LRC) with feedback |
Nothing of merit: Unsatisfactory level of
knowledge demonstrated. Content used irrelevant / not appropriate/ to the topic. Does not meet the learning outcomes. |
Nothing of merit: No evidence of appropriate business application & insight. | Nothing of merit: Unsatisfactory level of discussion/analysis/critical
evaluation &/or reflection
Must see CASE with feedback |
|
KEY ACTIONS To achieve a higher grade, next time you need to… (Where to go?) Who can help?) |
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