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Talk to an Expert| Category | Assignment | Subject | Business |
|---|---|---|---|
| University | King's College London (KCL) | Module Title | 0LEC30BS Business and Society |
| Module Title | Business and Society |
| Module Code | 0LEC30BS |
| Assignment Title | Summative 3: Argumentative Essay |
| Weighting | 40% |
| Deadline | Monday, 27th April 2026, before 11:00 am |
| Feedback Return | Tuesday, 27th May 2026, 6:00 pm |
| Module Learning Outcomes Assessed | LO1, LO2, LO3, LO4 |
| Word Count | 1200 (+5%) |
| Criteria Used in Assessment | Written Marking Criteria 25-26 |
| File Types Accepted | Microsoft Word and Adobe pdf. |
| Suggested Time Necessary to Complete | 25 hours (over 7 weeks, approximately) |
Select one of the 4 questions listed below and write an academic argumentative essay on it.
Note: The business case example can be from any week in the module.
| Topic | Essay Question |
|---|---|
| Business Measures | Can ethical decision-making in business be improved by relying more—or less—on data? Discuss using one business example from the module and reflect on the limitations of data-driven business decisions in complex social contexts. |
| Service Industries | Should essential services like health and education be protected from market logic? Critically evaluate the risks and benefits of treating these sectors as businesses, using one business example from the module. |
| Globalisation & Ethics | Is ethical business possible in a globalised world? Use one case study from the module to explore how globalisation shapes ethical challenges and opportunities across cultures and sectors. |
| Sustainable Business | How can consumers and investors distinguish between genuine sustainability and greenwashing in business? Use one business example from the module to explore the challenges of transparency, accountability, and impact measurement. |
We recommend a 5-paragraph structure (Introduction, 3 Body Paragraphs, Conclusion). For example:
1. Business Measures
Intro: Background and stance developed in detail.
Body 1: Benefits of data-driven ethics.
Body 2: Risks and limitations.
Body 3: Case study from the module showing both sides.
Conclusion: Your position on whether more or less reliance is better.
2. Service Industries
Intro: Background and stance developed in detail.
Body 1: Benefits of business models in health/education.
Body 2: Risks of this commodification.
Body 3: Case study and ethical implications.
Conclusion: Your stance on whether protection from market logic is needed.
3. Globalisation & Ethics
Intro: Background and stance developed in detail.
Body 1: Ethical opportunities.
Body 2: Ethical challenges.
Body 3: Case study both.
Conclusion: Your judgement on whether ethical business is possible globally.
4. Sustainable Business
Intro: Background and stance developed in detail.
Body 1: What makes sustainability genuine.
Body 2: How greenwashing works and why it’s hard to detect.
Body 3: Case study and stakeholder roles.
Conclusion: Your view on how consumers/investors can tell the difference.
1. Understand the Task:
Read all four essay questions carefully. Choose the one that interests you most and allows you to use examples from the module. Make sure you understand the key terms in the question (e.g. “ethical decision-making,” “market logic,” “greenwashing”).
2. Analyse the Question:
Identify the debate or tension in the question. Ask yourself: What are the two or more sides of this issue? Decide what your position will be (your argument or thesis).
3. Plan Your Essay Structure:
You may ask your seminar tutor for essay support during F&G hours for the following aspects of the assessment: checking you have interpreted the question correctly, discussing the outline, sense-checking whether the chosen business case is an effective example, consulting on references and their validity or relevance. Tutors will not read drafts of the essay.
4. Select and Use Sources:
Select sources that are relatively recent, unless you are referring to a core theory or past event.
5. Draft Thoughtfully:
Write in your own words. Avoid copying from lectures, AI tools, or websites, as well as inadvertently colluding with a friend after having shared ideas. Use topic sentences, transitions, and academic language. Avoid overusing quotes—paraphrase and analyse instead.
6. Be critical:
Question assumptions, compare perspectives, and show awareness of complexity.
7. Revise and Proofread:
Check your word count (1200 words ±5%). Make sure your argument is clear and consistent. Review grammar, referencing, and formatting. Ask yourself: Does this sound like my voice? Could I explain this in a seminar?
The deadline for this task is 11:00am Monday, 27th April 2026, before 11 am.
Submission after 10:59:59 will be considered a late submission and may result in penalties.
You must submit the assessment electronically via the KEATS module page. Please ensure you submit via Turnitin.
The assignment must include a completed cover sheet. This document can be found in the ‘Submit Assignment’ section on the module KEATS page.
Assignments are marked anonymously, and so you will need to submit using your student number (i.e. the number on your student card). This number should be clearly visible on the first page of the assignment. Please do not include your name on any part of the assignment.
Please name your assignment with your student number and class number (i.e. K1714743_BS4)
Assignments must be submitted on time. Penalties for non-submission and late submission are detailed in the King’s Foundations Student Handbook.
The suggested word count for this task is 1200 words. Title and reference list are not included in this total.
No penalty is applied for assignments which are up to 5% over the suggested work count. This means that the upper limit is 1260 words. 2% will be deducted for every 5% over the upper word limit (see the King’s Foundations Student Handbook for details).
Assignments exceeding this word limit by more than 5% will be penalised (see the King’s Foundations Student Handbook for details).
There is no penalty for under-length assignments; however, assignments that are more than 5% below the word count are unlikely to give adequate answers to the questions set.
Do not include visual data (e.g., graphs, diagrams) in your assignment.
You must also be sure to acknowledge any sources with correct referencing. Please note that in-text citations such as (Smith, 2021) are counted in the word count, so Smith, 2021 would count as two words.
All the sources should be adequately cited and included in a Reference List at the end of your submission; that is, your Reference List will include an entry for the Lecture/s and another one for the Core Text from the Source Pack.
You must present your work in a standard essay format, consisting of an introduction, body, and conclusion (note: you should not provide headings for these sections).
Use 12pt Arial or Times New Roman font. Written assignments should be 1.5-line spaced, with a single empty line between paragraphs.
You must fully reference your assignment (i.e., use in-text author/date/page citations and provide a full reference list at the end). Please use APA 7th Referencing Style as per the KCL APA 7th guidance.
If you are unable to submit your assignment by the deadline above and you believe you have a valid reason for this, you must complete the Mitigating Circumstances process. Information and guidance can be found via the ‘Assessment’ section on Student Services Online.
Using AI tools like Copilot or ChatGPT can support your learning, but using them uncritically or unethically may negatively impact your final grade. If you copy AI-generated content without understanding or adapting it, your work may lack originality, critical thinking, and synthesis — all of which are required by the marking criteria. Over-reliance on AI can also raise academic integrity concerns. You are responsible for ensuring that your submission reflects your own understanding and meets university standards.
Level of generative AI use allowed in B&S: Open.
Please see the King’s Generative AI Student Guidance for more details about what Open use of generative AI means.
Advice on the use of Generative AI – Please follow these 3 golden rules:
If you follow these three rules you are essentially ensuring that your assessed outputs are unlikely to breach academic integrity guidance in terms of use of generative AI.
Your response should:
Other points to remember:
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