OUMH1203 English for Written Communication Assignment Sample: AI Literacy Essay | OUM

For information and reference only – not to be submitted as your own work.

This sample illustrates how to approach Part I of the Open University Malaysia (OUM) OUMH1203 English for Written Communication assignment, September 2026 semester. Part I asks for the process of writing a basic essay in three stages, using the question: “Do you agree that Malaysian universities should introduce a compulsory AI literacy module for all undergraduate students?” You can browse related briefs on the OUM question hub, and an earlier 2026 OUMH1203 brief shows how the module words its stages (add the September 2026 question link when it is live). A planning guide is in our OUMH1203 three-stage essay guide.

The original assessment brief is available on our question page: OUMH1203: With the current pandemic situation in Malaysia, homeschooling is gaining MORE popularity among Malaysian parents: English for Written Communication Assignment, OUM, Malaysia.

The extract below covers Stage 1 in full (outline and thesis) and a short sample of the final essay. OUM penalises heavy unattributed use of AI-generated text, so write your own version, follow your assessment brief and rubric, and declare any permitted tool use.

Stage 1: Pre-writing and outlining

Position

I agree that Malaysian universities should introduce a compulsory AI literacy module for all undergraduate students.

Thesis statement

Malaysian universities should require every undergraduate to complete an AI literacy module because it develops the critical evaluation skills students need to use generative AI responsibly, creates a shared standard for academic integrity, and prepares graduates for workplaces shaped by AI; although a crowded curriculum is a fair concern, a short, credit-light module applied within each discipline answers it.

Outline

• Introduction
  • Hook: students already use generative AI for brainstorming, language support, searching and summarising.
  • Background: benefits (speed, access, feedback) and concerns (inaccurate information, integrity, overdependence).
  • Thesis statement (above).
• Body paragraph 1: Critical evaluation of AI output
  • Point: students need skills to check accuracy and bias.
  • Evidence: Long and Magerko (2020); Ng et al. (2021); Kasneci et al. (2023).
  • Example: a student accepts a fabricated reference from a chatbot.
• Body paragraph 2: Academic integrity and independent thinking
  • Point: common rules and practice reduce accidental misconduct.
  • Evidence: Cotton et al. (2024); UNESCO guidance (Miao & Holmes, 2023).
  • Example: acknowledging AI assistance in a draft.
• Body paragraph 3: Workplace and civic readiness
  • Point: graduates will meet AI tools at work and in public life.
  • Evidence: Long and Magerko (2020) on competencies for work and home.
• Opposing argument and rebuttal
  • Opposing view: the curriculum is crowded and universities already issue AI guidelines.
  • Rebuttal: guidelines tell students what is allowed, not how to evaluate AI; a short module with discipline-specific tasks costs little time.
• Conclusion
  • Restate position and three reasons; end with a recommendation for module design.

Why this thesis works

Check that each body paragraph in your outline matches one reason in the thesis, in the same order. If a paragraph does not, change the thesis or the paragraph before you start drafting. Markers read the outline and thesis first, so inconsistency here costs marks early.

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Stages 2 and 3 in general terms

After the outline, the assessment generally moves to collecting and using supporting sources, then writing the full essay. Because the exact wording of these stages is set in your own brief, follow its instructions on source numbers, dates, word limits and marks. The extract below shows how Stage 1 points are developed into finished paragraphs.

Extract from the final essay

Introduction (extract)

Generative artificial intelligence has moved from novelty to everyday study tool in a few years. Undergraduates use it to brainstorm topics, polish grammar, search for literature and summarise long readings. The benefits are real, but so are the risks: invented facts, blurred authorship and a temptation to let software do the thinking. This essay agrees that Malaysian universities should introduce a compulsory AI literacy module for all undergraduates. It argues that such a module builds critical evaluation skills, sets a common integrity standard and prepares graduates for the workplace, and that concerns about curriculum space can be met by careful design.

Body paragraph (extract)

First, a compulsory module is needed because using AI well is a skill that does not develop automatically. Long and Magerko (2020) describe AI literacy as a set of competencies that lets people critically evaluate AI technologies, communicate and collaborate with them, and use them as tools. Ng et al. (2021) similarly reviewed the field and organised AI literacy around knowing and understanding AI, using it, evaluating it and attending to ethical issues. Kasneci et al. (2023) caution that large language models bring opportunities for education but also risks such as bias and overreliance, and that learners need competencies to use them critically. A first-year student who copies a chatbot’s invented citation into an essay is not necessarily dishonest; the student may simply never have been taught to verify. A short module with practical checking tasks would teach that habit to everyone, not only to students who happen to ask.

Rebuttal paragraph (extract)

Critics may argue that the undergraduate curriculum is already full and that universities have issued their own AI rules. Malaysia’s Ministry of Higher Education has reportedly provided a framework from which universities developed their own guidelines and procedures (Bernama, 2026). These policies are valuable, but they mainly tell students what is permitted. They do not teach students how to test an answer, spot bias or decide when AI weakens their own thinking, which UNESCO’s guidance treats as a human-centred concern (Miao & Holmes, 2023). The curriculum objection can be met by keeping the module short, giving it a small credit weighting, and asking students to apply it to tasks in their own field. Rules without skills leave the same gap; skills with rules close it.

Conclusion (extract)

In short, the case for a compulsory AI literacy module rests on skill, integrity and readiness. Universities should treat it as a baseline capability, much like academic writing or information skills, and design it so it does not crowd out disciplinary learning.

Looking for guidance on your own essay? Our essay writing service and OUM assignment helper pages explain how support works.

About the expert

Azura Abd Aziz holds a Master’s in Education from Universiti Kebangsaan Malaysia. Her profile lists 12 years as a teacher and 5 years providing assignment help, with education topics such as teaching methodology and curriculum development. Her profile shows 2,349 completed orders.

References

Bernama. (2026, July 22). Generative AI guidelines help universities manage technology use. The Sun. https://thesun.my/news/malaysia-news/people-issues/generative-ai-guidelines-help-universities-manage-technology-use/

Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2024). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 61(2), 228-239. https://doi.org/10.1080/14703297.2023.2190148

Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., … Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, Article 102274. https://doi.org/10.1016/j.lindif.2023.102274

Long, D., & Magerko, B. (2020). What is AI literacy? Competencies and design considerations. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (pp. 1-16). ACM. https://doi.org/10.1145/3313831.3376727

Miao, F., & Holmes, W. (2023). Guidance for generative AI in education and research. UNESCO. https://www.unesco.org/en/articles/guidance-generative-ai-education-and-research

Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2, Article 100041. https://doi.org/10.1016/j.caeai.2021.100041