Research & Writing Support
File: tertiary-guide/05-research-writing.md
Research and writing are central to university study, but they do not look the same across disciplines. A literature review in nursing, a design report in engineering, a technical paper in computer science, a legal memorandum, a lab report, a business case analysis, or a critical essay in the arts all follow different conventions, expectations, and styles.
Generative AI can help you explore ideas, organise information, clarify complex material, and refine communication. However, it must never replace your own analysis, judgement, or writing. This section outlines responsible ways to use AI as a partner in academic research and writing, while keeping integrity, accuracy, and ownership at the centre.
◆ 1. Sourcing Academic Articles
Finding relevant academic sources is often one of the most challenging steps in research. AI can help by suggesting:
▸ search keywords and phrases
▸ relevant journals or publication areas
▸ possible angles for investigation
Prompt starter: “Suggest peer-reviewed articles published between 2020 and 2024 on the impact of generative AI in legal research. Provide APA-style references and a one-line summary of each.”
This can be adapted for:
▸ Healthcare & sciences: clinical studies, systematic reviews
▸ Engineering & CS: conference papers, technical journals
▸ Arts & humanities: critical theory, historical analysis
▸ Business & accounting: empirical studies, industry-focused research
✦ Reminder: AI may suggest sources that sound plausible but do not exist or are misattributed. Always verify articles through your library databases, Google Scholar, or official publisher sites before using them.
◆ 2. Summarising Academic Articles
Academic writing often assumes prior knowledge, making it difficult to access on first read. AI can help you work through challenging sections by paraphrasing, defining terms, and providing examples.
Prompt starter: “Here is a section from a journal article. Please explain it in simpler terms, highlight key theories, and give me a real-world example.”
This is particularly helpful when:
▸ interpreting statistical results
▸ understanding theoretical frameworks
▸ decoding technical language
✦ Reminder: Avoid asking AI to summarise entire articles. Nuance, methodology, and argument structure can be lost. Use AI to clarify specific sections, then re-engage with the original text.
◆ 3. Converting Text into Diagrams
Visual representations can help you understand relationships between ideas, processes, or systems. AI can assist in translating text-based explanations into diagrams or conceptual maps.
Prompt starter: “Here are three theories of motivation. Create a diagram that shows how they connect and differ.”
This approach works well for:
▸ biological or chemical pathways
▸ engineering systems and workflows
▸ software architectures
▸ theoretical models in social sciences
▸ conceptual frameworks in the humanities
✦ Reminder: Diagrams generated by AI are starting points. You should revise, annotate, or redraw them to reflect your own understanding.
◆ 4. Essay Writing Practice
Developing academic writing skill takes practice. AI can help you organise ideas, identify themes, and draft structures — without writing the essay for you.
Prompt starter: “Here is my essay question and rough notes. Please group my ideas into themes and suggest three possible topic sentences.”
This supports:
▸ clarity of argument
▸ logical flow
▸ alignment with the question
✦ Reminder: Topic sentences and outlines should inspire your thinking, not be copied verbatim. Your final writing should reflect your voice, reasoning, and disciplinary conventions.
◆ 5. Drafting and Refining Academic Writing
AI can act as a writing coach by identifying unclear phrasing, weak structure, or unsupported claims. This is especially useful when revising drafts.
Prompt starter: “Here is my draft legal memo. Please revise it for tone, structure, and clarity using the IRAC format. Flag any unsupported claims.”
This can also apply to:
▸ lab reports (clarity and precision)
▸ engineering reports (logical structure and justification)
▸ technical documentation (accuracy and conciseness)
▸ reflective writing (coherence and depth)
✦ Reminder: AI feedback is advisory. You are responsible for deciding what to change and for ensuring disciplinary accuracy.
◆ 6. Referencing and Citation Checks
Accurate referencing is essential for academic credibility. AI can help check formatting and consistency in citations and reference lists.
Prompt starter: “Act as an academic referencing assistant. I am using APA 7th edition. Check the in-text citations and reference list I paste below for accuracy and completeness.”
✦ Reminder: Always cross-check with your institution’s referencing guide. AI may miss details such as DOIs, page ranges, editions, or publication status.
◆ Responsible Use Reminder
- Never copy-paste AI outputs directly into assignments. Use them as scaffolding for your own work.
▸ Always verify references using trusted academic sources.
▸ Treat AI as a coach, not a ghostwriter. It can help you improve, but it cannot think or argue on your behalf.
▸ Check your institution’s policy on AI use in coursework — expectations vary across universities and faculties.
Before submitting, ask yourself:
▸ Does this work reflect my understanding and judgement? ▸ Could I explain and defend these ideas without AI support?
By using AI responsibly in research and writing, you can strengthen your analytical skills, develop your academic voice, and prepare for professional contexts where AI-supported drafting, reviewing, and documentation are increasingly common — but accountability remains human.