Research Skills and Academic Writing
Research Skills and Academic Writing
This course teaches one complete workflow:
Ask a bounded question, find and judge evidence, make only the claim that the design can support, and leave a traceable record of every decision.
It is suitable for undergraduate projects and as a methods refresher for taught postgraduate or early doctoral work. The examples are short; the standards are not.
What you will be able to do
By the end, you should be able to:
- turn a broad topic into a feasible, answerable research question;
- search transparently and explain why each source was included;
- distinguish a source's finding from your interpretation of it;
- synthesise agreement, disagreement, mechanism, context, and uncertainty;
- align a question with a design and calibrate the strength of the claim;
- build paragraphs in which evidence actually supports the claim;
- cite, paraphrase, and use AI without breaking source traceability;
- revise a paper through an auditable sequence of decisions.
One case across the whole course
Every chapter returns to the same case:
Does structured peer feedback improve the quality of research abstracts written by first-year undergraduates in a six-week methods module?
This question is useful because it contains a treatment, an outcome, a population, and a setting—but still leaves design choices open.
| Choice | Example | Consequence |
|---|---|---|
| Outcome | rubric score for argument, method, and clarity | “Quality” becomes measurable |
| Comparison | structured feedback versus usual comments | supports a comparative claim |
| Timing | draft and final abstract | permits change to be observed |
| Assignment | random or existing seminar groups | changes causal credibility |
| Context | one institution, one module | limits generalisation |
The case is grounded in an active research area. A 2024 systematic review found both reported benefits and recurring implementation challenges across 60 studies of peer feedback in higher-education writing; it also noted that much of the evidence concerned undergraduates and was qualitative (Wei & Liu, 2024). That is enough to motivate a study—not enough to predetermine its result.
Course structure
Core sequence
| Module | Central question | Your output |
|---|---|---|
| 1. Question and scope | What exactly can this project answer? | question + scope box |
| 2. Search, evaluate, and read | Which evidence deserves attention? | search log + source card |
| 3. Synthesis and argument | What does the evidence mean together? | matrix + argument map |
| 4. Literature review and gap | What is known, uncertain, and worth studying? | question-chain outline |
| 5. Design and evidence | What can the method justify? | design-alignment table |
| 6. Citation, integrity, and AI | Can every important claim be traced? | verified claim record |
| 7. Revision and submission | Will a sceptical reader follow and trust the paper? | revision audit |
Practice studios
| Studio | Use it when... |
|---|---|
| 8. Course workbook | you need copyable templates for each research decision |
| 9. Research workflow and tools | files, notes, citations, or versions are becoming hard to control |
| 10. Worked project | you want to see the full chain from question to defensible conclusion |
An eight-session teaching route
The course works as eight 75–90 minute seminars or as self-study units.
| Session | Before class | In class | Evidence of learning |
|---|---|---|---|
| 1 | bring a broad topic | question clinic | feasible question |
| 2 | find five candidate sources | search-and-screen lab | search log |
| 3 | read three sources | source autopsy | evidence matrix |
| 4 | draft topic headings | block-to-question conversion | review outline |
| 5 | propose a method | claim–design hearing | design table |
| 6 | bring one evidence paragraph | traceability audit | revised paragraph |
| 7 | exchange drafts | structured peer review | revision memo |
| 8 | submit decision records | five-minute defence | final research pack |
For self-study, replace peer discussion with a written answer to: “What evidence would make me change this decision?”
Undergraduate and postgraduate routes
| Route | Minimum standard | Extension |
|---|---|---|
| Undergraduate | one bounded question; reasoned source selection; claim–evidence fit | compare two plausible explanations |
| Postgraduate | explicit search and exclusion logic; design limitations; alternative interpretation | justify boundary conditions, robustness checks, and contribution |
Both routes use the same chapters. Depth comes from the quality of decisions, not from adding more headings.
The four-part test used throughout
Every substantial paragraph should survive four questions:
| Part | Test | Weak signal |
|---|---|---|
| Claim | What am I asking the reader to accept? | only a topic is named |
| Evidence | What observation or source supports it? | a citation is attached but not explained |
| Warrant | Why does that evidence support this claim? | the logical step is hidden |
| Limit | Where might the claim fail? | the wording is universal |
Short form: C–E–W–L. You will use it for literature synthesis, methods, results, and conclusions.
Research standards behind the course
This course uses four evidence-based practices:
- transparent review decisions: PRISMA 2020 shows why search, screening, and inclusion decisions must be reportable in systematic reviews (Page et al., 2021);
- lateral source checking: expert fact-checkers leave a page to investigate its author, organisation, and independent coverage (Wineburg & McGrew, 2019);
- human responsibility for AI-assisted work: AI can create an illusion of understanding while narrowing questions and viewpoints (Messeri & Crockett, 2024);
- draft–feedback–revision as observable research practice: the 2026 Exposía dataset links student proposals, peer/instructor feedback, revisions, and criterion-level ratings; expert-content criteria remained harder for models to assess (Zyska et al., 2026).
These sources do not prescribe one universal method. They justify the course's emphasis on transparency, verification, and visible revision.
Start here
Write your topic in five words. Then open Module 1 and turn those words into a question that a real project can answer.