Academic English revision

Plain English, Not Dumber: Methodology a 19-Year-Old Can Reproduce

Jargon is not rigor. Specificity is. If a sharp 19-year-old can't reconstruct your steps, you haven't explained them yet.

Your advisor just told you to 'rewrite the methodology so a first-year can follow it.' You felt the little crack. Six months of pilot testing, three revisions of the coding framework, a phone call with the IRB office — and now she wants it in... plain English. Your instinct is to dig in: 'But that's the point of the terminology. If I say I ran a model instead of I estimated a fixed-effects panel regression with two-way clustering, I've lost the precision that makes it rigorous.' You haven't. You've just confused specific with obscure. And that confusion is what makes your chapter read like a phone manual written by someone who hates humans.

Here's the reframe that should hit you like a cold shower: jargon is not technical accuracy. Jargon is a shortcut you took while thinking, and you left it in the draft. 'I conducted a mixed-methods study' is not a method — it's a genre. A reader can't reproduce it. 'I collected 48 semi-structured interviews (average 34 minutes) from K-12 teachers in three mid-size districts, then coded transcripts in NVivo using grounded theory (open, axial, selective) and cross-checked inter-rater reliability at 0.82 Cohen's kappa' — that's plain English with a technical spine. See the difference? Specific beats obscure every single time. That scoring tool doesn't care. Your reader does.

The rule I use, and I'm not softening this: if a sharp, curious 19-year-old who has never opened your journal can't follow your step-by-step, you haven't explained it. Not simplified. Explained. Technical accuracy means the reader can reconstruct what you did, in what order, with what tools, and why each choice was defensible. The moment a term appears and the reader has to look it up to keep going, the chain breaks. You're not dumbing it down. You're proving you understand it. 'I used a regression model' versus 'I regressed post-program test scores on the treatment indicator, controlling for baseline scores, school fixed effects, and year dummies.' The second sentence is simpler to read. It is also more rigorous.

Let's make this copyable. Three pairs from real student drafts: (1) ❌ 'A mixed-methods design was employed to triangulate findings across quantitative and qualitative data streams.' ✅ 'I ran two studies side by side: a survey of 212 students (Likert-5, 14 items) and 18 in-depth interviews (40 min each). I compared the quantitative patterns against the interview themes to check whether they pointed the same direction.' (2) ❌ 'Qualitative data were thematically analysed following the framework of Braun and Clarke (2006).' ✅ 'I read all 18 transcripts twice. On the second pass I tagged recurring phrases (e.g., I don't feel safe asking in class), grouped them into six themes, and had a second coder independently tag four transcripts. We agreed on 89% of tags; the rest we discussed and resolved.'

The third one hits closest: ❌ 'The sample was purposively selected to ensure maximum variation across demographic and experiential variables.' ✅ 'I recruited from four schools in two states. For each school I asked the department head for three teachers at different career stages (year 1, year 5, year 15+) across two content areas (math and English). That gave me 24 names; 18 agreed to interview.' Notice what happened: 'purposive sampling' didn't disappear. It became visible. The reader can now see the logic and judge whether it's defensible. That's what accuracy looks like when it stops hiding behind a phrase. Run your methodology through easydue before it goes to your advisor. Not to humanize it — to check whether every sentence actually tells the reader a specific, checkable thing. If a paragraph could be replaced by two sentences, cut it. easydue flags the spots where your technical vocabulary is doing the work a concrete example should be doing.

Here's the part nobody tells you in methodology workshops: your method section is an argument, not a recipe. Every choice — why interviews and not a survey, why 18 participants and not 12, why Cohen's kappa and not percent agreement — is a claim about rigor. When you wrap those claims in jargon, you've turned your argument into a password. Your committee, a cross-disciplinary reviewer, that one professor who'll actually read the appendix: they can't test your logic because they can't see it. Your rigor now depends on their vocabulary, not on your design. That's a vulnerability, not a flex. The moment you stop trusting the reader to follow you, you've stopped writing and started performing expertise.

So next time your advisor says 'plain English,' don't hear 'you're too smart for this.' Hear: 'Show me you understand it well enough to explain it without hiding.' The technical terms go where they earn their place — the specific test, the coding framework, the reliability metric — but the sentence around them should be one a human would say out loud to a colleague over coffee. Specific. Checkable. Reproducible. Run your final draft through easydue one last time before the committee meeting. Not to change the words. To confirm you've said it clearly. That's not less rigorous than jargon. That's the only rigor a reader can actually verify.