4.1 Grammar Checks and Style Consistency¶

What you will learn on this page

Practical grammar checking with generative AI
Grammar error patterns common among Japanese writers
A systematic framework for deciding English articles
Combining dedicated tools such as Grammarly and understanding their limits
How to keep style consistent across the whole manuscript
Compliance checks against your target venue’s style guide
Characteristics of AI-generated text and how to detect them

Grammar checking with AI¶

Generative AI can be very effective for grammar checking. Rather than only asking it to “fix” your English, ask it to explain why something is wrong. That makes it much more likely that you will avoid the same error next time.

Please identify problems in grammar and usage in the English below.
For each problem, provide:
- the problematic part (quote it)
- why it is problematic (brief rule explanation)
- one suggested correction (one option only)

Do not rewrite the entire text.

[Paste English here]

Grammar errors common among Japanese writers¶

Below is a systematic list of errors that are especially common in academic English written by Japanese speakers.

Category	Common error	Correct form	Likely cause
Articles	❌ In experiment, we...	In the experiment, we...	Refers to a specific experiment, so the is needed
Articles	❌ The education is important.	Education is important.	General statements often take no article
Countable/uncountable	❌ researches, informations, evidences	research, information, evidence	Incorrect pluralization of uncountable nouns
Subject–verb agreement	❌ The number of participants were...	The number of participants was...	the number of is treated as singular
Unnecessary prepositions	❌ discuss about, approach to (as a verb)	discuss X, approach X	Transfer from Japanese “〜について”
Relative clauses	❌ The method which was used it...	The method that was used...	Double use of relative pronoun and pronoun
There-construction	❌ There are many researches exist.	There are many studies. / Many studies exist.	Mixing “there is/are” with a regular verb clause
Noun strings	❌ student questionnaire result analysis	analysis of questionnaire results from students	Long noun strings reduce readability

Prompt: detect Japan-specific error patterns

Please check the English below, focusing only on grammar errors that are common among Japanese writers.

Focus items:
(1) Articles (a/the/zero article)
(2) Countable vs uncountable nouns
(3) Unnecessary prepositions
(4) Subject–verb agreement
(5) Overlong noun strings (noun + noun + noun ...)

For each issue:
- quote the problematic part
- provide the correct form
- explain in one line which Japanese thinking pattern likely caused it

[Paste English here]

A framework for deciding articles¶

Articles are often the hardest part for Japanese writers. The step-by-step procedure below helps you decide systematically.

Step 1: Is the noun countable or uncountable?

Uncountable (research, information, evidence, knowledge, etc.) → usually zero article or the
Countable → go to Step 2

Step 2: Does it refer to a specific item that the reader can identify?

Specific (the reader can identify “which one”) → the
Not specific (first mention, one general instance) → a/an

Step 3: Is it used as a general statement (generic reference)?

Generic → plural, zero article (Students need feedback.)
A specific group → the + plural (The students in this study...)

Common article patterns in academic writing

Expression	Article	Reason
the present study	the	the study in this paper is specific
a questionnaire (first mention)	a	first mention
the questionnaire (later)	the	already mentioned
in Table 1	zero	treated like a proper label
language learning (generic concept)	zero	general concept
the results	the	results of the present study are specific

Prompt: focused article check

Please check all uses of articles (a, the, zero article) in the English below.

For each article decision:
- mark it as correct (OK) or incorrect (NG)
- if NG, provide the correct article and a short reason (e.g., 'specific reference → the')

Ignore other grammar issues.

[Paste English here]

Combining dedicated tools¶

Using dedicated grammar tools in addition to AI can be very effective.

Tool	Key feature	Best for
ChatGPT / Claude / Gemini	Context-aware explanations, flexible interaction	Understanding why something is wrong
Grammarly	Real-time checking, browser extension	Grammar and spelling while drafting
DeepL Write	Natural rewrites and corrections	Polishing English after translation
QuillBot	Rewriting plus grammar checks	Improving readability via paraphrases
ProWritingAid	Style analytics, repetition detection	Revision and style consistency
LanguageTool	Open source, multilingual	Privacy-conscious proofreading

A practical two-step tool workflow

First, use Grammarly and similar tools to remove mechanical errors. Then use AI to check context-dependent issues such as tense consistency and appropriate hedging. No single tool is perfect, so it helps to learn each tool’s strengths and limits.

Do not overtrust tools

All tools can produce false positives and miss real errors. Make the final decision yourself. If you accept all suggestions uncritically, you can introduce changes that conflict with academic conventions in your field.

A staged approach to grammar checking¶

Generative AI is also useful as a final check for proofreading and detecting typos that word processors can miss. The three-stage workflow below reduces errors efficiently.

Stage 1: Mechanical errors (use tools)¶

Use Grammarly and similar tools, or AI, to detect spelling, punctuation, and obvious grammar errors.

Please proofread the English below and identify typos and formatting issues.

Checklist:
(1) spelling mistakes (especially ones word processors miss)
(2) punctuation issues (comma, period, semicolon)
(3) capitalization errors
(4) spacing issues (double spaces, missing spaces)
(5) confusable words (e.g., affect/effect, then/than, its/it's)

For each issue:
- quote the problematic part
- provide a correction
- if relevant, explain why word processors often miss it

[Paste English here]

Stage 2: Context-dependent issues (use AI)¶

Please check the English below as a [SECTION NAME] section of an academic paper,
focusing on context-dependent grammar and usage issues.

Checklist:
(1) tense appropriateness (consistent with [SECTION NAME] conventions)
(2) article usage (a/the/zero article)
(3) hedging strength (too much or too little)
(4) distance between subject and verb (overlong subjects)

Ignore mechanical errors such as spelling and punctuation.

[Paste English here]

Stage 3: Field-specific conventions (confirm yourself)¶

Some field-specific conventions are difficult for tools and AI to evaluate. Confirm these yourself.

Read 2–3 recent papers in top venues in your field and compare expression choices
If possible, ask senior colleagues for a check

How to keep style consistent¶

Style consistency becomes especially important when you write over multiple sessions.

What to check¶

Spelling: American vs British (e.g., analyze vs analyse)
Abbreviations: define at first mention, then use only the abbreviation
Numbers: spelling out rules (e.g., three participants), venue dependent
Citation style: APA, IEEE, Vancouver, etc.
Terminology: consistent terms for the same concept

Please identify style inconsistencies across the manuscript below.

Check items:
- spelling variants (US/UK mixing)
- abbreviation first-mention rule
- number formatting
- inconsistent terminology

For each item, quote the inconsistent parts and propose one consistent choice.

[Paste manuscript or target sections]

Create a style sheet¶

Creating a simple “style sheet” before drafting helps prevent drift.

Example style sheet

# Manuscript style sheet

## Core settings
- Spelling: American English
- Citation style: APA 7th
- Numbers: spell out under 10 (except statistics and measurements)

## Terminology
- L2 learners (avoid mixing with EFL learners / second language learners)
- generative AI (avoid mixing with GenAI / gen AI / LLM)
- vocabulary knowledge (avoid mixing with lexical knowledge)

## Abbreviations
- CALL: Computer-Assisted Language Learning (defined at first mention)
- RQ: Research Question (defined at first mention)
- AI: widely known, no definition needed

## Other
- serial comma: use (A, B, and C)
- figures: Figure 1, Figure 2... (avoid Fig.)
- tables: Table 1, Table 2...

Check compliance with your target venue’s style guide¶

Many venues have strict Author Guidelines. Violations can lead to desk rejection.

Typical items to confirm:

Item	What to check	Common mistakes
Word limits	Abstract, main text, inclusion of figures/tables	Abstract exceeds limit
Reference style	APA, IEEE, Vancouver, Harvard, etc.	mixed styles
Figure/table specs	resolution, format, color rules	low-resolution figures
Required sections	e.g., Data Availability	missing section
Anonymization	blind review requirements	self-identifying info left in text
AI-use disclosure	required / recommended / not needed	missing disclosure

Prompt: compliance check against a style guide

Based on the target venue requirements below, check whether my manuscript meets them.

Venue requirements:
- reference style: [APA 7 / IEEE / other]
- word limits: Abstract <= [X], main text <= [X]
- anonymization: [required / not required]
- AI-use disclosure: [required / recommended / not required]
- required sections: [e.g., Data Availability Statement]

Check:
(1) word counts
(2) reference format
(3) anonymization issues (self-citations revealing identity)
(4) required sections
(5) AI-use disclosure

[Paste manuscript]

Characteristics of AI-generated text and detection¶

To evaluate AI outputs critically, it helps to know common patterns in AI-generated writing. For detector limits and ethical self-management, see
1.2 Academic Integrity and Plagiarism Prevention.
Here, we focus on stylistic characteristics and practical ways to check your own draft.

Common characteristics of AI-generated text¶

Pattern	Example	Practical fix
Safe, middle-of-the-road claims	“This is an important area that deserves further attention.”	Replace with a concrete claim grounded in your data
Overuse of stock connectors	Repeated “Furthermore, … Moreover, … Additionally, …”	Remove redundant connectors and rely on logic
Over-hedging	“It may potentially suggest that there could be …”	Reduce to one hedge per sentence where possible
Lack of specificity	“Several studies have shown …” with no citation	Add author-year citations yourself
Uniform sentence length	Many sentences of similar length	Mix short and longer sentences intentionally
Unnecessary intensifiers	“remarkably,” “crucially,” “it is worth noting that”	Remove unless strongly justified

Expressions AI tends to overuse¶

See also the discussion in
1.2 Academic Integrity and Plagiarism Prevention.

Expression	Better alternatives
delve into	examine, investigate, explore
complex / overly “subtle” adjectives	use the simplest accurate descriptor
It is worth noting that	remove and state directly
plays a crucial role	is important for, contributes to
a better understanding	keep it concrete (what becomes clearer?)
shed light on	clarify, reveal, explain
within the field of	in / in research on
promote/support/encourage	choose the most precise verb
highlights	shows, demonstrates (if evidence is strong)

Prompt: detect AI-like style patterns

Please check whether the English below has stylistic characteristics typical of AI-generated writing.

Checklist:
(1) excessive use of stock connectors
(2) over-hedging (multiple hedges in one sentence)
(3) generic claims without specificity
(4) unnecessary intensifiers (remarkably, crucially, notably, etc.)
(5) overly uniform sentence length

Quote the problematic parts and suggest revision directions (no full rewrite).

[Paste English here]

Do not overfocus on 'AI-likeness'

Many of these expressions existed in academic writing before AI tools became common. If you chose an expression intentionally, you do not need to remove it. The issue is when these expressions become unusually concentrated due to accepting AI output without review.

Comparing and combining multiple AI models¶

Different models have different tendencies, and even the same model can vary across runs. Comparing outputs can be useful.

Purpose	Practical approach
Japanese → English conversion	Compare outputs and choose the most natural one
Grammar and usage checks	Check with one model, then double-check with another
Structure diagnosis	Use a stronger reasoning model
Phrase options	Collect options from multiple models for variety
Statistical code generation	Use a code-strong model and always test and verify

Model comparisons change over time

Models are updated frequently. Rather than depending on one model, keep the habit of making the final decision yourself.

AI proofreading vs. human editing¶

Has AI made human editing unnecessary? The answer is both yes and no.

AI may be enough: if you have extensive experience writing papers in your field and can judge correctness reliably
Human editing is helpful: if you are not confident in your ability to evaluate AI suggestions, or your field requires highly specialized phrasing

AI is an augmentation tool (see 3.1). If your baseline ability to judge language is low, the benefit is limited. Human editors can also help with whole-manuscript balance and venue-specific formatting, which AI often handles poorly.