# Accurate but Natural? Diagnosing Grammatical and Idiomatic Gaps in Japanese EFL Writing

arXiv: https://arxiv.org/abs/2608.09289 · HTML: https://mlsanity.com/paper/2608.09289/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 6 of its 29 references that are in the map.
- First posted on arXiv 10 Aug 2026.

## Builds on (most cited first, 6 of 6)

- [Is ChatGPT a Highly Fluent Grammatical Error Correction System? A Comprehensive Evaluation](https://mlsanity.com/paper/2304.01746/) (2023)
- [ChatGPT or Grammarly? Evaluating ChatGPT on Grammatical Error Correction Benchmark](https://mlsanity.com/paper/2303.13648/) (2023)
- [Evaluating Prompting Strategies for Grammatical Error Correction Based on Language Proficiency](https://mlsanity.com/paper/2402.15930/) (2024)
- [Analyzing the Performance of GPT-3.5 and GPT-4 in Grammatical Error Correction](https://mlsanity.com/paper/2303.14342/) (2023)
- [Multi-Dimensional Evaluation of LLMs for Grammatical Error Correction](https://mlsanity.com/paper/2605.07635/) (2026)
- [Penny: Transition Network Analysis of Learner-Chatbot Interactions in Scaffolded EFL Writing](https://mlsanity.com/paper/2607.14575/) (2026)

## Abstract (arXiv)

Second language writing research distinguishes grammatical accuracy from native-like idiomaticity, yet automated writing evaluation often conflates these dimensions. This study introduces a layered LLM-correction pipeline that isolates structural errors from unnaturalness by generating literal error corrections and idiomatic revisions for 3,830 English writing samples from 120 Japanese junior high school students. Applying the regex-based CEFR-J grammar extractor, we quantify two diagnostic measures: accuracy gaps (structures attempted but incorrectly produced) and idiomatic gaps (grammatically correct structures underused or overused relative to native norms). Results reveal distinct patterns: definite articles, third-person singular -s, and modals (would, could) exhibit significant accuracy difficulties, while -ing forms and hypothetical modals (would) show the largest idiomatic underuse, with simple present verbs, subject-verb-object patterns, and modal can conversely exhibiting the most pronounced overuse. A two-dimensional instructional typology maps error rates against idiomatic gaps, distinguishing accurate but overused grammar items from error-prone or avoided complex forms requiring targeted production practice. This framework advances pedagogical feedback by enabling teachers to diagnose whether learner difficulties arise from inaccurate execution, structural avoidance, or L1-mapped overreliance, supporting evidence-based interventions tailored to the specific needs of each learner.