准确但自然？诊断日本英语作为外语写作中的语法与习语差距
Accurate but Natural? Diagnosing Grammatical and Idiomatic Gaps in Japanese EFL Writing
- Kyoto University（京都大学）
- Ritsumeikan University（立命馆大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本研究提出分层LLM修正流水线，结合CEFR-J语法提取器，诊断日本初中生英语写作的语法准确性与习语性差距，为个性化教学反馈提供循证支持。
AI中文摘要：
二语写作研究将语法准确性与母语式习语性区分开来，但自动写作评估常混淆这两个维度。本研究提出一种分层大语言模型（LLM）修正流水线，通过为120名日本初中生的3830份英语写作样本生成字面错误修正与习语修订，将结构错误与不自然表达隔离开来。应用基于正则表达式的CEFR-J语法提取器，我们量化两项诊断指标：准确性差距（尝试使用但生成错误的结构）与习语差距（相对于母语规范，语法正确的结构使用不足或过度使用）。结果显示出不同模式：定冠词、第三人称单数-s、情态动词（would、could）存在显著准确性困难，而-ing形式与假设情态动词（would）表现出最大的习语使用不足，反之，一般现在时动词、主谓宾结构与情态动词can则表现出最明显的过度使用。一种二维教学类型学将错误率与习语差距对应，区分出准确但过度使用的语法项、易出错或需针对性产出练习的回避性复杂形式。该框架通过使教师诊断学习者困难源于不准确执行、结构回避还是母语（L1）映射的过度依赖，为个性化学习者需求的循证干预提供支持，从而推进教学反馈。
英文摘要：
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.
