  The writing examples of English language learners may be different from those
of native speakers. Given that there is a significant differences in second
language (L2) learners' error types by their proficiency levels, this paper
attempts to reduce overcorrection by examining the interaction between LLM's
performance and L2 language proficiency. Our method focuses on zero-shot and
few-shot prompting and fine-tuning models for GEC for learners of English as a
foreign language based on the different proficiency. We investigate GEC results
and find that overcorrection happens primarily in advanced language learners'
writing (proficiency C) rather than proficiency A (a beginner level) and
proficiency B (an intermediate level). Fine-tuned LLMs, and even few-shot
prompting with writing examples of English learners, actually tend to exhibit
decreased recall measures. To make our claim concrete, we conduct a
comprehensive examination of GEC outcomes and their evaluation results based on
language proficiency.
