This study aims to develop and evaluate a GPT-based English learning system that creates reading materials tailored to the Korean middle school first-grade English curriculum. To this end, this study adopted OpenAI’s MyGPTs platform and created the AI system through eight different developmental versions by iterating prompts and uploading relevant knowledge files. To evaluate its linguistic appropriateness, this study generated reading passages at three difficulty levels (low, medium, high) and compared them with eight textbook texts using seventeen key indices from Coh-Metrix 3. The results show that GPT-generated texts at the medium level most closely resembled actual textbook passages in sentence count, syntactic simplicity, lexical familiarity, and overall readability. Low-level outputs achieved the highest readability and concreteness scores, indicating suitability for beginner EFL learners, while high-level outputs featured greater syntactic complexity, longer sentences, and richer lexical diversity. The study also identified limitations in GPT’s consistent adherence to prescribed difficulty parameters, text-type variety, and adaptive difficulty adjustment based on learner performance.

1. 서론
2. 이론적 배경
    2.1. EFL 학습자를 위한 맞춤형 영어 읽기 자료의 필요성
    2.2. 생성형 AI 기반의 읽기 자료 제작 및 활용 사전 연구
    2.3. 맞춤형 텍스트 생성을 위한 난이도 분석 도구와 지표
3. 연구 방법
    3.1. GPT 모델 개발 과정
    3.2. 유사성 분석 및 언어 특성 평가 지표
4. 결과 및 논의
6. 결론 및 시사점
REFERENCES

• 이상민(Professor, Department of Metaverse, Kyung Hee University) | Sangmin-Michelle Lee
• 황요한(Associate Professor, Department of English Language and Literature, Jeonbuk National University, 567 Baekje-daero, Deokjin-gu, Jeonju-si, Jeollabuk-do 54896, South Korea) | Yohan Hwang Corresponding author