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국회도서관 홈으로 정보검색 소장정보 검색

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초록보기

This study aimed to explore the theoretical foundations of automatic item generation (AIG) methods and derive practical implications by examining the quality of English reading items automatically produced using generative language models, in order to support item writers seeking efficient development of high-quality items. To this end, open-source (Llama) and closed-source (ChatGPT) models were selected and test items were generated under four sets of conditions to compare the outcomes. These conditions specified eight variables — standard performance, item type, genre, topic, keyword, number of options, language and text length — to ensure maximal consistency between the two language models. Based on these conditions, two item types were pilot-generated for 7th- and 10th-grade students: identifying specific details and identifying mood/emotion changes. Subsequently, ten content experts evaluated the quality of the generated items. The results indicated that although test items produced by generative language models still require improvement and are not yet ready for immediate use in school settings, there was no meaningful difference in quality between the items generated by the open-source and closed-source models. These results suggest that institutions sensitive to data security may consider developing automatic generation systems based on open-source models.

권호기사

권호기사 목록 테이블로 기사명, 저자명, 페이지, 원문, 기사목차 순으로 되어있습니다.
기사명 저자명 페이지 원문 목차
다차원적 메타버스 플랫폼 기반 영어 발표 수업 = Multi-dimensional metaverse platform-based English presentation : learner factors and learning outcomes : 학습자 변인과 학습성과 하명정 p. 1-24
Analyzing linguistic gains and interaction patterns in ChatGPT-assisted L2 writing revision : a case study of adult EFL learners Myunghwan Hwang, Hee-Kyung Lee p. 25-52
Engagement with language through ChatGPT use : a systematic review Robert C. Kerr p. 53-72
Developing instructional materials for the integration of educational technology in English teaching Mee-Jee Kim p. 73-94
Personalized learning through AI : from rule-based systems to AI mentors Sangmin-Michelle Lee, Junseong Bang p. 95-114
바이브코딩을 통한 ACME 플랫폼 개발 = Integrating vibe coding into ACME : an AI-driven career, learning, and counseling platform for English education majors : 영어교육과 학생을 위한 인공지능 기반 진로·학습·상담 지원모델 연구 이혜진, 이도원 p. 115-142
영어 AI 디지털교과서에 대한 고등학생의 인식 = High school students' perceptions of English AI digital textbooks : a comparison based on English learning achievement : 영어학습 성취도에 따른 비교 이정은, 성은경 p. 143-168
패들렛(Padlet) 기반 과정 중심 쓰기 수업이 EFL 대학생의 쓰기 동기와 전략 사용에 미치는 영향 = The effects of Padlet-based process writing instruction on EFL university students' writing motivation and strategy use 이동주 p. 169-192
AI기반 영어 읽기 문항 자동 출제 방안 탐색 = Exploring AI-based automatic item generation for English reading comprehension 이문정, 이용상, 홍익현 p. 193-212
AIDT의 한국어 교육 적용 가능성 탐색 = Exploring the applicability of AIDT to Korean language education : a case review of Korean for All and recommendations : ‘모두의 한국어’의 사례 검토 및 제언 이대현, 한혜민 p. 213-233
ChatGPT의 평가와 피드백에 나타난 프레이밍 효과 = Framing effects on ChatGPT's evaluation and feedback : an exploratory mixed-methods study : 탐색적 혼합 연구 오현주 p. 234-255