Earticle

초록

영어

In undergraduate interpreter training, students are more likely to encounter bilateral interpreting between two working languages than conference interpreting, either during their studies or future careers. However, dialogue interpreting classes often present challenges due to students' limited linguistic competence and lack of subject knowledge. To address these difficulties, this study explores how students use generative AI to create dialogue scripts for interpreting practice, focusing on prompt literacy, AI-generated text features, and learners' perceptions. Students worked in small groups to generate weekly dialogue scripts on assigned topics using ChatGPT. These scripts were then enacted in class as role-plays, with each student taking a participant's role. Spontaneous interpreting was performed by other students selected by the instructor. Each group submitted full logs of their prompts and AI-generated outputs weekly and completed a survey at the end of the semester. The findings indicate that students' prompting strategies generally aligned with expert techniques and improved over time. The generated scripts proved suitable as source texts for interpreting exercises, requiring only minor revisions. Furthermore, the dialogues displayed a strong sense of realismand authenticity, enhancing learner immersion and engagement. Overall, students responded positively to the use of ChatGPT in script preparation. This study highlights the pedagogical potential of generative AI in undergraduate interpreter education.

목차

Abstract
I. 들어가는 말
II. 이론적 배경
1. 생성형 AI와 통역 교육
2. 프롬프트 리터러시(Prompt Literacy)
III. 연구방법
1. 학습자 프로필
2. 수업 운영
3. 데이터 분석과 연구 질문
IV. 분석결과
1. 학습자들이 사용한 프롬프트 전략: 유형과 개선사항
2. 생성 대화문의 특징
3. 챗GPT 사용 경험에 대한 학습자 인식
IV. 나가는 말
참고문헌
부록

키워드

저자

• 신나정 [ Shin, Najung | 한국외국어대학교 ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  통역과 번역 [Interpretation and Translation]

• 간기

  연3회

• pISSN

  1229-6074

• 수록기간

  1999~2025

• 등재여부

  KCI 등재

• 십진분류

  KDC 717 DDC 400