Earticle

초록

영어

This study aims to investigate the feasibility of TalkTrack, a hybrid feedback platform designed to enhance interpreter training by leveraging the crucial role of feedback. TalkTrack automatically detects disfluencies in interpreting and visualizes them, thereby providing immediate feedback to learners. In addition to AI-generated feedback, the platform allows instructors to offer qualitative evaluations, thereby enabling more detailed and comprehensive feedback. To assess the platform's feasibility, usability experiments were conducted with instructors and students from a graduate school of interpretation and translation. The findings indicate that users responded positively in terms of functional adequacy, overall satisfaction, and educational effectiveness, suggesting that the platform successfully met its intended objectives. The results of this study confirm that a hybrid feedback system can serve as an effective tool for enhancing both the quality and quantity of feedback in interpreter training. With continuous improvements, TalkTrack is expected to evolve into a technology-enhanced learning (TEL) tool that facilitates interaction between instructors and learners in interpreter education.

목차

1. 서론
2. 이론적 배경
2.1. 맞춤형 피드백
2.2. 자동 피드백 활용 가능성
3. 하이브리드 피드백 플랫폼 - 토크트랙
3.1. 하이브리드 피드백 플랫폼 개요
3.2. 플랫폼의 하이브리드 피드백 기능
3.1.1. 자동 피드백 기능
3.1.2. 수동 피드백 기능
3.1.3. 피드백 결과 확인 기능
4. 하이브리드 피드백의 사용성 실험
4.1. 실험 참여자 속성
4.2. 실험 진행 절차
5. 실험 결과 분석
5.1. 플랫폼 기능 (통역 교수자 vs 통역 학습자)
5.2. 피드백에 대한 신뢰도 (통역 교수자 vs 통역 학습자)
5.3. 플랫폼에 대한 만족도
5.3.1. 통역 교수자 vs 통역 학습자
5.3.2 통역 전공 vs 번역 전공
5.3.3 기타 요구 사항
6. 논의 및 결론
참고문헌

저자

• 상우연 [ Sang, Wooyeon | 이화여자대학교 ]
• 이주리애 [ Ju Ri Ae Lee | 이화여자대학교 ]
• 김세연 [ Kim Saeyeon | 이화여자대학교 ]
• 박혜경 [ Hae Kyung Park | 이화여자대학교 ]
• 손지봉 [ Ji-Bong Son | 이화여자대학교 ]

참고문헌