Chat-GPT를 활용한 교양영어에서의 수동구문에 관한 번역 지도 방안

Abstract

This paper explores how beginner college students use Chat-GPT to translate English sentences, with a focus on passive constructions. The research examines three specific forms: the standard passive (be+past participle), the modal auxiliary verb+be + past participle, and the get+past participle construction. The theoretical framework incorporates insights from Curme (1931), Jesperson (1949), and Hageman (1985) regarding the “get” passive construction, alongside language theories from Greenbaum and Quirk (1990) and Kennedy (1991). Students are directed to utilize Chat-GPT to translate sentences based on contextual cues, particularly those involving passive constructions. The study aims to determine whether students can effectively translate sentences according to their context with the help of Chat-GPT. By integrating AI language models and established language theories, this research seeks to enhance understanding of how learners utilize contextual cues to improve their translation skills, focusing on passive voice structures. The findings are expected to contribute to the pedagogical approaches in teaching translation and language use in passive constructions.