ScholarWorks@숙명여자대학교

초록

This study investigated the integration of machine translation (MT) and artificial intelligence (AI) into undergraduate translation education, focusing on how these tools support translation competence and language skill development through a social constructivist approach. Conducted in a Chinese-Korean translation class, the research analyzed how students improved their translation abilities using a collaborative machine-human model. Students utilized Papago and ChatGPT as key tools in their translation tasks, enhancing vocabulary, grammar, and sentence structure skills while developing cultural knowledge and translation competence. Team-based learning and classroom discussions played a crucial role in helping students refine machine-generated translations and acquire effective strategies. ChatGPT provided immediate feedback, fostering an interactive learning dynamic that boosted confidence and motivation. The findings highlight that integrating MT and AI into undergraduate courses can significantly improve translation quality and collaborative learning. This approach supports both individual skill-building and collective growth, demonstrating the potential of combining technological advancements with traditional translation education.

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