Research on the Application of Large Language Models in College English Translation Teaching

Abstract

The rapid development of large language models is profoundly reshaping the language services industry and bringing unprecedented
opportunities and challenges to college English translation teaching. This study focuses on the application of large language models in college
English translation teaching, analyzing their contributions to innovative teaching models, enriched teaching methods, and the transformation
of teacher roles. It explores how to construct a new teaching paradigm centered on "human-machine collaboration." Research shows that large
language models, with their powerful capabilities in language generation, comprehension, and instant feedback, can effectively empower all
aspects of translation teaching, supporting personalized learning and intelligent assessment. However, their application also brings challenges
such as over-reliance on translation accuracy, academic ethical risks, and the weakening of students' critical thinking. Therefore, translation
teaching in higher education should proactively adapt by clarifying the auxiliary role of technology, innovating teaching content and methods,
strengthening the technical literacy and ethical awareness of teachers and students, and deepening industry-academia collaboration. This will
help build an innovative translation talent training system that meets the demands of the artificial intelligence era, enhancing the quality and
effectiveness of translation education.