Application and Reflection of AI-Assisted Translation Tools in Translation Course Teaching

Meng Yuan （ Shaanxi University of International Trade & Commerce, Xianyang City, Shaanxi Province, 712046, China ）

Bai-Ru Zhao （ Shaanxi University of International Trade & Commerce, Xianyang City, Shaanxi Province, 712046, China ）

Ya-Lin Zhai （ Shaanxi University of International Trade & Commerce, Xianyang City, Shaanxi Province, 712046, China ）

Abstract

AI tools based on deep learning and neural network architectures exhibit characteristics such as high efficiency, precision, adaptability, and multimodal integration. In the curriculum, these AI tools are applied in scenarios including pre-translation preparation, draft generation, quality assessment, and strategy training, significantly enhancing both efficiency and quality. However, there are risks associated with over-reliance on technology and the potential weakening of core competencies in teaching. To address these challenges, this paper proposes optimization strategies such as balancing technological assistance with skill development, constructing a blended teaching model, enhancing teachers' technological literacy, and refining the curriculum evaluation system, thereby promoting innovation in translation education.

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