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Investigating the Effect of AI Literacy on the Quality of Technical Translation

Linguistics / 2025,7(2): 150-164 / 2025-06-25 7 5

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• Authors: Ke Xu Wenhui Tang Zhuangyuan Tian Qianhui Luan Leiyu Shi
• Information:

  1. School of Humanities, Beijing University of Posts and Telecommunications, Beijing;
  2. School of Foreign Studies, Chang’an University, Xi’an

• Keywords:
  AI literacy; instrumental competence; technical translation
• Abstract: Artificial Intelligence (AI) is increasingly seen as a collaborator for translators. However, there is a lack of empirical evidence on whether AI literacy can predict the quality of English-Chinese scientific translations. This mixed-methods study investigates how AI literacy influences the quality of scientific translation, with a focus on its impact on terminology accuracy, fluency, and stylistic coherence. The experiment involved student translators (n=29) who major in translation instead of computer science, translating two texts on computer science with high and low text complexity. Participants could choose whether to use AI at their own free will. Their AI literacy is quantified by the time spent on AI tools, usage frequency, and the number of AI tools used. Quantitative data is corroborated by the Think-Aloud Protocol (Jääskeläinen, 2000) and the postexperiment interviews. The quality is assessed using Multidimensional Quality Metrics (MQM) (Lommel et al., 2014) by two qualified raters. Our findings show that 1) AI literacy significantly increases the quality of the conceptual scientific passage, but not on the operational scientific passage; 2) student translators with high AI literacy perceive AI as an indispensable tool for high-quality scientific translation, while participants with low AI literacy show distrust. Ultimately, we concluded that AI can serve as an effective tool supplementing the translator’s lack of domain knowledge. Nevertheless, the translators’ competence in bilingual knowledge remains of paramount importance in producing accurate, fluent, and stylistically coherent scientific texts. Therefore, we recommend that AI literacy be incorporated into the technical sub-competence of the current mainstream translation competence models.
• DOI: https://doi.org/10.35534/lin.0702015 Research/ Funding
• Cite: Xu, K., Tang, W. H., Tian, Z. Y., Luan, Q. H., & Shi, L. Y. (2025). Investigating the Effect of AI Literacy on the Quality of Technical Translation. Linguistics, 7(2), 150-164.