Paper Status Tracking
Contact us
customer@davidpublishing.com
Click here to send a message to me 3275638434
Paper Publishing WeChat

Article
Affiliation(s)

Shanxi Vocational University of Culture and Tourism, Taiyuan, China

ABSTRACT

Against the backdrop of the rapid advancement of AI (artificial intelligence) technology permeating the language services industry and human-machine collaboration emerging as a prevailing trend in translation, traditional translation pedagogy centered on linguistic proficiency is at the risk of detaching from industry demands. In light of the philosophy of the New Liberal Arts, which advocates interdisciplinary integration and convergence of technology and the humanities, this study proposes a “Four Integrations” translation teaching model. This model comprises the integration of AI technology with translation pedagogy, blended learning (online and offline), theoretical instruction plus industry-academia collaboration, and translation competency plus cultural literacy. By constantly optimizing the curriculum system and innovating teaching modalities, this model incorporates the cultivation of human-machine collaboration capabilities into the entire process of translation education.

KEYWORDS

human-machine collaboration, New Liberal Arts, Four-Pronged Integration, translation pedagogy in higher education institutions

Cite this paper

ZHOU Yuhong. (2026). Human-Machine Collaboration: Paths and Strategies for Cultivating Competent Language Translation Talents. US-China Education Review A, April 2026, Vol. 16, No. 4, 203-209.


References

China Translators Association. (2025). Guidelines for Generative AI applications in the translation industry (2025). Beijing: China Translators Association.

CSA Research. (2023). Global language services industry report 2023. USA: CSA Research.

Lee, J., Lim, C., & Kim, H. (2017). Development of an instructional design model for flipped learning in higher education. Educational Technology Research and Development, 65(2), 427-453.

Sichuan International Studies University. (2024). Research on advanced simultaneous interpretation talent cultivation models for the AI era. Chongqing: Chongqing Municipal Education Teaching Reform Project Report.

Sun, F. J., Wang, B. L., & Li, W. (2023). Translation system based on cross-language dual-space alignment and genealogy guidance. Chinese Patent: CN202310245678.9.

Yan, M. (2015). Construction of a business English talent cultivation model aligning “Curriculum-Teaching-Evaluation”. Foreign Language Research, 38(5), 95-98.

Yang, Y. X., & Wei, X. Q. (2024). The essence and cultivation pathways of human-machine collaborative translation literacy. China Translator, 45(2), 58-65.

About | Terms & Conditions | Issue | Privacy | Contact us
Copyright © 2001 - David Publishing Company All rights reserved, www.davidpublisher.com
3 Germay Dr., Unit 4 #4651, Wilmington DE 19804; Tel: 001-302-3943358 Email: order@davidpublishing.com