sis 23(6):

Research Article

Translation Service Implementation in Cloud: Automation Trends in English Translation Industry

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  • @ARTICLE{10.4108/eetsis.3943,
        author={Qi Song and Xiang Ying Kou},
        title={Translation Service Implementation in Cloud: Automation Trends in English Translation Industry},
        journal={EAI Endorsed Transactions on Scalable Information Systems},
        volume={10},
        number={6},
        publisher={EAI},
        journal_a={SIS},
        year={2023},
        month={10},
        keywords={cloud computing, translation services, English translation, automation},
        doi={10.4108/eetsis.3943}
    }
    
  • Qi Song
    Xiang Ying Kou
    Year: 2023
    Translation Service Implementation in Cloud: Automation Trends in English Translation Industry
    SIS
    EAI
    DOI: 10.4108/eetsis.3943
Qi Song1, Xiang Ying Kou1,*
  • 1: Xi’an Traffic Engineering Institute
*Contact email: songqi-0807@163.com

Abstract

INTRODUCTION: The development of information technology has led to the renewal of teaching methods, and cloud translation combining offline and online learning has become a trend in higher education. OBJECTIVES: It is becoming increasingly apparent that the "surface issues" of blended learning are being addressed, especially the lack of consistency in online task development, which leads to inefficiencies in deep understanding. METHODS: Through literature research, the factors affecting task planning in cloud translation are analyzed, and a cloud computing task planning model is established based on task learning theory. RESULTS: The results show that task-based cloud translation can increase students' learning engagement and that targeted group task design is critical in improving students' interest and translation skills. CONCLUSION: Using complex task modeling can improve the academic level of translation students and increase their involvement in translation projects.