Research Article
Translation Service Implementation in Cloud: Automation Trends in English Translation Industry
@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
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.
Copyright © 2023 Song et al., licensed to EAI. This open-access article is distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transforming, and building upon the material in any medium so long as the original work is properly cited.
