Translation Service Implementation in Cloud: Automation Trends in English Translation Industry - Song, Qi; Kou, Xiang Ying (EAI Endorsed Transactions on Scalable Information Systems, 2023)
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.