Student Performance in Machine Translation Training: Assessment and Exploration

Abstract

The present research aims to conduct a process-oriented analysis to measure whether a group of graduate students enrolled in a translation course made steady progress in their performance of identifying machine translation (MT) errors and post-editing MT drafts of company web texts and news texts. A mixed methods approach consisting of quantitative and qualitative analyses was used. The findings show that there was a steady decline in the average number of MT errors that students could not spot or correctly identify in their three assignments. However, there was no significant improvement in student MTPE performance, with only a slight decrease in errors in the final MTPE assignment, which still remained worse than the first one. Finally, student responses in their reflection essays indicated that their reception of MT and MTPE had shifted from negative denial to positive acceptance. Overall, the findings of the present study reveal the need to extend the period of MTPE training for students. Incorporating MT training into the translation course has proven to be worthwhile for students, as it helps to dispel students’ previous misconception about MT and MTPE.