It is argued that Machine Translation (MT) can produce a good translation. Hence, this research p... more It is argued that Machine Translation (MT) can produce a good translation. Hence, this research project investigates the quality of MT outputs, especially Neural Machine Translation (NMT), studies the effect of MT on the learning outcome of translation students taking King Fahd School of Translation (KFST) as a case study, and compares MT as regards the accuracy of translations and productivity of translators. This research uses the results of a questionnaire that targeted 40 KFST students, and other data from a study conducted by Alsalem (2019) in the Department of English Language and Translation, College of Languages and Translation, King Saud University, in Riyadh, Saudi Arabia. The study revealed that MT’s output varies from a situation to another and cannot be deemed good or bad. The results also showed that students of KFST do not trust MT much; yet, the majority of them still use it continuously. In addition to that, the study found that MT affects the accuracy of translations but it boosts the productivity of translators. The question of whether MT affects the learning outcome of translation students negatively or positively could not be answered due to a lack in data, which is attributed essentially, unfortunately, to the unwillingness of students to participate in a qualitative study that would have been a great source to compare the translations produced by students who use MT and others who do not use it.
Keywords: Machine Translation, translation, Neural Machine Translation, King Fahd School of Translation
It is argued that Machine Translation (MT) can produce a good translation. Hence, this research p... more It is argued that Machine Translation (MT) can produce a good translation. Hence, this research project investigates the quality of MT outputs, especially Neural Machine Translation (NMT), studies the effect of MT on the learning outcome of translation students taking King Fahd School of Translation (KFST) as a case study, and compares MT as regards the accuracy of translations and productivity of translators. This research uses the results of a questionnaire that targeted 40 KFST students, and other data from a study conducted by Alsalem (2019) in the Department of English Language and Translation, College of Languages and Translation, King Saud University, in Riyadh, Saudi Arabia. The study revealed that MT’s output varies from a situation to another and cannot be deemed good or bad. The results also showed that students of KFST do not trust MT much; yet, the majority of them still use it continuously. In addition to that, the study found that MT affects the accuracy of translations but it boosts the productivity of translators. The question of whether MT affects the learning outcome of translation students negatively or positively could not be answered due to a lack in data, which is attributed essentially, unfortunately, to the unwillingness of students to participate in a qualitative study that would have been a great source to compare the translations produced by students who use MT and others who do not use it.
Keywords: Machine Translation, translation, Neural Machine Translation, King Fahd School of Translation
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Keywords: Machine Translation, translation, Neural Machine Translation, King Fahd School of Translation
Keywords: Machine Translation, translation, Neural Machine Translation, King Fahd School of Translation