Using Machine Translation Error Identification to Improve Translation Students’ Post-Editing Skills

Attempts to investigate challenges facing translation students in post-editing remain limited literature. This research investigates a common challenge observed during training using SDL Trados 2021 which is deciding whether post-edit MT output or translate from scratch. Making such decisions by may need more focused procedures and criteria improve this decision-making capability. The current suggests integrating error identification proposed Daems J, Vandepitte S, Hartsuiker RJ Macken L (2016) as basic criterion undertake process tested its effects on improving their performance regarding decision making time consumed. A quasi- experimental approach was adopted, the experiment applied thirty (30) at university level divided into control group an group. pre-test given both groups identify consumed process. techniques Statistical types were introduced five-day workshop task-based instruct received traditional with no focus types. post-test administered test improvement skills. findings showed significant students’ would contribute enhancing courses provided cope continuous advancement technologies market needs.