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Post-editing machine translation often results in discrepancies between industry expectations and the actual quality of the final product. Despite the usually, low-quality outcomes associated with machine translation, it remains underutilized, even when there are opportunities for improvement through post-editing jobs. This study focuses on the impact of technology-assisted training on English proficiency among students. It investigates a standard error observed among Iraqi students during the post-editing of machine translations using Google Translate deciding whether to edit the machine translation output or to translate from scratch and understand the source text. This research involved 20 undergraduates from Al-Mustansiriyah University and employed a mixed methods approach, collecting data through an online questionnaire completed by students in the undergraduate translation program. The findings indicate a significant improvement in the frequency of post-editing skills among Iraqi students, serving as a distinguishing factor between the two groups. It also highlighted differences in translation abilities among students in Iraqi higher education, with notable improvements observed in the experimental group. In summary, this study supports previous research from the last five years, indicating a more favourable attitude toward machine translation and suggesting that post-editing is considered an essential sub-competency in translation education.
Sammarraie et al. (Fri,) studied this question.