Márta Lesznyák: A longitudinal investigation of translation trainees’ translation and post-editing competence development I
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4 Summary and conclusions
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4.2 Implications for training

4.2 Implications for training

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Our findings have implications for training. As it is very likely that MT, AI-assisted translation and post-editing will dominate the language industry in the near future, we will focus on suggestions for training post-editing.

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One area that emerged repeatedly as a challenge was terminology. Terminology error numbers grew significantly between the two data collection waves; students often could not make a distinction between terms and everyday vocabulary, and lastly, terminology errors were also related to a number of task perception indicators.

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These findings imply that students should be made aware of the limitations of MT, particularly its challenges in handling terminology. They should be explicitly warned against over-reliance on MT in general, and on the terms it offers, in particular. This should be paralleled by targeted practical activities, where students analyse MT-generated texts for terminological errors and inconsistencies. Additionally, special emphasis should be placed on developing their ability to distinguish between terms and non-terms.

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It was shown that beliefs about translation are key sub-competencies in both translation and post-editing. It can be hypothesised that beliefs about post-editing are equally important, although they were not assessed in the research. Nevertheless, it can be recommended that theoretical and practical knowledge about post-editing is integrated into translation training to prevent the formation of possible misconceptions and misrepresentations. This knowledge may lead to the formation of a more favourable belief system on post-editing. On the basis of our findings, specific topics that should be covered include accuracy issues in MT, temporal, technical and cognitive effort needed to produce high-quality post-edited texts.

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A striking finding is some students’ inability to decide whether MT output is acceptable or not, particularly as this is associated with lower performance. The underlying causes of this problem may be multifaceted. The most straightforward explanation is that students require extensive practice in assessing MT-generated translations. While this may be true, it cannot be ruled out that additional experience in traditional translation could also be beneficial. By producing their own translations, students may develop a deeper understanding of what constitutes an acceptable or unacceptable translation. Lastly, it is important to acknowledge that deficiencies in language competence may contribute to students being indecisive, suggesting that further language skills development could facilitate more effective post-editing decisions.
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