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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4.4 Suggestions for further analysis and research

4.4 Suggestions for further analysis and research

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A large amount of data collected in the research project remained unanalysed because it fell out of the scope of the longitudinal study defined by the research questions. Thus, further correlations could be computed to shed light on how competencies and background factors are related and form a backdrop to the actual translation and post-editing performance. For example, correlations between task perception and sub-competencies could provide such insights.

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Furthermore, process data (translog files and screen-recordings) could be analysed to discover time management strategies, decision-making processes and research strategies of the participants. These data, then, could be related to the results of the present study. As indicated above, further analysis could focus on how successfully students solved the terminological problems they identified. Similarly, an analysis of the target texts from linguistic and text-linguistic perspectives, as well as in terms of the changes introduced under the post-editing condition, could yield valuable findings.

Jegyzet elhelyezéséhez, kérjük, lépj be.!

Finally, longitudinal data collected from students working with the legal text (copyright agreement) should be analysed. The results of this analysis are actually planned to be added to this paper.

Jegyzet elhelyezéséhez, kérjük, lépj be.!

As a further step in our research, it would be essential to collect data from professional translators, preferably from former students who participated in this study. This would allow for a more precise portrayal of competence development by incorporating an additional data collection wave into the longitudinal investigation.

Jegyzet elhelyezéséhez, kérjük, lépj be.!

Whereas several questions regarding translation and post-editing competence remain unexplored, future research will likely need to focus on the use of large language models (LLMs) in translation. Clearly, subcompetencies studied here and post-editing skills are relevant for LLM-based translation, too, but some additional elements like prompting, decision-making skills or the awareness of ethical issues should be included in future studies, as well.
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