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August 17, 2025Language learning & technologyOpen Access

Second language learners’ post-editing strategies for machine translation errors

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Authors

DSDongwook ShinAjou UniversityYCYuah V. ChonHanyang University

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Implication

Study examines how L2 learners correct machine translation errors using post-editing strategies, indicating a connection to proficiency.

Key Points

  • L2 proficiency significantly influences the effectiveness of post-editing strategies among learners, enhancing their writing skills.
  • Analysis of 57 students revealed common machine translation errors including mistranslation, extra words, and ungrammaticality.
  • Post-editing strategies such as grammar correction and paraphrasing were employed by L2 learners to improve machine translation output.
  • Understanding the taxonomy of MT errors aids in developing targeted training for second language learners in using AI tools.

Cite This Study

Shin et al. (2023) studied this question.

synapsesocial.com/papers/68a370e80a429f79733333behttps://doi.org/10.64152/10125/73523
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Also Consider

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  1. 1Strategically Informed Machine Translation Post-Editing: Enhancing Translation Performance among Intermediate Chinese EFL Learners2026
  2. 2Machine translation and post-editing in translator training: a systematic review of integration models, challenges, and pedagogical implications2026 · 2 citations
  3. 3The assistance role of LLMs and NMT in student translators’ Chinese–English post-editing: differences in workload, translation quality and user perception2025 · 2 citations
  4. 4A Study on Machine Translation Post-Editing Patterns of Learners Majoring in Korean at Vietnamese University2024
  5. 5Training in machine translation post-editing for foreign language students2022 · 18 citations