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September 27, 2025Open Access

Team dynamics and efficiency in post-editing: Machine translation systems versus artificial intelligence chatbots under tight deadline conditions

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Mixed-methods analysis compares post-editing efficiency in translating machine and AI outputs, suggesting insights for translator training.

Team dynamics impacted the efficiency of post-editing, stressing the importance of communication under tight deadlines.
Quantitative metrics revealed that Team 1 spent 60 minutes correcting 19 errors compared to Team 2's 48 minutes and 12 errors.
Qualitative insights highlighted stress levels that affected teamwork and decision-making during the post-editing process.
Both teams tended to prioritize speed over quality, suggesting a need for improved training on terminology and stress management.

Honghui Hu (2025) studied this question.

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Mixed-methods analysis compares post-editing efficiency in translating machine and AI outputs, suggesting insights for translator training.