October 1, 2025ElectronicsOpen Access

Using AI in Translation Quality Assessment: A Case Study of ChatGPT and Legal Translation Texts

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Results showed a high level of agreement between AI evaluations and instructor assessments, highlighting the reliability of AI.
Statistical analysis via paired sample t-test revealed no significant differences in scores, indicating consistency in evaluation methods.
Manual error categorization demonstrated detailed insights into translation errors, allowing for targeted feedback and corrections.
Strategic integration of AI tools in translation quality assessment may enhance the educational ecosystem, requiring careful design and oversight.

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Implication

Case study reveals high alignment between AI evaluations and instructor scores in legal translations, suggesting effective integration of technology in translator training.

Cite This Study

Alghamdi et al. (2025) studied this question.

synapsesocial.com/papers/68dd91dafe798ba2fc4994a5 https://doi.org/10.3390/electronics14193893

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Implication

Case study reveals high alignment between AI evaluations and instructor scores in legal translations, suggesting effective integration of technology in translator training.

Using AI in Translation Quality Assessment: A Case Study of ChatGPT and Legal Translation Texts

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Discussion

Implication

Cite This Study

Using AI in Translation Quality Assessment: A Case Study of ChatGPT and Legal Translation Texts

Key Points

Discussion

Implication

Cite This Study

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