Automatic Detection of Grammatical Errors in English Translations: Assessing the Efficacy and Suggesting Some Recommendations for Boosting Grammarly Software

Document Type : Scientific Research

Author
Mahmoud Afrouz
Associate Professor, Department of English Language and Literature, Faculty of Foreign Languages, University of Isfahan, Iran
10.48311/lrr.2025.7138
Abstract
Grammarly is one of the most widely used software applications for the automatic detection of grammatical errors in texts translated from Persian into English. This study aimed to evaluate the effectiveness of Grammarly and to propose suggestions for improving its performance. To achieve this objective, a corpus consisting of English translations of booklets introducing works of resistance literature was analyzed. After grammatical errors had been identified by the researchers (human evaluators), the electronic versions of the booklets were submitted to Grammarly for error detection. The identified errors were then categorized, and the results obtained by the researchers were compared with those generated by the software. Following the qualitative and quantitative analyses of the errors and the presentation of the findings, recommendations were made to enhance Grammarly’s effectiveness. According to the findings, of the 98 instances identified by Grammarly as errors, 16 were not actual errors. In four cases (4.9%), Grammarly failed to correctly identify the type of error. The software demonstrated its weakest performance in the detection of spelling errors and the misuse of masculine and feminine pronouns. Overall, Grammarly exhibited a high level of effectiveness, correctly identifying 82.8% of the errors.
Keywords
Grammatical Errors
Automatic Detection of Errors
Grammarly software
Translation Assessment
Subjects
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