Student poetry translations with and without the use of AI

An evaluation of translation quality

Authors

  • Issy Yuliasri Scopus ID. 57194435562, Universitas Negeri Semarang
  • Bambang Purwanto Universitas Negeri Semarang
  • Muhammad Zaki Pahrul Hadi Universitas Negeri Semarang
  • Agung Dwi Nurcahyo Universitas Negeri Semarang
  • Pryla Rochmahwati Scopus ID. 57218095387, Universitas Islam Negeri Ponorogo
  • Muhammad Rifqi Universitas Dian Nuswantoro
  • Kusuma Arum Diana Kumara
  • Fithriyatul Ma’sumah Universitas Negeri Semarang

DOI:

https://doi.org/10.33633/lite.v21i2.14336

Keywords:

artificial intelligence, poeticness, poetry translation, translation quality

Abstract

Poetry translation presents a unique challenge, as it requires maintaining a delicate balance between semantic fidelity and the preservation of the aesthetic qualities of the target text. This study aims to evaluate the quality of poetry translations produced by university students both with and without the assistance of artificial intelligence (AI), using four assessment criteria based on Nababan's (2012) framework: accuracy, acceptability, readability, and poeticness. The research employed a descriptive quantitative approach with an evaluation instrument using a three-point scale, where a score of 3 indicates high quality, 2 denotes moderate quality, and 1 reflects low quality. Data were obtained from poetry translations evaluated by experienced raters using a standardized rubric, with results analyzed in terms of frequency distribution and percentages. Findings reveal that in AI-assisted translations, the highest score attainment was observed in readability (52.76%), followed by acceptability (51.14%), accuracy (50.39%), and poeticness (24.34%) as the lowest. In contrast, in translations without AI, the highest score attainment was also found in readability (34.76%), followed by accuracy (33.06%), acceptability (32.43%), and poeticness (12.33%). This comparison indicates that AI use consistently enhances accuracy, acceptability, and readability scores, yet shows limited capacity to improve poeticness significantly. This aspect requires creativity, stylistic sensitivity, and nuanced linguistic judgment beyond the current capabilities of AI systems.

Author Biographies

Issy Yuliasri, Scopus ID. 57194435562, Universitas Negeri Semarang

Prof. Dr.  Issy Yuliasri, M.Pd.. Professor of applied linguistics at Universitas Negeri Semarang. Scopus ID. 57194435562

Bambang Purwanto, Universitas Negeri Semarang

English Lecturer at Universitas Negeri Semarang

Pryla Rochmahwati, Scopus ID. 57218095387, Universitas Islam Negeri Ponorogo

Dr. Pryla Rochmahwati, M.Pd., English Lecturer and Head of Language Development at Universitas Islam Negeri Kiai Ageng Muhammad Besari, Ponorogo.

Muhammad Rifqi, Universitas Dian Nuswantoro

Dr. Muhammad Rifqi, S.S., M.Pd., English Lecturer at Universitas Dian Nuswantoro Semarang

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Published

2025-09-30

How to Cite

Yuliasri, I., Purwanto, B., Hadi, M. Z. P. ., Nurcahyo, A. D. ., Rochmahwati, P. ., Rifqi, M. ., Kumara, K. A. D. ., & Ma’sumah, F. (2025). Student poetry translations with and without the use of AI: An evaluation of translation quality. LITE: Jurnal Bahasa, Sastra, Dan Budaya, 21(2), 452–468. https://doi.org/10.33633/lite.v21i2.14336

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