Indonesian EFL Learners’ Perceptions of ChatGPT’s Translation Readability in Translating English Literary Text
Abstrak
This study investigated how English as foreign language (EFL) learners in a literary community setting perceived the readability of ChatGPT’s translations in translating an English short story into Indonesian. This research used a short story written by Gerald Murnane entitled The Boy’s Name was David. By using a descriptive qualitative approach, the research explored two questions: the readability score of the translations and learners’ perceptions of this readability. Purposive sampling was employed by involving 18 EFL learners from Kurvadot Creative, a literature discussion community in Cepu, Indonesia. The data were collected through document, questionnaires, and focus group discussions. The readability assessment was analyzed by using Nababan’s Translation Quality Assessment (TQA) framework, while the EFL learners’ perceptions in the discussion was analyzed by using thematic analysis. The results revealed that learners generally rated the ChatGPT translations as Readable, with an average score of 2.68. However, the participants also identified several challenges. These included linguistic issues, such as issues with syntax, semantics, and stylistics, as well as reading engagement problems where the participants required more time to read certain parts of the translation. In addition, the untranslated sentences caused by ChatGPT's content policy restrictions added to the challenges. Despite the relatively high readability ratings, these factors disrupted participants' overall reading experiences with the translated short story by ChatGPT.
Artikel teks lengkap
Referensi
Afdholy, N., Ahmadi, A., & Murti, G. H. (2020). Preserving local literary community: literary planning and policy as a cultural strategy in Indonesia. Satwika : Kajian Ilmu Budaya Dan Perubahan Sosial, 4(2), 157–164. https://doi.org/10.22219/satwika.v4i2.13945
Ainan Ningrum, & Dewi, U. (2024). The Use of Google Translate and U-Dictionary as Machine Translation for Translating Text: EFL College Student’s Preference and Perceptions. ETERNAL (English Teaching Journal), 15(1), 167–179. https://doi.org/10.26877/eternal.v15i1.373
Baihaqi, A., & Mulyana, A. (2021). Reviewing the result of machine translation: a case for indonesian translation version by google translate and imtranslator. PROJECT (Professional Journal of English Education), 4(1), 1. https://doi.org/10.22460/project.v4i1.p1-9
Bania, A. S., & Faridy, N. (2023). Quality of translation via google translate in comedy texts. Englisia: Journal of Language, Education, and Humanities, 11(1). https://doi.org/10.22373/ej.v11i1.19364
Beinborn, L., Zesch, T., & Gurevych, I. (2014). Readability for foreign language learning: The importance of cognates. ITL - International Journal of Applied Linguistics, 165(2), 136–162. https://doi.org/10.1075/itl.165.2.02bei
Bukar, U. A., Sayeed, M. S., Abdul Razak, S. F., Yogarayan, S., & Ahmed Amodu, O. (2024). An integrative decision-making framework to guide policies on regulating ChatGPT usage. PeerJ Computer Science, 10, e1845. https://doi.org/10.7717/peerj-cs.1845
Carman, L. (2018, April 23). In the room with Gerald Murnane. Sydney Review of Books. https://sydneyreviewofbooks.com/essays/in-the-room-with-gerald-murnane
Creswell, J. W. (2013). Qualitative inquiry and research design: Choosing among five approaches (third edition). SAGE.
Diasti, K. S. (2024). Utilizing ChatGPT in English Language Learning: Higher Education Students’ Experience. In E. M. Dukut, A. Suratno, H. Hartono, R. Gajjala, M. M. Jayanthi, C. D. Gabriel, & H. P. Atilano (Eds.), Proceedings of the 7th Celt International Conference (CIC 2024) (Vol. 897, pp. 190–200). Atlantis Press SARL. https://doi.org/10.2991/978-2-38476-348-1_14
Duncan, C., & Mcculloh, I. (2023). Unmasking Bias in Chat GPT Responses. Proceedings of the International Conference on Advances in Social Networks Analysis and Mining, 687–691. https://doi.org/10.1145/3625007.3627484
Gambier, Y. (2023). The conceptualisation of translation in translation studies: A response. Translation Studies, 16(2), 317–322. https://doi.org/10.1080/14781700.2023.2209576
Ghosh, S., & Caliskan, A. (2023). ChatGPT Perpetuates Gender Bias in Machine Translation and Ignores Non-Gendered Pronouns: Findings across Bengali and Five other Low-Resource Languages. Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 901–912. https://doi.org/10.1145/3600211.3604672
Guerberof-Arenas, A., & Toral, A. (2024). To be or not to be: A translation reception study of a literary text translated into Dutch and Catalan using machine translation. Target. International Journal of Translation Studies, 36(2), 215–244. https://doi.org/10.1075/target.22134.gue
Haleem, A., Javaid, M., & Singh, R. P. (2022). An era of ChatGPT as a significant futuristic support tool: A study on features, abilities, and challenges. BenchCouncil Transactions on Benchmarks, Standards and Evaluations, 2(4), 100089. https://doi.org/10.1016/j.tbench.2023.100089
Hidayati, N. N., & Nihayah, D. H. (2024). Google Translate, ChatGPT or Google Bard AI: A Study toward Non-English Department College Students’ Preference and Translation Comparison. Inspiring: English Education Journal, 7(1), 14–33. https://doi.org/10.35905/inspiring.v7i1.8821
Ismailia, T. (2023). Analysis of Machine Translation Performance on Translating Informative Text from English into Indonesian. EBONY: Journal of English Language Teaching, Linguistics, and Literature, 3(2), 129–138. https://doi.org/10.37304/ebony.v3i2.9809
Jeane Tuilan, Herminus Efrando Pabur, & Ignatius J. C. Tuerah. (2023). Online Machine Translation and Language Learning: EFL Learners’ Practices and Beliefs. Technium Social Sciences Journal, 50, 342–354. https://doi.org/10.47577/tssj.v50i1.9910
Kastowo, C., Christiani, T. A., & Sundari, E. (2024). Chat GPT from Educational, Legal and Ethical Perspectives in Indonesia. Revista de Gestão Social e Ambiental, 18(7), e04941. https://doi.org/10.24857/rgsa.v18n7-071
Khairudin, A., Sukma, N. C., & Kebudayaan, I. D. J. (2023). Lawatan jalan terus: Catatan perjalanan. Direktorat Jenderal Kebudayaan, Kemendikbudristek RI. https://books.google.co.id/books?id=MW6r0AEACAAJ
Kim, M. (2004). Literature Discussions in Adult L2 Learning. Language and Education, 18(2), 145–166. https://doi.org/10.1080/09500780408666872
Manifeste, D. (2023). Mastering ChatGPT: Create Highly Effective Prompts, Strategies, and Best Practices to Go From Novice to Expert. TJ Books. https://destinymanifest.gumroad.com/l/
McDonald, S. V. (2020). Accuracy, readability, and acceptability in translation. Applied Translation. https://doi.org/10.51708/apptrans.v14n2.1238
Murnane, G. (2018). Stream system: The collected short fiction of Gerald Murnane (First edition). Farrar, Straus and Giroux.
Murphy, J. (2013). Reading landscape in Gerald Murnane’s ThePlains. Exegesis 4, 2, 4–13.
Murphy, J. (2014). Being-in-Landscape: A Heideggerian Reading of Landscape in Gerald Murnane’s Inland. Journal of the Association for the Study of Australian Literature, 14(3). https://openjournals.library.sydney.edu.au/JASAL/article/view/10279
Nababan, M., & Nuraeni, A. (2012). Pengembangan model penilaian kualitas terjemahan. Kajian Linguistik dan Sastra, 24(1), 39–57.
Nababan, M., & Santosa, R. (2018). Translation techniques and their impact on the readability of translated bible stories for children. Humanus, 17(2), 212–222. http://dx.doi.org/10.24036/humanus.v17i2.102729
Nasution, D. K. (2022). Machine Translation in Website Localization: Assessing its Translation Quality for Language Learning. AL-ISHLAH: Jurnal Pendidikan, 14(2), 1879–1886. https://doi.org/10.35445/alishlah.v14i2.1308
Naveen, P., & Trojovský, P. (2024). Overview and challenges of machine translation for contextually appropriate translations. iScience, 27(10), 110878. https://doi.org/10.1016/j.isci.2024.110878
Neuman, W. L. (2014). Social research methods: Qualitative and quantitative approaches (Seventh edition, Pearson new international edition). Pearson.
Postigo, M. L. (2024). ChatGPT and MT-Systems: Advantages and Limitations when Translating English to Spanish and Portuguese. LABARTA POSTIGO. https://roderic.uv.es/rest/api/core/bitstreams/d5ef9b11-ef36-4776-8eac-79a5d99a0a5c/content
Putrawan, G. E. (2019). The Role of First Language and Translation in EFL Learning: A Brief Literature Review. International Journal of Linguistics, Literature and Translation, 2(2), 150–154. https://doi.org/10.32996/ijllt.2019.2.2.23
Raad, B. (2020). The Role of Machine Translation in Language Learning. Academic Research International, 7, 2348–7666.
Rohmah, Z. (2005). English as a global language: Its historical past and its future. Jurnal Bahasa & Seni, 33(1), 106–117.
Taivalkoski-Shilov, K. (2019). Free indirect discourse: An insurmountable challenge for literary MT systems? Proceedings of the Qualities of Literary Machine Translation, 35–39.
Teng, M. F. (2024). “ChatGPT is the companion, not enemies”: EFL learners’ perceptions and experiences in using ChatGPT for feedback in writing. Computers and Education: Artificial Intelligence, 7, 100270. https://doi.org/10.1016/j.caeai.2024.100270
Turganbayeva, A., Rakhimova, D., Karyukin, V., Karibayeva, A., & Turarbek, A. (2022). Semantic Connections in the Complex Sentences for Post-Editing Machine Translation in the Kazakh Language. Information, 13(9), 411. https://doi.org/10.3390/info13090411
Uhlmann, A. (2015). Silence and Sound in the Sentences of Gerald Murnane’s A Million Windows. Journal of the Association for the Study of Australian Literature, 15(1). https://openjournals.library.sydney.edu.au/JASAL/article/view/9937
Urlaub, P., & Dessein, E. (2022). Machine translation and foreign language education. Frontiers in Artificial Intelligence, 5, 936111. https://doi.org/10.3389/frai.2022.936111
Vo, T. K. O., & Huynh, M. T. V. (2024). Exploring the Benefits of Authentic Materials in Enhancing Translation Students’ Motivation. International Journal of Social Science and Human Research, 7(07). https://doi.org/10.47191/ijsshr/v7-i07-39
Winiharti, M., Syihabuddin, S., & Sudana, D. (2021). On Google Translate: Students’ and Lecturers’ Perception of the English Translation of Indonesian Scholarly Articles. Lingua Cultura, 15(2), 207–214. https://doi.org/10.21512/lc.v15i2.7335
Xiao, Y., & Zhi, Y. (2023). An Exploratory Study of EFL Learners’ Use of ChatGPT for Language Learning Tasks: Experience and Perceptions. Languages, 8(3), 212. https://doi.org/10.3390/languages8030212
Yuxiu, Y. (2024). Application of translation technology based on AI in translation teaching. Systems and Soft Computing, 6, 200072. https://doi.org/10.1016/j.sasc.2024.200072
Penulis
Hak Cipta (c) 2025 Luqman Rosyidy, Anam Sutopo, Dwi Haryanti
Artikel ini berlisensi Creative Commons Attribution-NonCommercial 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-NonCommercial 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published workÂ