هوش مصنوعی مولد و تحول ترجمه ادبی: تحقیق کیفی در دیدگاه دانشجویان ادبیات

نوع مقاله : علمی پژوهشی(عادی)

نویسندگان

1 گروه زبان و ادبیات انگلیسی، دانشکده ادبیات و علوم انسانی، دانشگاه حکیم سبزواری، سبزوار، ایران.

2 گروه آموزش زبان انگلیسی، دانشکده ادبیات و علوم انسانی، دانشگاه اصفهان، اصفهان، ایران.

3 گروه زبان و ادبیات انگلیسی، دانشکده ادبیات و علوم انسانی، دانشگاه زنجان، زنجان، ایران.

10.22059/jflr.2025.392118.1198

چکیده

کاربردهای چت‌جی‌پی‌تی در حوزه آموزش به‌طور گسترده‌ای مورد توجه پژوهشگران قرار گرفته است، اما بررسی‌های علمی در زمینه ترجمه، به‌ویژه ترجمه متون ادبی، بسیار محدود است. مطالعه حاضر به واکاوی نگرش‌های دانشجویان ادبیات انگلیسی نسبت به هوش مصنوعی مولد، به‌ویژه چت‌جی‌پی‌تی، در زمینه ترجمه آثار ادبی می‌پردازد. این پژوهش با مشارکت ۲۲ دانشجوی مقطع کارشناسی رشته ادبیات انگلیسی دانشگاه حکیم سبزواری انجام شده و برای گردآوری داده‌ها از روش‌های کیفی، شامل مصاحبه‌های نیمه‌ساختاریافته و چهارچوب‌های روایی، جهت تحلیل تجربیات شرکت‌کنندگان در طول یک دوره آموزشی ۱۲ هفته‌ای بهره گرفته است. در این بازه زمانی، دانشجویان با استفاده از چت‌جی‌پی‌تی به ترجمه متون ادبی متنوعی همچون شعر، داستان کوتاه و بخش‌هایی از رمان پرداختند. یافته‌های به‌دست‌آمده، ابعاد مثبت و منفی استفاده از هوش مصنوعی در فرایند ترجمه را آشکار ساخت. دانشجویان، چت‌جی‌پی‌تی را به‌دلیل سرعت، سهولت دسترسی و نقش آن در ارتقای خلاقیت، گسترش دامنه واژگان و تسهیل فرایند یادگیری مورد تحسین قرار دادند. بااین‌حال، محدودیت‌هایی نظیر ناتوانی در درک ظرافت‌های فرهنگی، عمق احساسی و پیچیدگی‌های سبکی به‌ویژه در متون شعری، به‌طور ملموسی نمایان شد. افزون‌بر این، نگرانی‌هایی پیرامون وابستگی بیش از حد به ابزار هوش مصنوعی، مسائل اخلاقی نظیر سرقت ادبی و همچنین ناتوانی این فناوری در جایگزینی بینش انسانی مطرح گردید. باوجوداین چالش‌ها، بیشتر دانشجویان چت‌جی‌پی‌تی را ابزاری مکمل و نه جایگزین مترجمان انسانی ارزیابی کردند. این پژوهش بر ضرورت تدوین راهبردهای آموزشی تأکید دارد که دانشجویان را برای تعامل انتقادی با هوش مصنوعی آماده ساخته و توازنی میان کارآمدی و خلاقیت ایجاد کند. مطالعات آتی می‌بایست بر ارتقای توانمندی‌های هوش مصنوعی در فهم پیچیدگی‌های فرهنگی و عاطفی و همچنین بررسی شیوه‌های ادغام آن در روندهای کاری مشترک با مترجمان انسانی تمرکز نمایند.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Generative AI and the Transformation of Literary Translation: A Qualitative Inquiry into the Perspectives of Literature Students

نویسندگان [English]

  • Asghar Moulavinafchi 1
  • Masoud Madahiian 2
  • Sayyede Maryam Hosseini 3
1 Department of English Language and Literature, Faculty of Literature and Humanities, Hakim Sabzevari University, Sabzevar, Iran.
2 Department of English Language Teaching, Faculty of Literature and Humanities, University of Isfahan, Isfahan, Iran.
3 Department of English Language and Literature, Faculty of Literature and Humanities, University of Zanjan, Zanjan, Iran.
چکیده [English]

The applications of ChatGPT in the field of education have attracted widespread attention from researchers; however, scholarly investigations in the area of translation—particularly literary translation—are considerably limited. The present study explores the attitudes of English literature students toward generative artificial intelligence (GenAI), especially ChatGPT, in the context of literary translation. This research was conducted with the participation of 22 undergraduate students majoring in English literature at Hakim Sabzevari University. Qualitative methods, including semi-structured interviews and narrative frameworks, were employed to collect data and analyze participants’ experiences over a twelve-week instructional period. During this interval, students utilized ChatGPT to translate a variety of literary texts, such as poetry, short stories, and excerpts from novels. The findings revealed both positive and negative aspects of using artificial intelligence in the translation process. Students praised ChatGPT for its speed, accessibility, and its role in enhancing creativity, expanding vocabulary, and facilitating the learning process. Nevertheless, limitations such as the inability to grasp cultural subtleties, emotional depth, and stylistic complexities—particularly in poetic texts—became tangibly apparent. Furthermore, concerns were raised regarding overreliance on artificial intelligence tools, ethical issues such as plagiarism, and the incapacity of this technology to replace human insight. Despite these challenges, most students evaluated ChatGPT as a supplementary tool rather than a substitute for human translators.

کلیدواژه‌ها [English]

  • ChatGPT
  • Generative Artificial Intelligence (GenAI)
  • Literary Translation
  • Literature Students
  • Translation Education

مراجع

Alharbi, W. (2023). The Use and Abuse of Artificial Intelligence-Enabled Machine Translation in the EFL Classroom: An Exploratory Study. Journal of Education and e-learning Research, 10(4), https://doi.org/10.689-701. 0.20448/jeelr.v10i4.5091
Alifa S, M., Dzatil Hidayah, A. G., Aditya, R., & Wihadi, M. (2021). Artificial Intelligence Meet Language as Technology Advances in Translation Tools. International Journal of Computer in Humanities, 1, 51-58. Retrieved from https://ojs.unikom.ac.id/index.php/injuchum/article/view/9594
Alsaqer, B. N. A. (2023). The role of deconstructing as a part of translation process in literary text. World Journal of Advanced Research and Reviews, 20(02), 960-968. https://doi.org/10.30574/wjarr.2023.20.2.2335
Ayvazyan, N., Torres-Simón, E., & Pym, A. (2024). Translation students' trust in machine translation: Too good to be true? In C. Odacioglu (Ed.), Revolutionizing Translation Studies: Synthesizing Translation with AI and IT innovation (pp. 9-30).
Ayyaz, S. (2025). AI Translation Tools in Language Learning: Bridging Gaps and Enhancing Skills. In AI Applications for English Language Learning (pp. 43-72). IGI Global Scientific Publishing.
Başer, Z., & Aral, M. (2024). Perspectives of translation students on artificial intelligence-based translation tools. Kırıkkale Üniversitesi Sosyal Bilimler Dergisi, 14(3), 39-55.
Birt, L., Scott, S., Cavers, D., Campbell, C., & Walter, F. (2016). Member checking: a tool to enhance trustworthiness or merely a nod to validation?. Qualitative health research, 26(13), 1802-1811. https://doi.org/10.1177/1049732316654870
Bowker, L. (2020). Machine translation literacy instruction for international business students and business English instructors. Journal of Business & Finance Librarianship, 25(1-2), 25-43. https://doi.org/10.1080/08963568.2020.1794739
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
Budiharjo, B. (2024). Artificial Intelligence in Translation: The Menace, Promise, and Response to Technology and Superseded Practice. In Third International Conference on Communication, Language, Literature, and Culture (ICCoLliC 2024) (pp. 681-694). Atlantis Press. https://doi.org/10.2991/978-2-38476-321-4_52
Cheng, Y., Wang, R., Chen, J., Chao, Y., Maimaitili, A., & Zhang, H. (2023). Context-Based AI Translation from a Globalization Perspective: A Case Study of ChatGPT. Sino-US English Teaching, 20(9), 370-380. https://doi.org/10.17265/1539-8072/2023.09.005
Creswell, J. W. (2014). Research design: Qualitative, quantitative and mixed method approaches (4th ed.). Sage Publications.
Darawsheh, W. (2014). Reflexivity in research: Promoting rigour, reliability and validity in qualitative research. International Journal of Therapy and Rehabilitation, 21(12), 560-568. https://doi.org/10.12968/ijtr.2014.21.12.560
Dracsineanu, C. (2024). Transformative translation: navigating the era of chatGPT and artificial intelligence. In Probleme de lingvistică romano-germanică şi comunicare interculturală (pp. 211-214). https://doi.org/10.5281/zenodo.10650241
Dziri, K., & Hassani, M. F. (2024). Improving English as Foreign Language Students’ Translation Quality Using Artificial Intelligence (Doctoral dissertation, ibn Khaldoun University-Tiaret).
Emara, E. A. E. H. M. (2024). Using AI tools to enhance translation skills among basic education English major students. CDELT Occasional Papers in the Development of English Education, 86(1), 339-380. https://doi.org/10.21608/opde.2024.362829
Fadnes, L. T., Taube, A., & Tylleskär, T. (2009). How to identify information bias due to self-reporting in epidemiological research. The Internet Journal of Epidemiology, 7(2), 28-38.
Falempin, A., & Ranadireksa, D. (2024). Human vs. Machine: The Future of Translation in an AI-Driven World. In Widyatama International Conference on Engineering 2024 (WICOENG 2024) (pp. 177-183). Atlantis Press.
Ferguson, L. (2004). External validity, generalizability, and knowledge utilization. Journal of Nursing Scholarship, 36(1), 16-22. https://doi.org/10.1111/j.1547-5069.2004.04006.x
Gao, J., & Yin, J. (2024). Emotional Expression of AI-generated Artistic Design: A Case Analysis Approach. Chitrolekha Journal, 8(1). https://doi.org/10.21659/cjad.81.v8n104
Huang, X., Zou, D., Cheng, G., Chen, X., & Xie, H. (2023). Trends, Research Issues and Applications of Artificial Intelligence in Language Education. Educational Technology & Society, 26(1), 112–131. https://doi.org/10.30191/ETS.202301_26(1).0009
Islam, M. A., & Aldaihani, F. M. F. (2022). Justification for adopting qualitative research method, research approaches, sampling strategy, sample size, interview method, saturation, and data analysis. Journal of International Business and Management, 5(1), 01-11. https://doi.org/10.37227/JIBM-2021-09-1494
Jakobson, R. (1959). On linguistic aspects of translation. In On translation (pp. 232-239). Harvard University Press.
Jaruwatsawat, M., Khiaosen, C., Sriram, W., & Phoowong, S. (2024). EFL Learners’ Perspectives on Using AI Translation Applications. BRU ELT JOURNAL, 2(3), 252–267. https://doi.org/10.14456/bej.2024.17
Khasawneh, M. A. S., & Al-Amrat, M. G. R. (2023). Evaluating the role of artificial intelligence in advancing translation studies: Insights from experts. Migration Letters, 20(S2), 932-943. https://doi.org/10.5430/jct.v13n2p180
Kocabıyık, H. S. (2022). The Effects of Translation Theories on the Assessment of Translations. Söylem Filoloji Dergisi, 7(1), 225-236. https://doi.org/10.29110/soylemdergi.1076815
Kolb, D. A. (2014). Experiential learning: Experience as the source of learning and development. FT Press.
Kornacki, M., & Pietrzak, P. (2024). Hybrid Workflows in Translation: Integrating GenAI Into Translator Training. Taylor & Francis.
Kruk, M., & Kałużna, A. (2025). Investigating the Role of AI Tools in Enhancing Translation Skills, Emotional Experiences, and Motivation in L2 Learning. European Journal of Education, 60(1), e12859. https://doi.org/10.1111/ejed.12859
Kumar, O. (2023). Investigating the impact of artificial intelligence AI and technology in English language learning. Advances in Social Behavior Research, 3, 27-36. https://doi.org/10.54254/2753-7102/3/2023026
Le, D. (2024). Investigating how cultural differences influence the translation process and the strategies used by translators to bridge cultural gaps. Journal of Translation and Language Studies, 5(3), 26–36. https://doi.org/10.48185/jtls.v5i3.1268
Macken, L., Prou, D., & Tezcan, A. (2020). Quantifying the effect of machine translation in a high-quality human translation production process. In Informatics (Vol. 7, No. 2, p. 12). MDPI.
Mills, J., Birks, M., & Lewis, P. (2014). Narrative research. In Narrative research (pp. 161-180). SAGE Publications, Inc., https://doi.org/10.4135/9781473920163.n10
Mirzaeian, V. Reza (2024). The Effect of Artificial Intelligence Generated Translation versus Human Translation on Reading Comprehension of the Speakers of Less Commonly Taught Languages. Iranian Journal of Applied Language Studies, 16(1), 63-74.  https://doi.org/10.22111/ijals.2024.47092.2395
Mohamed, Y. A., Mohamed, A. H., Kannan, A., Bashir, M., Adiel, M. A., & Elsadig, M. A. (2024). Navigating the Ethical Terrain of AI-Generated Text Tools: A Review. IEEE Access, 12, 197061 -197120. https://doi.org/10.1109/ACCESS.2024.3521945
Nida, E. A. (1964). Toward a science of translating: with special reference to principles and procedures involved in Bible translating. Brill Archive.
Padash, M. and Behjat, H. (2016). Review of advertisement translation problems: offering some solutions. Journal of Foreign Language Research, 6(1), 115-130. https://doi.org/10.22059/jflr.2016.62812
Popel, M., Tomkova, M., Tomek, J., Kaiser, Ł., Uszkoreit, J., Bojar, O., & Žabokrtský, Z. (2020). Transforming machine translation: a deep learning system reaches news translation quality comparable to human professionals. Nature communications, 11(1), 4381. https://doi.org/10.1038/s41467-020-18073-9
Rai, N., & Thapa, B. (2015). A study on purposive sampling method in research. Kathmandu School of Law, 5(1), 8-15. https://doi.org/10.1186/s13104-019-4156-9
Ren, X. (2025). We want but we can’t: measuring EFL translation majors’ intention to use ChatGPT in their translation practice. Humanities and Social Sciences Communications, 12(1), 1-11. https://doi.org/10.1057/s41599-025-04604-6
Roberts, K., Dowell, A., & Nie, J. B. (2019). Attempting rigour and replicability in thematic analysis of qualitative research data; a case study of codebook development. BMC medical research methodology, 19(1), 1-8. https://doi.org/10.1186/s12874-019-0707-y
Robinson, P. (2010). Poetry & Translation: The art of the impossible. Liverpool University Press.
Ruoqi, S., Yuan, X., & Gochuico, M. T. (2023). Translators and their use of ChatGPT. Academia Lasalliana Journal of Education and Humanities, 5(1), 49-59. https://doi.org/10.55902/PLRU9197
Ruwaiza Sasmita, & Tiara Azzahra Marpaung. (2024). Code of Ethics for the use of AI in Translation. BLAZE: Jurnal Bahasa Dan Sastra Dalam Pendidikan Linguistik dan Pengembangan, 3(1), 108–119. https://doi.org/10.59841/blaze.v3i1.2260
Sabounchi, M. (2015). The Importance of Knowledge of Culture in Translation: Case Study. Journal of Foreign Language Research, 5(2), 333-352. https://doi.org/10.22059/jflr.2015.62555
Santos, S. (2000). A poetry of two minds. University of Georgia Press.
Sasmita, R., & Marpaung, T. A. (2025). Code of ethics for the use of ai in translation. BLAZE: Jurnal Bahasa dan Sastra dalam Pendidikan Linguistik dan Pengembangan, 3(1), 108-119. https://doi.org/10.59841/blaze.v3i1.2260
Shahiditabar, M. (2023). “When Persia meets the Caucasus through poetry”: Ashraf of Gilan’s allusion to Mirza Alakbar Sabir during the Iranian constitutional era. International Journal of Turkish Literature Culture Education (TLCE), 12(2), 482-495. https://doi.org/10.7884/teke.1312740
Shahiditabar, M. (2024a). An Intertextual and Crosslinguistic Study of Versified Translation of Poetry. Translation and Interpreting Research, 1(2), 78-90. https://doi.org/10.22054/tir.2024.79944.1026
Shahiditabar, M. (2024b). Mechanism of poetry translation: A case study of versified translation. Journal of Foreign Language Research, 13(4), 613-624. https://doi.org/10.22059/jflr.2023.361263.1047
Spall, S. (1998). Peer debriefing in qualitative research: Emerging operational models. Qualitative inquiry, 4(2), 280-292. https://doi.org/10.1177/107780049800400208
Steiner, D. F., Chen, P. H. C., & Mermel, C. H. (2021). Closing the translation gap: AI applications in digital pathology. Biochimica et Biophysica Acta (BBA)-Reviews on Cancer, 1875(1), 188452. https://doi.org/10.1016/j.bbcan.2020.188452
Thabet, M. A., & Qadha, A. M. (2024). The Influence of AI-Based Translation Tools on the Translation of Dr. Ghazi Al-Qusaibi’s Poetry by Saudi EFL Learners. مجلة العلوم التربویة و الدراسات الإنسانیة, (38), 772-799.‎ https://doi.org/10.55074/hesj.vi38.1046
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., ... & Polosukhin, I. (2017). Attention is all you need. Advances in neural information processing systems, 30.
Venuti, L. (2017). The translator's invisibility: A history of translation. Routledge.
Wang, Y. (2023). Artificial intelligence technologies in college English translation teaching. Journal of psycholinguistic research, 52(5), 1525-1544. https://doi.org/10.1007/s10936-023-09960-5
Yang, J. (2024). The perception of pre-service English teachers’ use of AI translation tools in EFL writing. The Journal of the Convergence on Culture Technology, 10(1), 121–128. https://doi.org/10.17703/JCCT.2024.10.1.121
Yin, R. K. (2015). Qualitative research from start to finish. Guilford publications.
Yu, H., Guo, Y., Yang, H., Zhang, W., & Dong, Y. (2025). Can ChatGPT Revolutionize Language Learning? Unveiling the Power of AI in Multilingual Education Through User Insights and Pedagogical Impact. European Journal of Education, 60(1), e12749. https://doi.org/10.1111/ejed.12749
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
Zhai, C., & Wibowo, S. (2023). A systematic review on artificial intelligence dialogue systems for enhancing English as foreign language students’ interactional competence in the university. Computers and Education: Artificial Intelligence, 4, 100134. https://doi.org/10.1016/j.caeai.2023.100134
Zhai, C., Wibowo, S., & Li, L. D. (2024). The effects of over-reliance on AI dialogue systems on students' cognitive abilities: a systematic review. Smart Learning Environments, 11(1), 28. https://doi.org/10.1186/s40561-024-00316-7
Zhang, W., Li, A. W., & Wu, C. (2025). University students’ perceptions of using generative AI in translation practices. Instructional Science, 1-23. https://doi.org/10.1007/s11251-025-09705-y
Zhao, W., Huang, S., & Yan, L. (2024, May). ChatGPT and the future of translators: Overview of the application of interactive AI in English translation teaching. In 2024 4th international conference on computer communication and artificial intelligence (CCAI) (pp. 303-307). IEEE. https://doi.org/10.1109/CCAI61966.2024.10602989.
Zuo, Y., Ching, G. S., & Khotsing, R. (2024). The Application of ChatGPT in Literary Translation: A Case Study from Thai to Chinese. In International Workshop on Learning Technology for Education Challenges (pp. 332-348). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-61678-5_24
پژوهشهای زبانشناختی در زبانهای خارجی
دوره 15، شماره 2
مرداد 1404
صفحه 171-193

فایل ها

هم رسانی

ارجاع به این مقاله

آمار