Embracing Technology: Perspectives of Translation and Interpreting Students on Machine Translation (MT) in Turkish Universities

Yıl 2025, Sayı: 23, 159 - 177, 11.12.2025

Bilge Metin Tekin

https://doi.org/10.26650/iujts.2025.1634780

https://izlik.org/JA32HK98WH

Öz

The goal of this study is to analyze the university students’ perception of Machine Translation (MT) in the scope of translation and interpreting studies regarding its advantages, obstacles, and ethical issues. Using a structured questionnaire, data was obtained from 82 students attending various state universities in the academic year 2023-2024. The results illustrate that students view the utility of MT as encompassing the effectiveness, accessibility, and cognitive skills of translation involving lexicon and grammatical aspects. Although these aspects are advantageous for MT, the lack of specialization in cultural, contextual, and multilayered document translation is a major limitation for MT. The study emphasizes the need to include MT training in translation curricula, as it is believed that students can benefit from learning critical skills such as post-editing and the ethical evaluation of MT output. More importantly, it emphasizes the need for clear institutional policies surrounding the ethical use of MT. However, most students indicate that they would like more information on MT, the study suggests that the majority of students learned about MT through self-learning rather than formal training. These results add to the ongoing dialogue about the incorporation of technology in translation pedagogy while providing some practical guidance for educators and academic institutions that aim to prepare students for a technology-driven industry better.

Anahtar Kelimeler

Ethical issues , Machine Translation (MT) , translation curriculum , translation pedagogy , translator trainees

Kaynakça

• Açıkgöz, F., & Sert, O. (2006). Interlingual machine translation: Prospects and setbacks. Translation Journal, 10(3), 1-16. google scholar
• Agustine, I., & Permatasari, K. M. (2021). Students’ attitudes on the use of machine translation in Japanese language class. Al-Ishlah: Jurnal Pendidikan, 13(3), 2557–2564. https://doi.org/10.35445/alishlah.v13i3.1461 google scholar
• Aslan, E. (2023). Machine translation: Perception of translation and interpretation students in Turkey. Current Trends in Translation Teaching and Learning E, 10, 185–216. https://doi.org/10.51287/cttl20237 google scholar
• Bowker, L. (2002). Computer-Aided Translation Technology. A Practical Introduction. (Didactics of Translation Series). Ottawa: Universtiy of Ottawa Press. google scholar
• Çakır, İ., & Bayhan, S. (2021). The effect of machine translation on translation classes at the tertiary level. Journal of Narrative and Language Studies, 9(16), 122–134. google scholar
• Çetiner, C. (2018). Analyzing the attitudes of translation students towards CAT (computer-aided translation) tools. Journal of Language and Linguistic Studies, 14(1), 153–161. google scholar
• Jiménez-Crespo, M. Á. (2013). Building from the ground up: on the necessity of using translationcompetence models in planning and evaluating translation and interpreting programs. Cuadernos de ALDEEU, Special Issue, Translation and Interpreting Training, 11–42 google scholar
• Kiraly, D. (2000): A Social Constructivist Approach to Translator Education; Empowerment from Theory to Practice, Manchester, UK & Northampton MA, St. Jerome Publishing, 207 p. google scholar
• Klepikova, T. (2018). Students’ common mistakes in technical texts when using computer technologies. SHS Web of Conferences, 50, Article 01014. https://doi.org/10.1051/shsconf/20185001014 google scholar
• Lin, G. H.-C., & Chien, P. S. C. (2009). Machine translation for academic purposes. In Proceedings of the International Conference on TESOL and Translation 2009 (pp. 133–148). https://files.eric.ed.gov/fulltext/ED513879.pdf google scholar
• Liu, K., Kwok, H. L., Liu, J., & Cheung, A. K. F. (2022). Sustainability and influence of machine translation: Perceptions and attitudes of translation instructors and learners in Hong Kong. Sustainability, 14(11), 6399. https://doi.org/10.3390/su14116399 google scholar
• McBride, C. (2009). Translation memory systems: An analysis of translators' attitudes and opinions. University of Ottawa. google scholar
• Melby, A. K. & Warner, C. T. (1995). The Possibility of Language: A Discussion of the Nature of Language, with Implications for Human and Machine Translation. John Benjamins Publishing. google scholar
• Özcan Dost, B. (2024). Haber çevirisinde makine çevirisi araçlarının kullanımına yönelik bir inceleme: Google Translate ve DeepL örneği. Söylem Filoloji Dergisi, 9(1), 259-276. https://doi.org/10.29110/soylemdergi.1414417 google scholar
• Palanichamy, N., & 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 google scholar
• Rana, J., Gutierrez, P. L., & Oldroyd, J. C. (2021). Quantitative methods. In A. Farazmand (Ed.), Global encyclopedia of public administration, public policy, and governance (pp. 1-6). Springer. https://doi.org/10.1007/978-3-319-31816-5_460-1 google scholar
• Trang, N. M. (2024). Common online technical tools for translation: Students’ choices, perceptions, and translation strategies used. google scholar
• European Journal of Multilingualism and Translation Studies, 4(1) 155–170. https://doi.org/10.46827/ejmts.v4i1.533 google scholar
• Vauquois, B. (1968). A survey of formal grammars and algorithms for recognition and transformation in machine translation. IFIP Congress-68 (pp. 254–260). Edinburgh, United Kingdom. google scholar