PERSPECTIVES OF TRANSLATION STUDENTS ON ARTIFICIAL INTELLIGENCE-BASED TRANSLATION TOOLS
Year 2024,
Volume: 14 Issue: 3, 39 - 55, 30.12.2024
Zeynep Başer
,
Mehtap Aral
Abstract
Today, artificial intelligence (AI) has started to dominate many fields. This threatens the future of existing professions. One of the most striking of these fields is undoubtedly translation and interpreting. With the strengthening of AI, the use of AI-based translation tools is rapidly increasing as a faster, more efficient, and easily accessible alternative to traditional methods. This raises questions and problems about the skills that a translator should have in the world of AI, the practices and contents that need to be revised in higher education curricula that provide translation education and the readiness of translation students to practice their profession in the future. The aim of this study is to determine and compare the views of the 1st- and the 4th-grade students in the Department of English Translation and Interpreting on artificial intelligence-based translation tools. A questionnaire was administered to learn the future concerns and expectations of the students who are new to translation education and to examine the 4th-grade students' evaluation of the current education program and how ready they are to become translators in the world of artificial intelligence. The students were asked questions on three main topics. These can be listed as (1) the opinions of translation students on the curriculum and course contents in terms of AI applications, (2) students' self-evaluation of their level of using AI applications in translation, and (3) their positive or negative thoughts on how AI will affect their profession in the near future. The findings demonstrate that the 4th-grade students use AI more than the 1st-grade students, and trust the accuracy of AI more; however, they are indecisive about the ratio of courses on AI-based tools in the curriculum or find it more insufficient, and have more negative concerns about the future of the profession. The results of the study are expected to contribute to the field in terms of revising the current English Translation and Interpreting curricula and course contents and raising awareness about the effects of artificial intelligence on the future of the translation profession.
Ethical Statement
Ethics committee permission information
Name of the ethical review board: Kırıkkale University Social Sciences and Humanities Research Ethics
Committee
Date of ethical assessment decision: 18.12.2023
Number of the ethical assessment certificate: 12
References
- Alifa, M., Hidayah, A. G. D., Aditya, R., & Wihadi, M. (2021). Artificial intelligence meet language as technology advances in translation tools. International Journal of Computer in Humanities, 1, 51-58.
- Ayvazyan, N., & Torres-Simón, E., Pym, A. (2024). Translation students’ trust in machine translation: Too good to be true? In M. Odacıoglu (Ed.), Revolutionizing Translation Studies. Synthesizing Translation with AI and IT Innovation (1st ed.). Aktif.
- Bacaksiz, A. D. (2019). The future of translation studies through artificial intelligence [Master's thesis, Atılım University]. Turkish Council of Higher Education National Thesis Center.
- Bowker, L. (2002). Computer-aided translation technology: A practical introduction. University of Ottawa Press.
- Bowker, L. (2015). Translation technologies: Translator training. InChan Sin-wai (Ed.) Routledge Encyclopedia of Translation Technology (pp. 95-111). Routledge.
- Bowker, L. (2020). Chinese speakers’ use of machine translation as an aid for scholarly writing in English: a review of the literature and a report on a pilot workshop on machine translation literacy. Asia Pacific Translation and Intercultural Studies, 7(3), 288-298.
- Charles-Kenechi, S. (2024). Artificial Intelligence in Translation Studies: Benefits and Challenges. Cascades, Journal of the Department of French & International Studies, 2(1), 5–15. Retrieved from https://cascadesjournal.com/index.php/cascades/article/view/31
- 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.
- Çetiner, C., & İşisağ, K. (2019). Undergraduate level translation students’ attitudes towards machine translation post-editing training. International Journal of Languages' Education and Teaching, 7(1), 110-120.
- He, Y. (2021). Challenges and countermeasures of translation teaching in the era of artificial intelligence. In Journal of Physics: Conference Series (Vol. 1881, No. 2, p. 022086). IOP Publishing.
- Hutchins, W. J. (1995). Machine translation: A brief history. In Concise history of the language sciences (pp. 431-445). Pergamon.
- Kenny, D. (Ed.) (2022). Machine translation for everyone: Empowering users in the age of artificial intelligence. (Translation and Multilingual Natural Language Processing 18). Berlin: Language Science Press.
- 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.
- Kirov, V., & Malamin, B. (2022). Are translators afraid of artificial intelligence? Societies, 12(2), 70.
- Koka, N. A. (2024). The integration and utilization of artificial intelligence (AI) in supporting older/Senior lecturers to adapt to the changing landscape in translation pedagogy. Migration Letters, 21(S1), 59 71.
- Laksana K. N., & Komara, C. (2024). Indonesian EFL students’ perceptions of DeepL machine translation tool: Utilization, Advantages and Disadvantages. JOLLS, Journal of Language and Literature Studies, 4 (2), 256-276. https:// doi.org/10.36312/jılls.v4i2.1931
- LeBlanc, M. (2017) ‘“I Can’t Get No Satisfaction!” Should We Blame Translation Technologies or Shifting Business Practices?’, in D. Kenny (ed.) Human Issues in Translation Technology. London & New York: Routledge, 45–62.
- Lee, T. K. (2023). Artificial intelligence and posthumanist translation: ChatGPT versus the translator. Applied Linguistics Review. https://doi.org/10.1515/applirev-2023-0122
- Liu, K., Kwok, H. L., Liu, J., & Cheung, A. K. (2022). Sustainability and influence of machine translation: perceptions and attitudes of translation instructors and learners in Hong Kong. Sustainability, 14(11), 6399.
- Man, D., Mo, A., Chau, M. H., O’Toole, J. M., & Lee, C. (2020). Translation technology adoption: Evidence from a postgraduate programme for student translators in China. Perspectives, 28(2), 253-270.
- Pastor, D. G. (2021). Introducing machine translation in the translation classroom: A survey on students’ attitudes and perceptions. Tradumàtica tecnologies de la traducció, (19), 47-65.
- Shi, Z. (2019). Advanced artificial intelligence (Vol. 4). World Scientific.
- Şahin, M. (2023). Yapay çeviri. Çeviribilim Yayınları.
- Tian, S., Jia, L., & Zhang, Z. (2023). Investigating students’ attitudes towards translation technology: The status quo and structural relations with translation mindsets and future work self. Frontiers in Psychology, 14, 1122612.
- Tok, Z. (2019). Bilgisayar destekli çeviri sürecinde çevirmenin görevi. Language and Literature, 14(2), 905-915.
- Türkmen, B., & Can, M. Z. (2019). The opportunities and the limitations of using the independent post-editor technology in translation education. International Journal of Advanced Computer Science and Applications, 10(3).
- Yaman, İ. (2023). DeepL Translate ve Google Translate sistemlerinin İngilizce-Türkçe ve Türkçe-İngilizce çeviri performanslarının karşılaştırılması. Söylem Filoloji Dergisi, (Çeviribilim Özel Sayısı), 29-41.
Yapay Zekâ Temelli Çeviri Araçlarına İlişkin Mütercim ve Tercümanlık Öğrencilerinin Görüşleri
Year 2024,
Volume: 14 Issue: 3, 39 - 55, 30.12.2024
Zeynep Başer
,
Mehtap Aral
Abstract
Günümüzde yapay zekâ pek çok alana hâkim hale gelmeye başlamıştır. Bu da mevcut mesleklerin geleceğini tehdit etmektedir. Bu alanlardan en dikkat çekenlerden biri de şüphesiz çeviridir. Yapay zekânın güçlenmesiyle geleneksel yöntemler yerine daha hızlı, verimli ve kolay ulaşılabilir bir alternatif olarak yapay zekâ destekli çeviri araçlarının kullanımı hızla artmaktadır. Bu da yapay zekâ dünyasında çevirmende olması gereken beceriler, çeviri eğitimi veren yükseköğretim müfredatlarında gözden geçirilmesi gereken uygulama ve içerikler, çeviri eğitimi gören öğrencilerin gelecekte mesleklerini icra etme noktasında hazır bulunuşlukları ile ilgili soru ve sorunları gündeme getirmektedir. Bu çalışmanın amacı İngilizce Mütercim ve Tercümanlık bölümünde eğitim gören 1. ve 4. sınıf öğrencilerinin yapay zekâ temelli çeviri araçlarına yönelik görüşlerini belirlemek ve karşılaştırmaktır. Çeviri eğitimine yeni adım atan öğrencilerin geleceğe yönelik kaygılarını ve eğitim programından beklentilerini öğrenmek, son sınıf öğrencilerinin ise mevcut eğitim programıyla ilgili değerlendirmelerini ve yapay zekâ dünyasında çevirmen olmaya ne kadar hazır olduklarını incelemek için anket uygulanmıştır. Öğrencilere üç ana kategoride sorular yöneltilmiştir. Bunlar; (1) yapay zekâ uygulamaları bakımından İngilizce Mütercim ve Tercümanlık öğrencilerinin müfredat ve ders içerikleri hakkındaki görüşleri, (2) öğrencilerin yapay zekâ uygulamalarını çeviride kullanma düzeylerine yönelik kendi kendilerini değerlendirmeleri ve (3) yapay zekânın yakın gelecekte mesleklerini ne yönde etkileyeceğine dair olumlu ya da olumsuz düşünceleri olarak sıralanabilir. Bulgular, 4. sınıf öğrencilerinin 1. sınıf öğrencilerine kıyasla yapay zekâ temelli çeviri araçlarını daha fazla kullandıklarını, yapay zekanın doğruluğuna daha fazla güvendiklerini, ancak müfredatta yapay zekâ temelli çeviri araçlarıyla ilgili derslerin oranı konusunda kararsız olduklarını ya da bu oranı daha yetersiz bulduklarını ve mesleğin geleceği hakkında daha olumsuz endişelere sahip olduklarını göstermektedir. Çalışmanın sonuçlarının, mevcut İngilizce Mütercim ve Tercümanlık müfredat ve ders içeriklerinin yeniden gözden geçirilmesi ve yapay zekânın çevirmenlik mesleğinin geleceğine etkileri ile ilgili farkındalık uyandırması bakımından alana katkı sağlaması beklenmektedir.
References
- Alifa, M., Hidayah, A. G. D., Aditya, R., & Wihadi, M. (2021). Artificial intelligence meet language as technology advances in translation tools. International Journal of Computer in Humanities, 1, 51-58.
- Ayvazyan, N., & Torres-Simón, E., Pym, A. (2024). Translation students’ trust in machine translation: Too good to be true? In M. Odacıoglu (Ed.), Revolutionizing Translation Studies. Synthesizing Translation with AI and IT Innovation (1st ed.). Aktif.
- Bacaksiz, A. D. (2019). The future of translation studies through artificial intelligence [Master's thesis, Atılım University]. Turkish Council of Higher Education National Thesis Center.
- Bowker, L. (2002). Computer-aided translation technology: A practical introduction. University of Ottawa Press.
- Bowker, L. (2015). Translation technologies: Translator training. InChan Sin-wai (Ed.) Routledge Encyclopedia of Translation Technology (pp. 95-111). Routledge.
- Bowker, L. (2020). Chinese speakers’ use of machine translation as an aid for scholarly writing in English: a review of the literature and a report on a pilot workshop on machine translation literacy. Asia Pacific Translation and Intercultural Studies, 7(3), 288-298.
- Charles-Kenechi, S. (2024). Artificial Intelligence in Translation Studies: Benefits and Challenges. Cascades, Journal of the Department of French & International Studies, 2(1), 5–15. Retrieved from https://cascadesjournal.com/index.php/cascades/article/view/31
- 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.
- Çetiner, C., & İşisağ, K. (2019). Undergraduate level translation students’ attitudes towards machine translation post-editing training. International Journal of Languages' Education and Teaching, 7(1), 110-120.
- He, Y. (2021). Challenges and countermeasures of translation teaching in the era of artificial intelligence. In Journal of Physics: Conference Series (Vol. 1881, No. 2, p. 022086). IOP Publishing.
- Hutchins, W. J. (1995). Machine translation: A brief history. In Concise history of the language sciences (pp. 431-445). Pergamon.
- Kenny, D. (Ed.) (2022). Machine translation for everyone: Empowering users in the age of artificial intelligence. (Translation and Multilingual Natural Language Processing 18). Berlin: Language Science Press.
- 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.
- Kirov, V., & Malamin, B. (2022). Are translators afraid of artificial intelligence? Societies, 12(2), 70.
- Koka, N. A. (2024). The integration and utilization of artificial intelligence (AI) in supporting older/Senior lecturers to adapt to the changing landscape in translation pedagogy. Migration Letters, 21(S1), 59 71.
- Laksana K. N., & Komara, C. (2024). Indonesian EFL students’ perceptions of DeepL machine translation tool: Utilization, Advantages and Disadvantages. JOLLS, Journal of Language and Literature Studies, 4 (2), 256-276. https:// doi.org/10.36312/jılls.v4i2.1931
- LeBlanc, M. (2017) ‘“I Can’t Get No Satisfaction!” Should We Blame Translation Technologies or Shifting Business Practices?’, in D. Kenny (ed.) Human Issues in Translation Technology. London & New York: Routledge, 45–62.
- Lee, T. K. (2023). Artificial intelligence and posthumanist translation: ChatGPT versus the translator. Applied Linguistics Review. https://doi.org/10.1515/applirev-2023-0122
- Liu, K., Kwok, H. L., Liu, J., & Cheung, A. K. (2022). Sustainability and influence of machine translation: perceptions and attitudes of translation instructors and learners in Hong Kong. Sustainability, 14(11), 6399.
- Man, D., Mo, A., Chau, M. H., O’Toole, J. M., & Lee, C. (2020). Translation technology adoption: Evidence from a postgraduate programme for student translators in China. Perspectives, 28(2), 253-270.
- Pastor, D. G. (2021). Introducing machine translation in the translation classroom: A survey on students’ attitudes and perceptions. Tradumàtica tecnologies de la traducció, (19), 47-65.
- Shi, Z. (2019). Advanced artificial intelligence (Vol. 4). World Scientific.
- Şahin, M. (2023). Yapay çeviri. Çeviribilim Yayınları.
- Tian, S., Jia, L., & Zhang, Z. (2023). Investigating students’ attitudes towards translation technology: The status quo and structural relations with translation mindsets and future work self. Frontiers in Psychology, 14, 1122612.
- Tok, Z. (2019). Bilgisayar destekli çeviri sürecinde çevirmenin görevi. Language and Literature, 14(2), 905-915.
- Türkmen, B., & Can, M. Z. (2019). The opportunities and the limitations of using the independent post-editor technology in translation education. International Journal of Advanced Computer Science and Applications, 10(3).
- Yaman, İ. (2023). DeepL Translate ve Google Translate sistemlerinin İngilizce-Türkçe ve Türkçe-İngilizce çeviri performanslarının karşılaştırılması. Söylem Filoloji Dergisi, (Çeviribilim Özel Sayısı), 29-41.