Differentiating between machine translation and student translation: red flags and salient lexicogrammatical features.

Andrew Richard Burns Innes

Abstract


ABSTRACT

Machine translation enables students to produce work in the target L2 which may be superior to that which they could produce otherwise.  The present study examines whether use of machine translation can be detected by teachers.  Seventeen native teachers compared and assessed the authorship of five human translations (HT) and five machine translations (MT) of Japanese news stories.  Native teachers were able to accurately detect the difference in 74.04% of cases due to increased passive clauses (a ratio of 1 to 2.5), and inappropriate pronoun use (a ratio of 1 to 6.5) when MT was used.

 


Keywords


SFL, machine translation, detection, student essays.

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References


Aharoni, R., Koppel, M., & Goldberg, Y. (2014). Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Short Papers), pages 289–295, Baltimore, Maryland, June 23-25 2014. Association for Computational Linguistics.

Benda, J. (2013). Google Translate in the EFL Classroom Taboo or Teaching Tool? Writing & pedagogy . Retrieved March 14, 2019 from https://journals.equinoxpub.com/WAP/article/view/19968. DOI: 10.1558/wap.v5i2.317.

BERA (2011). Retrieved April 5, 2019, from https://www.bera.ac.uk/wp-content/uploads/2014/02/BERA-Ethical-Guidelines-2011.pdf?noredirect=1.

Briggs, N. (2018). Neural machine translation tools in the language learning classroom: Students` use, perceptions, and analyses. Jalt call journal, 14(1), 3-24.

Çakır, S. (2013). A Study on the efficiency of the Google Translate translation program. In I. Özyıldırım, S. N. Büyükkantarcıoğlu, E. Yarar, & E. Alpaslan (Eds.), Kırkıncı Yıl Yazıları (pp. 75-83). Ankara: Hacettepe Üniversitesi Yayınları.

Clifford, J., Merschel, L., & Reisinger, D. (2013). Meeting the challenges of machine translation. The Language Educator, 8, 44–47.

Coffin, C., Donohue, J., & North, S. (2009). Exploring English Grammar From Formal to Functional. London: Routledge.

Correa, M. (2014). Leaving the “peer” out of peer-editing: Online translators as a pedagogical tool in the Spanish as a second language classroom. Latin American Journal of Content and Language Integrated Learning, 7(2), 1–20 DOI:10.5294/laclil.2014.7.1.1.

Crystal, D. (2003). English as a Global Language. Cambridge: Cambridge University Press.

Davies, R. J., & Ikeno, O. (2002). The Japanese Mind: Understanding Contemporary Japanese Culture. Clarendon, VT: Tuttle Publishing.

Ebbert-Hübner, C. & Maas, C. (2017). Can Translation Improve EFL Students' Grammatical Accuracy? International Journal of English Language & Translation Studies, 5(4), 191-202.

Garcia, I., & Pena, M. I. (2011). Machine translation-assisted language learning: writing for beginners. Computer Assisted Language Learning, 24(5), 471-487. DOI: 10.1080/09588221.2011.582687.

Gibbons, P. (2008). “It was taught good and I learned a lot”: Intellectual practices and ESL learners in the middle years. Australian Journal of Language and Literacy, 31(2), 155–173.

Groves, M., & Mundt, K. (2015). Friend or foe? Google Translate in language for academic purposes. English for Specific Purposes, 37, 112-121.

Retrieved April 5, 2019, from https://www.sciencedirect.com/science/article/pii/S088949061400060X#!).

Hall, E. T. (1976). Beyond culture. New York: Doubleday.

Kazemzadeh, A., & Kashani, A. (2014). The effect of computer-assisted translation on L2 learners’ mastery of writing. International Journal of Research Studies in Language Learning, 3, 29-44.

Lee J., & Liao, P. (2011). A Comparative Study of Human Translation and Machine Translation with Post-editing.Compilation and Translation Review, 4(2), 105-149.

Lommel, A. (2019). tcworld.info - translation and localization. Tcworld.info. Retrieved March, 30, 2019 from http://www.tcworld.info/e-magazine/translation-and-localization/article/neural-machine-translation-offers-significant-advances-with-remaining-challenges.

McGuire, N. (2018). How accurate is Google Translate in 2018? ARGO Translation. Retrieved March 12, 2019, from https://www.argotrans.com/blog/accurate-google-translate-2018.

News Web Easy (2019). Retrieved April, 15, 2019 from https://www3.nhk.or.jp/news/easy/k10011858001000/k10011858001000.

Prensky, M. (2001). Digital Natives Digital Immigrants. Part 1. On the Horizon, 9(5), 1-6.

Schuster, M., Johnson, M., & Thorat, N. (2016). Zero-Shot Translation with Google's Multilingual Neural Machine Translation System. Retrieved March 3, 2019, from https://ai.googleblog.com/2016/11/zero-shot-translation-with-googles.html.

Sugiyama, S. (2019). All aboard the Sakai Muscle Line? Osaka Metro axes foreign language website after botched translation. From Japan. Retrieved February 10, 2019, from https://www.fromjapan.co.uk/news/all-aboard-the-sakai-muscle-line-osaka-metro-axes-foreign-language-website-after-botched-translation/.

Surveymonkey.com. (2019). SurveyMonkey - Free online survey software and questionnaire tool. Retrieved April 15, 2019, from https://www.surveymonkey.com.

Upwork.com. What is Translation Plagiarism and How do You Detect it? Retrieved March 13, 2019 from https://www.upwork.com/hiring/for-clients/translation-plagiarism-detection/.

White, K. D., & Heidrich, E. (2013). Our Policies, Their Text: German Language Students' Strategies with and Beliefs about Web-Based Machine Translation. Die Unterrichtspraxis/Teaching German, 46(2), 230-250.

Van Praag, B., & Sanchez, H.S. (2015). Mobile technology in second language classrooms: Insights into its uses, pedagogical implications, and teacher beliefs. ReCALL, 27(3), 288-303. DOI: 10.2017/S0958344015000075.

Vygotsky, I. (1978). Mind in society: Development of higher psychological processes. Cambridge: Harvard University Press.

Wu, Y., Schuster, M., Chen, Z., Le, Q., & Norouzi, M. (2016). Google’s Neural Machine Translation System: Bridging the Gap between Human and Machine Translation. Retrieved March 18, 2019, from https://arxiv.org/abs/1609.08144.

Young, L., & Fitzgerald, B. (2006). The Power of Language How Discourse Influences Society. London: Equinox.




DOI: http://dx.doi.org/10.17951/lsmll.2019.43.4.1-13
Date of publication: 2019-12-30 00:00:00
Date of submission: 2019-05-14 11:55:12


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