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The Korean Association for the Study of English Language and Linguistics
[ Article ]
Korea Journal of English Language and Linguistics - Vol. 24, No. 0, pp.425-440
ISSN: 1598-1398 (Print) 2586-7474 (Online)
Print publication date 31 Jan 2024
Received 31 Mar 2024 Revised 17 Apr 2024 Accepted 20 Apr 2024
DOI: https://doi.org/10.15738/kjell.24..202404.425

Machine Translation Use in Presentation Scripts: Learners’ Reflections and Implications for English Education

Hyun-Jin Kim
(1st author) Teaching Professor, Dasan University College Ajou University 206 Worldcup-ro, Yeongtong-gu Suwon, Korea, Tel: 031)219-3044 hjinkim@ajou.ac.kr


© 2024 KASELL All rights reserved
This is an open-access article distributed under the terms of the Creative Commons License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The significant advancements in machine translation (MT) technologies highlight their inevitable integration into language learning contexts. This study examines Korean university students’ utilization and perceptions of MT tools, particularly in writing English presentation scripts, exploring their strategies and experiences with MT in language learning. The participants comprised 29 first-year students enrolled in a general English course at a university. Data collection involved students’ reflection papers on the presentation, focusing on guiding questions to explore various aspects of their experiences, viewpoints, and attitudes regarding MT use in script writing for oral presentations. Findings reveal that students use MT to address challenges in clarity, word order, and complex sentences in English writing, indicating a willingness to engage with MT. The unanimous agreement among students highlights the perceived benefits of using MT, notably its significant impact on enhancing the overall effectiveness and efficiency of English writing tasks. This positive aspect, however, calls for strategic guidance from language educators to mitigate potential drawbacks. The study proposes strategies for incorporating MT in classroom English language instruction, emphasizing the importance of instructor guidance and student reflection in navigating the complexities and potentials of MT in this underexplored genre in foreign language education.

Keywords:

machine translation, English teaching and learning, L2 writing, presentation script, student reflection

References

  • Ahn, S. and E.-S. Chung. 2020. Students’ perceptions of the use of online machine translation in L2 writing. Multimedia-Assisted Language Learning 23(2), 10-35.
  • Celce-Murcia, M. and D. Larsen-Freeman. 1999. The Grammar Book: An ESL/EFL Teacher’s Course (2nd ed.). Boston, MA: Heinle & Heinle.
  • Chon, W.Y., G. Shin and D. Kim. 2020. Comparing L2 learners’ writing against parallel machine-translated texts: Raters’ assessment, linguistic complexity and errors. System 96, 102408. [https://doi.org/10.1016/j.system.2020.102408]
  • Clifford, J., L. M. Merschel and J. Munné. 2013. Surveying the landscape: What is the role of machine translation in language learning? Research in Education and Learning Innovation Archives 10, 108-121.
  • Crossley, S. A. 2018. Technological disruption in foreign language teaching: The rise of simultaneous machine translation. Language Teaching 51(4), 541-552. [https://doi.org/10.1017/S0261444818000253]
  • Garcia, I. and M. Pena. 2011. Machine translation-assisted language learning: Writing for beginners. Computer Assisted Language Learning 24(5), 471-487. [https://doi.org/10.1080/09588221.2011.582687]
  • Gritsay, I. and L. Vodyanitskaya. 2021. Pedagogical technologies of machine translation skills forming on the example of bachelor students specializing in mechatronics and robotics at Don State Technical University. In E3S Web of Conferences 273, 6. [https://doi.org/10.1051/e3sconf/202127312140]
  • Groves, M. and K. Mundt. 2015. Friend or foe? Google Translate in language for academic purposes. English for Specific Purposes 37, 112-121. [https://doi.org/10.1016/j.esp.2014.09.001]
  • Helyer, R. 2015. Learning through reflection: The critical role of reflection in work-based learning. Journal of Work-Applied Management 7(1), 15-27. [https://doi.org/10.1108/JWAM-10-2015-003]
  • Hutchins, E. 1995. Machine translation: A brief history. In E. F. K. Koerner and R. E. Asher, eds., Concise History of the Language Sciences: From the Sumerians to the Cognitivists, 431-445. Oxford: Pergamon Press. [https://doi.org/10.1016/B978-0-08-042580-1.50066-0]
  • Im, H.-J. 2017. The university students’ perceptions or attitudes on the use of the English automatic translation in a general English class: Based on English writing lessons. Korean Journal of General Education 11(6), 727-751.
  • Jeong, N.-S. 2021. A study on the effects of machine translators on college students’ writing proficiency and affective attitude. Multimedia-Assisted Language Learning 24(1), 134-157.
  • Jiménez-Crespo, M. 2017. The role of translation technologies in Spanish language learning. Journal of Spanish Language Teaching 4(2), 181-193. [https://doi.org/10.1080/23247797.2017.1408949]
  • Jolley, J. and L. Maimone. 2015. Free online machine translation: Use and perceptions by Spanish students and instructors. In A. J. Moeller, ed., Learn Languages, Explore Cultures, Transform Lives, 181-200. Minneapolis: Central States Conference on the Teaching of Foreign Languages.
  • Kim, H.-J. 2022. Benefits of collaborative writing: University students’ reflections. Modern English Education 23(2), 1-9. [https://doi.org/10.18095/meeso.2022.23.2.1]
  • Klimova, B., M. Pikhart, P. Polakova, M. Cerna, S. Y. Yayilgan and S. Shaikh. 2023. A systematic review on the use of emerging technologies in teaching English as an applied language at the university level. Systems 11(1), 42. [https://doi.org/10.3390/systems11010042]
  • Koehn, P. 2020. Neural Machine Translation. Cambridge: Cambridge University Press. [https://doi.org/10.1017/9781108608480]
  • Lee, E.-N. and H. Yoon. 2010. The effects of writing as a pre-speaking activity on the college students’ speaking performance. English Language Teaching 22(3), 143-166. [https://doi.org/10.17936/pkelt.2010.22.3.007]
  • Lee, S.-M. 2019. Korean college students’ perceptions toward the effectiveness of machine translation on L2 revision. Multimedia-Assisted Language Learning 22(4), 206-225.
  • Lee, S.-M. 2020. The impact of using machine translation on EFL students’ writing. Computer Assisted Language Learning 33(3), 157-175. [https://doi.org/10.1080/09588221.2018.1553186]
  • Lee, S.-M. and N. Briggs. 2020. Effects of using machine translation to mediate the revision process of Korean university students’ academic writing. ReCALL 33(1), 18-33. [https://doi.org/10.1017/S0958344020000191]
  • Murtisari, E., R. Widiningrum, J. Branata and R. Susanto. 2019. Google Translate in language learning: Indonesian EFL students’ attitudes. The Journal of Asia TEFL 16(3), 978-986. [https://doi.org/10.18823/asiatefl.2019.16.3.14.978]
  • Niño, A. 2009. Machine translation in foreign language learning: Language learners’ and tutors’ perceptions of its advantages and disadvantages. ReCALL 21(2), 241-258. [https://doi.org/10.1017/S0958344009000172]
  • Niño A. 2020. Exploring the use of online machine translation for independent language learning. Research in Learning Technology 28. [https://doi.org/10.25304/rlt.v28.2402]
  • O’Neill, E. M. 2016. Measuring the impact of online translation on FL writing scores. The IALLT Journal of Language Learning Technologies 46(2), 1-39. [https://doi.org/10.17161/iallt.v46i2.8560]
  • O’Neill, E. M. 2019. Training students to use online translators and dictionaries: The impact on second language writing scores. International Journal of Research Studies in Language Learning 8(2), 47-65. [https://doi.org/10.5861/ijrsll.2019.4002]
  • Sheppard, F. 2011. Medical writing in English: The problem with Google Translate. La Presse Médicale 40(6), 565-566. [https://doi.org/10.1016/j.lpm.2011.02.024]
  • Somers, H., F. Gaspari and A. Niño. 2006. Detecting inappropriate use of free online machine-translation by language students: A special case of plagiarism detection. In Proceedings of the 11th Annual Conference of the European Association for Machine Translation, 41-48.
  • Tsai, S.-C. 2019. Using Google Translate in EFL drafts: A preliminary investigation. Computer Assisted Language Learning 32(5-6), 510-526. [https://doi.org/10.1080/09588221.2018.1527361]
  • Vold, E. T. 2018. Using machine-translated texts to generate L3 learners’ metalinguistic talk. In Å. Haukås, C. Bjørke and M. Dypedahl, eds., Metacognition in Language Learning and Teaching, 67-97. London: Routledge. [https://doi.org/10.4324/9781351049146-5]
  • White, K. and E. Heidrich. 2013. Our policies, their text: German language students’ strategies with and beliefs about web-based machine translation. Die Unterrichtspraxis 46(2), 230-250. [https://doi.org/10.1111/tger.10143]