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Characteristics of Eight Korean EFL Young Adults’ L2 Writing Using Machine Translation Programs

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주제분류영어와문학

초록

Since artificial neural networks were applied to machine translation (MT) programs such as Google Translate and Papago, their quality of translation has improved dramatically. It leads to the consideration of MT as a pedagogical tool for teaching and learning English. In this regard, this study observed and analyzed eight Korean EFL young adults’ English writing processes using Google Translate and Papago in real-time. To explore when and how they exploited MT in completing a narrative essay, a qualitative method using screen recordings of writing sessions and retrospective interviews was implemented. The findings revealed three most representative instances among many others that the participants utilized MT to resolve difficulties in English. Moreover, those instances are closely related to self-judgment the writers constantly made. Self-judgment is an inevitable process for the writers to incorporate MT output in their writing. In the process of self-judgment, English abilities and knowledge the writers possess might play significant roles to accept appropriate MT outputs. The results of the present study also indicate that the participants, albeit a small number, preferred Papago over Google Translate based on their assumptions in accuracy and usefulness. Finally, some implications and limitations drawn from these results were also discussed.

Abstract

Since artificial neural networks were applied to machine translation (MT) programs such as Google Translate and Papago, their quality of translation has improved dramatically. It leads to the consideration of MT as a pedagogical tool for teaching and learning English. In this regard, this study observed and analyzed eight Korean EFL young adults’ English writing processes using Google Translate and Papago in real-time. To explore when and how they exploited MT in completing a narrative essay, a qualitative method using screen recordings of writing sessions and retrospective interviews was implemented. The findings revealed three most representative instances among many others that the participants utilized MT to resolve difficulties in English. Moreover, those instances are closely related to self-judgment the writers constantly made. Self-judgment is an inevitable process for the writers to incorporate MT output in their writing. In the process of self-judgment, English abilities and knowledge the writers possess might play significant roles to accept appropriate MT outputs. The results of the present study also indicate that the participants, albeit a small number, preferred Papago over Google Translate based on their assumptions in accuracy and usefulness. Finally, some implications and limitations drawn from these results were also discussed.

참고문헌 (22)

  1. 안수진, "Students’ Perceptions of the Use of Online Machine Translation in L2 Writing", 멀티미디어 언어교육, 23(2), pp.10~35 (2020), 한국멀티미디어언어교육학회[DOI]
  2. Case, M., "Machine translation and the disruption of foreign language learning activities", Elearning Papers, 45, pp.4~16 (2015)
  3. Chenoweth, N. A., "Fluency in writing : Generating text in L1 and L2", Written Communication, 18(1), pp.80~98 (2001)
  4. 최연희, "L1 Use in L2 Writing Process of Korean EFL Students", 영어교육, 61(1), pp.205~225 (2006), 한국영어교육학회
  5. 정은선, "The Effect of L2 Proficiency on Post-editing Machine Translated Texts", Journal of Asia TEFL, 17(1), pp.182~193 (2020), 아시아테플
  6. Clifford, J., "Surveying the landscape: What is the role of machine translation in language learning?", The Acquisition of Second Languages and Innovative Pedagogies, 10, pp.108~121 (2013)
  7. Correa, M., "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 & Language Integrated Learning, 7(1), pp.1~20 (2014)
  8. Garcia, I., "Machine translation-assisted language learning : Writing for beginners", Computer Assisted Language Learning, 24(5), pp.471~487 (2011)
  9. Groves, M., "Friend or foe? Google Translate in language for academic purposes", English for Specific Purpose, 37, pp.112~121 (2015)
  10. "A story that wasn’t on the air, a story that wasn’t done (1)" (2019)[URL]
  11. Kliffer, M. D., "Post-editing machine translation as an FSL exercise", Porta Linguarum, 9, pp.53~67 (2008)
  12. Lee, S. M., "The impact of using machine translation on EFL students’ writing", Computer Assisted Language Learning, 33(3), pp.157~175 (2020)
  13. Lee, S. M., "Effects of using machine translation to mediate the revision process of Korean university students’ academic writing", ReCALL, 33(1), pp.18~33 (2021)
  14. Leki, I., "A synthesis of research on second language writing in English" (2008), Routledge
  15. "No need to study English with AI translator?" (2018)[URL]
  16. Niño, A., "MT Post-editing : A text repair experience for the foreign language class", Cadernos de Tradução, 1(19), pp.115~131 (2007)
  17. Niño, A., "Evaluating the use of machine translation post-editing in the foreign language class", Computer Assisted Language Learning, 21(1), pp.29~49 (2008)
  18. O’Brien, S., "Translation quality assessment: From principles to practice", pp.237~262 (2018), Springer
  19. 박준석, "Analysis of the Types of Translation Errors by the Google Translator", 영어영문학연구, 59(4), pp.279~299 (2017), 한국중앙영어영문학회[DOI]
  20. Tsai, S. C., "Using google translate in EFL drafts : A preliminary investigation", Computer Assisted Language Learning, 32(5-6), pp.510~526 (2019)
  21. Wang, W., "L1 use in the L2 composing process : An expository study of 16 Chinese EFL Writers", Journal of Second Language Writing, 11(3), pp.225~246 (2002)
  22. Williams, L., "Web-based machine translation as a tool for promoting electronic literacy and language awareness", Foreign Language Annals, 39(4), pp.565~578 (2006)

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