Your browser does not support the PubReader view.
Go to this page to see a list of supporting browsers.
The Korean Association for the Study of English Language and Linguistics
[ Article ]
Korea Journal of English Language and Linguistics - Vol. 23, No. 0, pp.38-58
ISSN: 1598-1398 (Print) 2586-7474 (Online)
Print publication date 30 Jan 2023
Received 19 Nov 2022 Revised 16 Jan 2023 Accepted 28 Jan 2023
DOI: https://doi.org/10.15738/kjell.23..202301.38

The Role of AI Translators on Reading Comprehension

Hea-Suk Kim ; Yoonjung Cha
(1st author) Professor, Dept. of General Education, Seoul Women’s Univ. shskim@swu.ac.kr
(corresponding author) Professor, Peace and Liberal Arts College, Hanshin Univ. yjcha@hs.ac.kr


© 2023 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

This study aims to investigate reading comprehension and students’ perception in a university reading course using an AI translator, whether Google or Papago Translate. The subjects were comprised of 113 students divided into three groups: the control group analyzed reading texts traditionally, the first experimental group analyzed reading texts using Google or Papago Translate, while the second experimental group also analyzed reading texts using Google or Papago Translate, but then also revised the machine translator’s incorrect translations. Reading comprehension tests and a post-questionnaire were then administered to examine the effects of using AI translators. The findings showed that all three groups significantly improved their reading comprehension scores in the post-tests as compared to those in the pre-tests. However, there were no statistically significant differences between groups. Regarding students’ perception, the participants using an AI translator showed no statistical differences between the two experimental groups. However, in terms of sentence structure, students’ translations after using an AI translator were perceived to be of significantly higher quality compared with those that simply used the translator. Most participants stated that using AI translators was much more beneficial to get the main idea and for understanding the whole passage, rather than using it simply to learn vocabulary and expressions. Furthermore, using AI translators relieved the participants’ anxiety and burden while also satisfying them. However, such students also had lower mean scores in terms of interest and motivation for language learning in the post-questionnaire items. Based on the results of the study, pedagogical implications and future research are suggested.

Keywords:

AI translator, reading, perception, artificial intelligence, machine translator

Acknowledgments

This paper was supported by Hanshin University Research Fund in 2022.

References

  • Akbulut, Y. 2007. Effects of multimedia annotations on incidental vocabulary learning and reading comprehension of advanced learners of English as a foreign language. Instructional Science 35(6), 499-517. [https://doi.org/10.1007/s11251-007-9016-7]
  • Alhaisoni, E. and M. Alhaysony. 2017. An investigation of Saudi EFL university students’ attitudes towards the use of Google Translate. International Journal of English Language Education 5(1), 72-82. [https://doi.org/10.5296/ijele.v5i1.10696]
  • Bagheri M. and I. Fazel. 2011. EFL beliefs about translation and its use as a strategy in writing. Reading Matrix: An International Online Journal 11(3), 292-301.
  • Bahri H. and T. Mahadi. 2016. Google Translate as a supplementary tool for learning Malay: A case study at Universiti Sains Malaysia. Advances in Language and Literary Studies 7(3), 161-167. [https://doi.org/10.7575/aiac.alls.v.7n.3p.161]
  • Baker, C. L. 2013. Student and instructor perceptions of the use of online translation in English composition. Mississippi State University. Retrieved January 29 2019, from https://core.ac.uk/download/pdf/71975137.pdf
  • Becker, H. J. 2000. Pedagogical motivations for student computer use that lead to student engagement. Educational Technology 40(5), 5-17.
  • Brahmana, C. R. P. S., R. Sofyan and D. M. Putri. 2020. Problems in the application of Google Translate as a learning media in translation. Language Literacy: Journal of Linguistics, Literature, and Language Teaching 4(2), 384-389. [https://doi.org/10.30743/ll.v4i2.2893]
  • Briggs, N. 2018. Neural machine translation tools in the language learning classroom: Students’ use, perceptions, and analyses. JALT CALL J 14, 2-24. [https://doi.org/10.29140/jaltcall.v14n1.221]
  • Cha, Y., H.-S. Kim and N-Y Kim. 2022. An application of Padlet to English reading at three reading stages. Multimedia-Assisted Language Learning 25(3), 9-38.
  • Chon, Y. V. and D. Shin. 2020. Direct writing, translated writing, and machine-translated writing: A text level analysis with Coh-Metrix. English Teaching 75(1), 25-48. [https://doi.org/10.15858/engtea.75.1.202003.25]
  • Hoi, H. T. 2020. Machine translation and its impact in our modern society. International Journal of Scientific and Technology Research 9(2), 1918-1921.
  • Jo, I. H. 2018. The effect of machine translation on English writing instruction: Focusing on the writing self-efficacy and the writing quantity. English Language and Literature Studies 60(2), 253-279.
  • Jolley, J. R. and L. Maimone. 2015. Free online machine translation: Use and perceptions by Spanish students and instructors. Learn Language, Explore Cultures, Transform Lives, 181-200.
  • Karnal, A. R. and V. V. Pereira. 2015. Reading strategies in a L2: A study on machine translation. The Reading Matrix 15(2), 69-79.
  • Karnal, A. R. and P. W. Vera. 2013. Reading comprehension and the use of Google Translator. International Journal of English Linguistics 3(6), 113-118. [https://doi.org/10.5539/ijel.v3n6p113]
  • Kelly, N. and J. Bruen. 2015. Translation as a pedagogical tool in the foreign language classroom: A qualitative study of attitudes and behaviours. Language Teaching Research 19(2), 150-168. [https://doi.org/10.1177/1362168814541720]
  • Kim, H.-S. and Y. Cha. 2020. Exploring the use of a machine translator on EFL learners’ reading comprehension. STEM Journal 21(1), 119-143.
  • Kim, N-Y. 2018. Effects of the use of bilingual dictionary and machine translation on EFL students’ English proficiency. Journal of the Korea English Education Society 17(1), 21-42. [https://doi.org/10.18649/jkees.2018.17.1.21]
  • Kim, R. 2018. A critical review of the impact of the fourth industrial revolution on the development of the basic communicative competence of Korean EFL learners. Multimedia-Assisted Language Learning 21(3), 115-148.
  • Kumar, A. 2012. Machine translation in Arabic-speaking ELT classrooms: Applications and implications. International Journal of Social Science and Humanity 2(6), 442-445.
  • Lee, S. B. 2018. A phenomenological study of undergraduate students’ experiences of machine translation post-editing. Interpreting and Translation Studies 22(1), 117-143.
  • Lee, S. 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. 2022a. An investigation of machine translation output quality and the influencing factors of source texts. ReCALL 34(1), 81-94. [https://doi.org/10.1017/S0958344021000124]
  • Lee, S-M. 2022b. Korean middle school students’ perceptions and behaviors in using machine translation. Multimedia-Assisted Language Learning 25(3), 146-164.
  • Lee, S-M and N. Briggs. 2021. 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]
  • Lee, Y. J. and D. J. Lee. 2020. A study on the use of machine translator and its effects on high school students’ English writing. Journal of the Korea English Education Society 19(2), 159-180.
  • Medvedev, G. 2016. Google Translate in teaching English. Journal of Teaching English for Specific and Academic Purposes 4(1), 181-193.
  • 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]
  • Noh, Yusoo. 2021. The effects of using a machine translator on Korean university students’ English writing. The Journal of Linguistic Science 99, 125-143. [https://doi.org/10.21296/jls.2021.12.99.125]
  • O’Neill, E. 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]
  • Park, H. K. 2018. Teaching machine translation in master’s degree translation courses: A case study of post-editing activity in the Korean-Japanese language pair. The Journal of Translation Studies 19(3), 163-193. [https://doi.org/10.15749/jts.2018.19.3.007]
  • Qun, L. and Z. Xiaojun. 2015. Machine translation: General. In C. Sin-wai, ed., The Routledge encyclopedia of translation technology, 105-119. Routledge.
  • Siregar, R., R. Risnawaty, Y. Arfanti and M. Sembiring. 2020. Reflection of undergraduate students on translation process: An outlook of translation teaching in university. Lingua Cultura 14(1), 57-67. [https://doi.org/10.21512/lc.v14i1.6232]
  • Stapleton, P and B. L. K. Kin. 2019. Assessing the accuracy and teachers’ impressions of Google Translate: A study of primary L2 writers in Hong Kong. English for Specific Purposes 56, 18-34. [https://doi.org/10.1016/j.esp.2019.07.001]
  • Tsai, SC. 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]
  • Valijärvi, R. L. and E. Tarsoly. 2019. Language students as critical users of Google Translate: Pitfalls and possibilities. Practitioner Research in Higher Education 12(1), 61-74.
  • Vasheghani, M. 2020. Adequacy in machine vs. human translation: A comparative study of English and Persian languages. Applied Linguistics Research Journal 4(5), 84-104.