A Post-Editing of Translation Process by Google Translate: Metacognitive and Cognitive Study

Aries Utomo

Abstract


This study aims (1) to analyze the translator's metacognitive and cognitive strategies during the post-editing of English-Indonesian Google Translate outputs and (2) to analyze the translator's metacognitive and cognitive strategies during the post-editing of Indonesian-English Google Translate outputs. This study was qualitative research. One person was involved in this study, and the data used were one translated Indonesian-English text and one translated English-Indonesian text. To analyze the data, several steps were taken: transcribing the video, analyzing the description, considering strategies, displaying findings, and concluding. Based on the findings, it was found that the metacognitive and cognitive strategies of English-Indonesian Google Translate outputs during post-editing include Identifying and Correcting Errors, Revising, and Rereading. Cognitive strategies, such as Elaborating Ideas, Contrasting, Summarizing, Self-Questioning, Identifying Key Ideas, Expressing Opinions, Reaffirming, Connecting Ideas, Selecting Ideas, Rewriting, and Looking for Information were also noted. Reasoning strategies were not found during the post-editing of the English-Indonesian text. For the metacognitive strategies used by the translator for Indonesian-English Google Translate outputs during post-editing, the following were identified: Identifying and Correcting Errors, Revising, and Rereading. Cognitive strategies included: Elaborating Ideas, Contrasting, Summarizing, Self-Questioning, Expressing Opinions, Reaffirming, Connecting Ideas, Selecting Ideas, Rewriting, and Looking for Information. Key ideas and strategies were not identified during the post-editing of the Indonesian-English translated text. Therefore, it can be concluded that post-editing using a translation machine like Google Translate is more accurate than others.

Keywords


Post-editing; Translation; Metacognitive and cognitive

Full Text:

PDF

References


Azer, H. S., & Aghayi, M. B. (2015). An evaluation of output quality of machine translation (Padideh Software vs. Google Translate). Advances in Language and Literary Studies, 6(4), 226–237.

Bowker, L., & Ciro, J. B. (2019). Machine translation and global research: Towards improved machine translation literacy in the scholarly community. Emerald Group Publishing.

Fayruza, A. Z., Irhamni, I., & Tohe, A. (2020). The Quality of Translation Result by Google Translate and Microsft Translator in Translating Arabic Text Based on The Translation of The Book MATN AL-GHĀYAH WAT TAQRIB by Faiz El Muttaqin. Bahasa Dan Seni: Jurnal Bahasa, Sastra, Seni, Dan Pengajarannya, 48(1), 59–72.

Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2012). How to Design and Evaluate Research in Education. McGraw-Hill.

Hashempour, M., Ghonsooly, B., & Ghanizadeh, A. (2015). A study of translation students’ self-regulation and metacognitive awareness in association with their gender and educational level. International Journal of Comparative Literature and Translation Studies, 3(3), 60–69.

Hatim, B., & Munday, J. (2019). Translation: An Advanced Resource Book for Students. Routledge.

Haukås, Å., Bjørke, C., & Dypedahl, M. (2018). Metacognition in language learning and teaching. Taylor & Francis.

Hilma, R. (2011). Literal translation using Google Translate in translating the text from French to English in digital tourism brochure “Bienvenue À Paris.” Binus Business Review, 2(1), 502–509.

Hu, K., & Cadwell, P. (2016). A comparative study of post-editing guidelines. Baltic Journal of Modern Computing, 4(2), 346–353.

Larenas, C., Ramos Leiva, L., & Ortiz Navarrete, M. (2017). Rhetorical, Metacognitive, and Cognitive Strategies in Teacher Candidates’ Essay Writing. Profile Issues in TeachersProfessional Development, 19(2), 87–100.

Li, Y., & Lu, X. (2021). Study on Post-editing for Machine Translation of Railway Engineering Texts. SHS Web of Conferences, 96, 5001.

Moorkens, J., Castilho, S., Gaspari, F., & Doherty, S. (2018). Translation Quality Assessment. Machine Translation: Technologies and Applications Ser. Cham: Springer International Publishing, 1, 299.

Noviarini, T. (2021). The Translation Results of Google Translate from Indonesian to English. JURNAL SMART, 7(1), 21–26.

Perfect, T. J., & Schwartz, B. L. (2002). Applied metacognition (Vol. 15). Cambridge University Press Cambridge.

Praet, S., & Verhelst, B. (2020). Teaching Translation Theory and Practice. Journal of Classics Teaching, 21(42), 31–35.

Siregar, B. U. (2021). Metacognition [PowerPoint Slides].Atma Jaya Catholic University of Indonesia.

Sugiarto, B. R., & Siregar, B. U. (2023). Lexical Cohesion in English – Indonesia Machine Translation Output: The realization of Manual Post-Editing. JALL (Journal of Applied Linguistics and Literacy), 7(1), 174. https://doi.org/10.25157/jall.v7i1.9862




DOI: http://dx.doi.org/10.25157/jall.v9i2.18733

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.