Writing Instruction for Students Using Google Translate with Scaffolding Method to Enhance Arabic Writing Skills

Mad Ali; Nalahuddin Saleh; Shofa Musthofa Khalid; Zilva Raihan Nazir Ali Alfathimy

doi:10.17509/alsuniyat.v7i1.67958

Writing Instruction for Students Using Google Translate with Scaffolding Method to Enhance Arabic Writing Skills

Mad Ali, Nalahuddin Saleh, Shofa Musthofa Khalid, Zilva Raihan Nazir Ali Alfathimy

Abstract

This research concerns the analysis of Indonesian and Arabic student paragraphs, the results of the writing learning process using the scaffolding method, and using Google Translate to improve the ability to write Arabic paragraphs. This study aims to obtain an overview of the quality of Arabic paragraphs and efforts to improve their writing skills and bridge the pros and cons between lecturers and students regarding using Google Translate in learning to write Arabic. Data was obtained from three students who had studied morph syntax in Arabic, representing students who received the highest, medium and lowest morph syntax scores. They were tasked with making a synopsis of the film they watched for 20 minutes using Indonesian. Next, they were asked to translate it into Arabic without using any dictionary or translation machine. Then, they were asked to translate the Indonesian text using Google Translate. After that, they compared the independent translation with the translation from Google Translate and revised the independent translation better. The results showed that the quality of their respective Arabic paragraphs got better after following the scaffolding process using Google Translate

Keywords

Google Translate; Indonesian-Arabic translation; Paragraph analysis; Scaffolding

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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.doi:10.7575/aiac.alls.v.6n.4p.226

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, no. 2: 1–20. doi:10.5294/laclil.2014.7.1.1. eISSN 2322-9721. [Internet]. http://laclil.unisabana.edu.co/index.php/LACLIL/article/ view/3568/3411.]

Garcia, I. (2016). Can machine translation help the language learner? International conference ICT for language learning. https://conference.pixel-online.net/conferences/ICT4LL2010/common/download/Proceedings_pdf/TRAD02-Garcia.pdf.

Giannetti, T. R. (2016). Google Translate as a resource for writing: A study of error production in seventh grade Spanish. St. John Fisher College, master’s thesis.

Godwin-Jones, R. (2015). Contributing, creating, curating: Digital literacies for language learners. Language Learning & Technology, 19(3), 8-20. Retrieved from: http://llt.msu.edu/issues/october2015/emerging.pdf

Groves, M., and K Mundt. (2015). Friend or foe? Google Translate in language for academic purposes. English for Specific Purposes 37: 112–121. [Internet]. https://www.sciencedirect.com/science/article/pii/S088949061400060X.]

Hu, C., Bederson, B., & Rensik, P. (2010). Translation by iterative collaboration between monolingual users. Proceedings of Graphics Interface, May 31–June 2, Ottawa, Ontario, Canada. pp. 39–46.

Farzi, R. (2016). Taming translation technology for L2 writing: documenting the use of free online translation tools by ESL students in a writing course. Doctoral diss., University of Ottawa. [Internet]. https://ruor.uottawa.ca/handle/10393/ 34585.]

Jolley, J., and L. Maimone. (2015). Free online machine translation: use and perceptions by Spanish students and instructors. In Learn Languages, Explore Cultures, Transform Lives: Selected Papers from the 2015 Central States Conference on the Teaching of Foreign Languages, ed. A.J. Moeller, 181–200. https://digitalcommons.unl.edu/cgi/viewcontent.cgi? article = 1298&context = teachlearnfacpub#page = 202]

Koponen, M. (2016). Is machine translation post-editing worth the effort? A survey of research into post-editing and effort. The Journal of Specialised Translation, 25, 131–148.

Le, Q., and M. Schuster. (2016). A neural network for machine translation, at production scale. [Internet]. https://ai. googleblog.com/2016/09/a-neural-network-for-machine.html.

Lewis-Kraus, G. (2016). The great AI awakening. The New York Times Magazine, 14, p.12. [Internet] https://www.nytimes. com/2016/12/14/magazine/the-great-ai-awakening.html.

Lee, S. (2022). An investigation of machine translation output quality and the influencing factors of source texts. ReCALL, 34(1), 81-94. doi:10.1017/S0958344021000124

Lewis-Kraus, G. (2016). The great AI awakening. The New York Times Magazine, 14, p.12. [Internet] https://www.nytimes. com/2016/12/14/magazine/the-great-ai-awakening.html.

Mundt, K., & Groves, M. (2016). A double-edged sword: the merits and the policy implications of Google Translate in higher education. European Journal of Higher Education, 6(4), 387-401. https://doi.org/10.1080/21568235.2016.1172248

Rensburg, A. , Snyman, C., & Lotz, S. (2012). Applying Google Translate in a higher education environment: Translation products assessed, Southern African Linguistics and Applied Language Studies, 30:4, 511-524, DOI: 10.2989/16073614.2012.750824.

Resnik, P., Buzek, O., Hu, C., Kronrod, Y., Quinn, A. & Bederson, (2010). Improving translation via targeted paraphrasing. Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, MIT, Massachusetts, USA, pp. 127–137.

Smagorinsky, P. (2017). Deconflating the ZPD and instructional scaffolding: Retranslating and reconceiving the zone of proximal development as the zone of next development. Learning, culture and social interaction, 16, 70-75. https://doi.org/10.1016/j.lcsi.2017.10.009

Taylor, L., (1993). Vygotskian influences in mathematics education, with particular reference to attitude development, Focus on Learning Problems in Mathematics, Vol. 15, Pages 3–17.

Ping K. (2009). Machine Translation. In Baker M & Saldanha G (eds) Routledge Encyclopedia of Translation Studies. 2ndedition. New York: Routledge, pp 162–169.

Plitt, M., & Masselot, F. (2010). A productivity test of statistical machine translation post-editing in a typical localisation context. Prague Bull. Math. Linguistics, 93, 7-16.

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.

Van Rensburg, A., Snyman, C., & Lotz, S. (2012). Applying

Google Translate in a higher education environment: Translation products assessed, Southern African Linguistics and Applied Language Studies, 30:4, 511-524, DOI: 10.2989/16073614.2012.750824.

DOI: https://doi.org/10.17509/alsuniyat.v7i1.67958