An Assistance of Islamic University EFL Students through Artificial Intelligence (AI) Machine Translation and Writing Tools
DOI:
https://doi.org/10.58879/ijcep.v3i2.36Keywords:
Assistance Using Artificial Intelligence (AI), Machine Translation, AI Writing ToolsAbstract
Integrating Artificial Intelligence (AI) into language learning has transformed traditional educational paradigms, particularly in the context of English language acquisition among Islamic university students. This research aimed to assist Islamic university EFL students at Metro Lampung in using AI, especially machine translation and AI writing tools. The method used Participatory Action Research (PAR). PAR can act as a framework that facilitates collaboration between technology developers (AI) and English language learners. This assistance gave an impact for Islamic university EFL students. Using AI writing tools such as Grammarly presents many advantages for students, encompassing the refinement of grammatical precision and the fostering of autonomous writing skills. The merits considerably surpass the drawbacks when these tools are judiciously incorporated into the educational process. As students navigate the complexities of academic writing, the support of AI can serve as a conduit to heightened proficiency and self-assurance in their communicative abilities. Moreover, assistance through Machine Translation, such as DeepL, emerges as an essential resource for students navigating the intricacies of multilingual academic landscapes. Its sophisticated technology, intuitive interface, and capacity for ongoing enhancement render it indispensable for improving comprehension and facilitating effective communication. The support it offers signifies a substantial progression in the domain of language translation, harnessing the potential of deep learning technology to provide superior-quality translations.
References
Adams, D., & Chuah, K.-M. (2022). Artificial Intelligence-Based Tools in Research Writing : Current Trends and Future Potentials. Artificial Intelligence in Higher Education, 169–184. https://doi.org/10.1201/9781003184157-9
Al-Rahmi, W. M., Yahaya, N., Alamri, M. M., Alyoussef, I. Y., Al-Rahmi, A. M., & Kamin, Y. Bin. (2021). Integrating innovation diffusion theory with technology acceptance model: supporting students’ attitude towards using a massive open online courses (MOOCs) systems. Interactive Learning Environments, 29(8), 1380–1392. https://doi.org/10.1080/10494820.2019.1629599
Alamri, H., Lowell, V., Watson, W., & Watson, S. L. (2020). Using personalized learning as an instructional approach to motivate learners in online higher education: Learner self-determination and intrinsic motivation. Journal of Research on Technology in Education, 52(3), 322–352. https://doi.org/10.1080/15391523.2020.1728449
Alharbi, W. (2023). AI in the Foreign Language Classroom: A Pedagogical Overview of Automated Writing Assistance Tools. Education Research International, 2023(1), 4253331. https://doi.org/10.1155/2023/4253331
Alsariera, Y. A., Baashar, Y., Alkawsi, G., Mustafa, A., Alkahtani, A. A., & Ali, N. (2022). Assessment and Evaluation of Different Machine Learning Algorithms for Predicting Student Performance. Computational Intelligence and Neuroscience, 2022(1), 4151487. https://doi.org/10.1155/2022/4151487
Bouchrika, I., Harrati, N., Wanick, V., & Wills, G. (2021). Exploring the impact of gamification on student engagement and involvement with e-learning systems. Interactive Learning Environments, 29(8), 1244–1257. https://doi.org/10.1080/10494820.2019.1623267
Cahyadi, A., Hendryadi, Widyastuti, S., & Suryani. (2022). COVID-19, emergency remote teaching evaluation: the case of Indonesia. Education and Information Technologies, 27(2), 2165–2179. https://doi.org/10.1007/S10639-021-10680-3/TABLES/2
Chatzikoumi, E. (2020). How to evaluate machine translation: A review of automated and human metrics. Natural Language Engineering, 26(2), 137–161. https://doi.org/10.1017/S1351324919000469
Cornish, F., Breton, N., Moreno-Tabarez, U., Delgado, J., Rua, M., de-Graft Aikins, A., & Hodgetts, D. (2023). Participatory action research. Nature Reviews Methods Primers 2023 3:1, 3(1), 1–14. https://doi.org/10.1038/s43586-023-00214-1
Coupland, N. (2010). The Handbook of Language and Globalization. The Handbook of Language and Globalization. https://doi.org/10.1002/9781444324068
Dai, Y., Chai, C. S., Lin, P. Y., Jong, M. S. Y., Guo, Y., & Qin, J. (2020). Promoting Students’ Well-Being by Developing Their Readiness for the Artificial Intelligence Age. Sustainability 2020, Vol. 12, Page 6597, 12(16), 6597. https://doi.org/10.3390/SU12166597
Ding, L., & Zou, D. (2024). Automated writing evaluation systems: A systematic review of Grammarly, Pigai, and Criterion with a perspective on future directions in the age of generative artificial intelligence. Education and Information Technologies, 29(11), 14151–14203. https://doi.org/10.1007/S10639-023-12402-3/TABLES/3
Dong, Y., & Shi, L. (2021). Using Grammarly to support students’ source-based writing practices. Assessing Writing, 50, 100564. https://doi.org/10.1016/J.ASW.2021.100564
Fitria, T. N. (2021). QuillBot as an online tool: Students’ alternative in paraphrasing and rewriting of English writing. Englisia: Journal of Language, Education, and Humanities, 9(1), 183–196. https://doi.org/10.22373/EJ.V9I1.10233
Fitrianto, I. (2024). Innovation and Technology in Arabic Language Learning in Indonesia: Trends and Implications. International Journal of Post Axial: Futuristic Teaching and Learning, 134–150. https://doi.org/10.59944/POSTAXIAL.V2I3.375
Gayed, J. M., Carlon, M. K. J., Oriola, A. M., & Cross, J. S. (2022). Exploring an AI-based writing Assistant’s impact on English language learners. Computers and Education: Artificial Intelligence, 3, 100055. https://doi.org/10.1016/J.CAEAI.2022.100055
Giglio, A. Del, & da Costa, M. U. P. (2023). The use of artificial intelligence to improve the scientific writing of non-native english speakers. Revista Da Associação Médica Brasileira, 69(9), e20230560. https://doi.org/10.1590/1806-9282.20230560
Guerberof-Arenas, A., & Toral, A. (2022). Creativity in translation: Machine translation as a constraint for literary texts. Translation Spaces, 11(2), 184–212. https://doi.org/10.1075/TS.21025.GUE
Hasyim, U. A. F. A., Suhono, S., Anshar, F. A., Sari, Y. A., Puspita, N., Usada, B., & Rozi, F. (2023). Going to Santri International through Upgrade English Productive Skills of Students Islamic Boarding School. Bulletin of Community Engagement, 3(2), 54–62. https://doi.org/10.51278/BCE.V3I2.758
Hobbs, R., Chapman, R., Doerr-Stevens, D., French, C. M., Lynch, S. D., Medina, T. L., Morrell, C., Sloan, E., Stringfellow, C., & Ziemke, L. (2022). Artificial Intelligence in English Education: Challenges and Opportunities for Teachers and Teacher Educators. https://prospect.org/education/multimedia-multiple-
Kastrati, Z., Dalipi, F., Imran, A. S., Nuci, K. P., & Wani, M. A. (2021). Sentiment Analysis of Students’ Feedback with NLP and Deep Learning: A Systematic Mapping Study. Applied Sciences 2021, Vol. 11, Page 3986, 11(9), 3986. https://doi.org/10.3390/APP11093986
Kharisma, B. (2022). Surfing alone? The Internet and social capital: evidence from Indonesia. Journal of Economic Structures, 11(1), 1–17. https://doi.org/10.1186/S40008-022-00267-7/TABLES/6
Lee, H., Phatale, S., Mansoor, H., Lu, K. R., Mesnard, T., Ferret, J., Bishop, C., Hall, E., Carbune, V., & Rastogi, A. (n.d.). RLAIF: Scaling Reinforcement Learning from Human Feedback with AI Feedback.
Lee, S. M. (2022). 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. (2023). The effectiveness of machine translation in foreign language education: a systematic review and meta-analysis. Computer Assisted Language Learning. https://doi.org/10.1080/09588221.2021.1901745
Lee, S. M., & Briggs, N. (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
Li, Y., Garza, V., Keicher, A., & Popov, V. (2019). Predicting High School Teacher Use of Technology: Pedagogical Beliefs, Technological Beliefs and Attitudes, and Teacher Training. Technology, Knowledge and Learning, 24(3), 501–518. https://doi.org/10.1007/S10758-018-9355-2/METRICS
Liang, L. (2024). The impact of using DeepL Translator on Chinese EFL students’ story writing. Journal of China Computer-Assisted Language Learning. https://doi.org/10.1515/JCCALL-2024-0009
Melchers, G., Shaw, P., & Sundkvist, P. (2019). World englishes. World Englishes, 1–246. https://doi.org/10.4324/9781351042581/WORLD-ENGLISHES-PHILIP-SHAW-GUNNEL-MELCHERS-PETER-SUNDKVIST/ACCESSIBILITY-INFORMATION
Mulyani, N., Suhono, S., Pratiwi, W., Sari, Y. A., & Rokhmawan, T. (2024). The Development of English Learning Media through Animated Videos for Student Grade IX Maarif Ansoru Al Hasaniyah Junior High School. International Journal on Advanced Science, Education, and Religion, 7(3), 371–384. https://doi.org/10.33648/IJOASER.V7I3.413
Munir, H., Vogel, B., & Jacobsson, A. (2022). Artificial Intelligence and Machine Learning Approaches in Digital Education: A Systematic Revision. Information 2022, Vol. 13, Page 203, 13(4), 203. https://doi.org/10.3390/INFO13040203
Muthmainnah, Ibna Seraj, P. M., & Oteir, I. (2022). Playing with AI to Investigate Human-Computer Interaction Technology and Improving Critical Thinking Skills to Pursue 21st Century Age. Education Research International, 2022(1), 6468995. https://doi.org/10.1155/2022/6468995
Nazari, N., Shabbir, M. S., & Setiawan, R. (2021). Application of Artificial Intelligence powered digital writing assistant in higher education: randomized controlled trial. Heliyon, 7(5). https://doi.org/10.1016/j.heliyon.2021.e07014
Orishev Jamshid Bahodirovich1, B. R. R. (2021). PROJECT FOR TRAINING PROFESSIONAL SKILLS FOR FUTURE TEACHERS OF TECHNOLOGICAL EDUCATION. Mental Enlightenment Scientific-Methodological Journal, 139–150. http://mentaljournal-jspu.uz/index.php/mesmj/article/view/88
Polakova, P., & Klimova, B. (2023). Using DeepL translator in learning English as an applied foreign language – An empirical pilot study. Heliyon, 9(8). https://doi.org/10.1016/j.heliyon.2023.e18595
Putra, R. M. (2024). Using TikTok as a Media to Enhancing Speaking Skills in English Foreign Language Classroom. Attractive : Innovative Education Journal, 6(3), 232–241. https://doi.org/10.51278/AJ.V6I3.1487
Rivera, E. S., & Garden, C. L. P. (2021). Gamification for student engagement: a framework. Journal of Further and Higher Education, 45(7), 999–1012. https://doi.org/10.1080/0309877X.2021.1875201
Sanusi, T., Suhono, S., Hidayatullah, R., Sari, Y. A., & Hidayah, Y. (2024). Developing of English Vocabulary Material Pocket Book for Pharmacy Vocational School Maarif 5 Kotagajah. International Journal on Advanced Science, Education, and Religion, 7(2), 213–223. https://doi.org/10.33648/IJOASER.V7I2.499
Spiteri, M., & Chang Rundgren, S. N. (2020). Literature Review on the Factors Affecting Primary Teachers’ Use of Digital Technology. Technology, Knowledge and Learning, 25(1), 115–128. https://doi.org/10.1007/S10758-018-9376-X/TABLES/3
Sugiarto, S., & Suhono, S. (2023). Studi Kasus Penggunaan ChatGPT pada Mahasiswa di PTKI Lampung. Jurnal Al-Qiyam, 4(2), 110–119. https://doi.org/10.33648/ALQIYAM.V4I2.318
Teng, M. F. (2024). “ChatGPT is the companion, not enemies”: EFL learners’ perceptions and experiences in using ChatGPT for feedback in writing. Computers and Education: Artificial Intelligence, 7, 100270. https://doi.org/10.1016/J.CAEAI.2024.100270
Tong, S., Jia, N., Luo, X., & Fang, Z. (2021). The Janus face of artificial intelligence feedback: Deployment versus disclosure effects on employee performance. Strategic Management Journal, 42(9), 1600–1631. https://doi.org/10.1002/SMJ.3322
Using an AI-Based Object Detection Translation Application for English Vocabulary Learning on JSTOR. (n.d.). Retrieved January 1, 2025, from https://www.jstor.org/stable/48734318
Voita, E., Sennrich, R., & Titov, I. (2019). When a Good Translation is Wrong in Context: Context-Aware Machine Translation Improves on Deixis, Ellipsis, and Lexical Cohesion. ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference, 1198–1212. https://doi.org/10.18653/v1/p19-1116
Wang, Y., & Stockwell, G. (2024). Training to use machine translation for vocabulary learning. Theory and Practice in Vocabulary Research in Digital Environments, 132–153. https://doi.org/10.4324/9781003367543-9
Webster, R., Fonteyne, M., Tezcan, A., Macken, L., & Daems, J. (2020). Gutenberg Goes Neural: Comparing Features of Dutch Human Translations with Raw Neural Machine Translation Outputs in a Corpus of English Literary Classics. Informatics 2020, Vol. 7, Page 32, 7(3), 32. https://doi.org/10.3390/INFORMATICS7030032
Wulandari, R., Suhono, Hasyim, U. A. F. A., Sari, Y. A., & Hidayat, R. E. (2024). Students Motivation toward the Use of Informatics Technology in Teaching English at MA Ma’arif Roudlotut Tholibin. Bulletin of Pedagogical Research, 4(2), 171–182. https://doi.org/10.51278/BPR.V4I2.1149
Xu, Y. (2022). English Speech Recognition and Evaluation of Pronunciation Quality Using Deep Learning. Mobile Information Systems, 2022(1), 7186375. https://doi.org/10.1155/2022/7186375
Young, A. E. (2024). Machine translation use in the English as a Foreign Language (EFL) classroom. EuroCALL 2023. CALL for All Languages - Short Papers. https://doi.org/10.4995/EUROCALL2023.2023.16862
Yulianto, A., & Supriatnaningsih, R. (2021). Google Translate vs. DeepL: A quantitative evaluation of close-language pair translation (French to English). AJELP: Asian Journal of English Language and Pedagogy, 9(2), 109–127. https://doi.org/10.37134/AJELP.VOL9.2.9.2021
Yuskar, B. O. (2024). The Utilization of Three Writing Schemes (TWS) in Teaching Essay Writing to UBSI Students in English Department. Bulletin of Science Education, 4(1), 24–34. https://doi.org/10.51278/BSE.V4I1.817
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