Analisis Kesalahan dalam Karangan Pembelajar Bahasa Jepang Penutur Indonesia dalam konteks pembelajaran yang berpotensi melibatkan AI
DOI:
https://doi.org/10.69908/nawa.v3i1.49987Keywords:
error analysis, Japanese learner writing, Japanese language education, artificial intelligence (AI) in writingAbstract
This study aims to identify the characteristics of errors that commonly occur in the written compositions of intermediate-level Japanese language learners at the tertiary level in Indonesia. The participants were third-year students (fifth semester) enrolled in the Japanese Literature Program, Faculty of Cultural Sciences, Universitas Hasanuddin, who took the Japanese Composition course during the odd semester of the 2025/2026 academic year. The data analyzed consisted of in-class writing assignments (Compositions 3–5) and final examination compositions. Compositions 1 and 2 were excluded from the analysis because, at that stage, students had not yet received instruction on the use of genkōyōshi and paragraph structure. Compositions 3–5 were produced through a staged instructional process that included teacher guidance on writing, draft preparation, and group-based revision through peer response activities. In contrast, the final examination compositions were written under time constraints, with a 50-minute limit and without access to dictionaries or other reference materials. In this study, the analysis focused exclusively on errors that appeared repeatedly and were shared by multiple learners, while individual or incidental errors were excluded from consideration. The findings indicate that errors related to basic grammatical aspects, such as particle usage and verb conjugation, were relatively limited. By contrast, errors associated with the use of genkōyōshi, paragraph organization, stylistic choices, and the mixing of written and spoken language were consistently observed. This article further discusses the underlying factors contributing to these errors by considering instructional practices, differences in writing conditions between assignments and examinations, and the potential influence of artificial intelligence technologies in the writing process, which is interpreted as a contextual consideration based on the learning environment rather than as an empirically verified finding of this study.
References
Corder, S. P. (1981). Error analysis and interlanguage. Oxford University Press.
Ellis, R. (1997). Second language acquisition. Oxford University Press.
Hyland, K. (2004). Second language writing. Cambridge University Press.
Kusumawati, M. (2019). An inquiry on Japanese language education in Indonesia: A focus on the curriculum and its implementation. JAPANEDU: Jurnal Pendidikan dan Pengajaran Bahasa Jepang, 4(1), 1–6.
https://doi.org/10.17509/japanedu.v4i1.16658
Ranalli, J., Link, S., & Chukharev-Hudilainen, E. (2023). Exploring L2 writers’ use of GPT-based AI writing tools. Computer Assisted Language Learning. Advance online publication.
https://doi.org/10.1080/09588221.2023.2199706
Sari, R. P., & Natsuko, O. (2021). Analisis kesalahan gramatikal dalam karangan bahasa Jepang pembelajar tingkat menengah. Jurnal Pendidikan Bahasa Jepang, 7(2), 85–95.
https://doi.org/10.23887/jpbj.v7i2.34912
Sugiyono. (2019). Metode penelitian kualitatif, kuantitatif, dan R&D (Cet. ke-26). Alfabeta.
Sutedi, D. (2011). Penelitian pendidikan bahasa Jepang. Humaniora Utama Press.
The Japan Foundation. (2023). Survey report on Japanese-language education abroad 2021. The Japan Foundation.
https://www.jpf.go.jp/e/project/japanese/survey/result/dl/survey2021/All_contents_r2.pdf
Zhang, Z., & Hyland, K. (2022). Fostering learner engagement with feedback: The role of automated writing evaluation. Journal of Second Language Writing, 56, 100872.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Haruna Fukuda

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




