Generative AI in Arabic Grammar Learning: A Critical Review of Pedagogical Benefits and Linguistic Limitations

https://doi.org/10.56113/takuana.v5i1.493

Authors

International Islamic University Malaysia, Malaysia
×

Muhammad Fariq Heemal Attruk

International Islamic University Malaysia, Malaysia
International Islamic University Malaysia, Malaysia
×

Nik Hanan Mustapha

International Islamic University Malaysia, Malaysia

Abstract

The rapid development of generative artificial intelligence (AI) has significantly influenced Arabic language education, particularly in the learning of nahwu (syntax) and shorof (morphology). This study aims to critically examine the pedagogical benefits and linguistic limitations of generative AI in Arabic grammar learning through a narrative literature review approach. The study analyzes recent scholarly works on AI-assisted Arabic language instruction and grammatical analysis. The findings reveal that generative AI supports independent learning, provides immediate feedback, and increases learner engagement. However, persistent limitations remain in handling complex syntactic structures, contextual ambiguity, and accurate grammatical interpretation. The review also highlights concerns regarding learners’ overreliance on AI and the continuing need for teacher supervision. The study concludes that generative AI should function as a supportive instructional tool rather than a fully autonomous learning authority in Arabic grammar education.

Keywords


generative artificial intelligence, Arabic grammar learning, nahwu, shorof, AI-assisted learning, pedagogical implications

References

Abdelrehim, M., Torki, M., & El-Makky, N. (2025). Hybrid LLM and rule-based synthetic data generation for Arabic grammatical error correction. In 2025 International Conference on Machine Intelligence and Smart Innovation (ICMISI). IEEE. https://doi.org/10.1109/ICMISI65108.2025.11115884

Adawiyah, R. (2025). Implementing AI in Arabic language learning: Challenges and insights from Islamic higher education. Al-Ishlah: Jurnal Pendidikan, 17(3), 3729–3739. https://doi.org/10.35445/alishlah.v17i3.7390

Adel, M., Alhafni, B., & Habash, N. (2026). Arabic morphosyntactic tagging and dependency parsing with large language models [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2603.16718

Albantani, A. M., Rozak, A., Sahrir, M. S., & Khoiriyyah, B. (2025). The influence of generative AI on student engagement and academic outcomes in Arabic language learning. Asalibuna, 9(2), 149–163. https://doi.org/10.30762/asalibuna.v9i02.6810

Al-Jamali, S., & Abdalla, S. Z. S. (2025). Behavioral determinants of AI-driven Arabic language learning: Insights from the extended UTAUT2 model. Educational Process: International Journal, 16, Article e2025282. https://doi.org/10.22521/edupij.2025.16.282

Al-Jarf, R. (2025). Specific linguistic questions that artificial intelligence (AI) cannot answer accurately: Implications for digital didactics. Frontiers in Computer Science and Artificial Intelligence, 4(4), 43–61. https://doi.org/10.32996/fcsai.2025.4.4.4

Alkaabi, M. H., & Almaamari, A. S. (2025). Generative AI implementation and assessment in Arabic language teaching. International Journal of Online Pedagogy and Course Design (IJOPCD), 15(1), 1–18.

Baalbaki, R. (2019). Arabic linguistic tradition I: Naḥw and ṣarf. In J. Owens (Ed.), The Oxford handbook of Arabic linguistics (pp. 7–21). Oxford University Press.

Baumeister, R. F., & Leary, M. R. (1997). Writing narrative literature reviews. Review of General Psychology, 1(3), 311–320. https://doi.org/10.1037/1089-2680.1.3.311

Falagas, M. E., Pitsouni, E. I., Malietzis, G. A., & Pappas, G. (2008). Comparison of PubMed, Scopus, Web of Science, and Google Scholar: Strengths and weaknesses. The FASEB Journal, 22(2), 338–342. https://doi.org/10.1096/fj.07-9492LSF

Ferrari, R. (2015). Writing narrative style literature reviews. Medical Writing, 24(4), 230–235. https://doi.org/10.1179/2047480615Z.000000000329

Grant, M. J., & Booth, A. (2009). A typology of reviews: An analysis of 14 review types and associated methodologies. Health Information and Libraries Journal, 26(2), 91–108. https://doi.org/10.1111/j.1471-1842.2009.00848.x

Karima, S. R., Edidarmo, T., & Raswan. (2025). A comparison of the accuracy of generative artificial intelligence models in taṣrīf and the explanation of wazan meanings: A study on their application in Arabic morphology (ṣarf). JALSAT Journal of Arabic Language Studies and Teaching, 5(2), 234–250. https://doi.org/10.15642/jalsat.2025.5.2.234-250

Kwon, S. Y., Bhatia, G., Nagoudi, E. M. B., & Abdul-Mageed, M. (2023). ChatGPT for Arabic grammatical error correction [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2308.04492

Linur, R., Rusdi, T., Lubis, T., & Rohman, K. S. (2025). Student perception analysis of AI's impact on Arabic language learning: A personality perspective. Jurnal Al Bayan: Jurnal Jurusan Pendidikan Bahasa Arab, 17(2), 312–328. https://doi.org/10.24042/fya8h073

Morrison, A., Polisena, J., Husereau, D., Moulton, K., Clark, M., Fiander, M., Mierzwinski-Urban, M., Clifford, T., Hutton, B., & Rabb, D. (2012). The effect of English-language restriction on systematic review–based meta-analyses: A systematic review of empirical studies. International Journal of Technology Assessment in Health Care, 28(2), 138–144. https://doi.org/10.1017/S0266462312000086

Nugraha, A., & Syafe'i, I. (2025). Curriculum foundations for Arabic language education in the AI era: Holistic, juridical, and technological perspectives. Journal of Arabic Language Learning and Teaching (JALLT), 3(2), 151–160. https://ejournal.iain-palangkaraya.ac.id/index.php/jallt

Othman, A. M. W., & Asbulah, L. H. B. (2025). Problems of artificial intelligence applications in digitizing the Arabic language in the areas of grammar and morphology and methods to resolve it. IJAZ ARABI: Journal of Arabic Learning, 8(2), 721–740. https://doi.org/10.18860/ijazarabi.V8i2.31596

Rahmaddani, A., & Naifah. (2025). Students' perspectives on the use of Chat-GPT in the fields of phonology, morphology, and syntactics in Arabic language learning. Journal of Islamic Education Thought and Development, 1(1), 48–60.

Rahmouni, K. (2024). Exploring the use of ChatGPT in teaching Arabic case endings: Effectiveness, challenges and recommendations. Journal of Educational Technology and Innovation, 6(4), 1–18.

Rishanda, A. T., Koderi, F. G., & Mizan, A. N. (2025). Artificial intelligence dalam pembelajaran nahwu secara mandiri. Al Mi'yar: Jurnal Ilmiah Pembelajaran Bahasa Arab dan Kebahasaaraban, 8(1), 27–39. https://doi.org/10.35931/am.v8i1.4594

Rizki, R. B., Rizal, M. F., Rahmawati, C., Bachrudin, M. A., Farhani, S., & Batul, Z. (2025). Qalam Al: A study on the potential of automatic harakat detection for Arabic sentence learning. Alsina: Journal of Arabic Studies, 7(2), 285–316. https://doi.org/10.21580/alsina.7.2.27500

Sa'idah, M. A., Dolan, E., Diantoro, K., Santoso, N. A., Mahmudah, U., & Junaedi, S. R. P. (2024). Enhancing Arabic language teaching through artificial intelligence: Assessing effectiveness and educational implications. In 2024 3rd International Conference on Creative Communication and Innovative Technology (ICCIT) (pp. 1–8). IEEE. https://doi.org/10.1109/ICCIT62134.2024.10701089

Tamam, M. I., Ilahi, M. M. K., Cholilah, Z., Taufiqurrochman, R., & Machmudah, U. (2024). Utilizing ChatGPT for analyzing Arabic texts in the study of nahwu (Arabic grammar). KITABA: Journal of Interdisciplinary Arabic Learning, 2(3), 193–208. https://doi.org/10.18860/kitaba.v2i3.28463

Zubaidi, A., Munip, A., Widodo, S. A., & Zerrouki, T. (2025). Enhancing Arabic writing skills using ChatGPT-based AI learning models: A tridimensional human-AI collaboration framework. Indonesian Journal of Applied Linguistics, 15(1), 87–101. https://doi.org/10.17509/ijal.v15i1.75378

Downloads

Full Text Download

Published

June 17, 2026

How to Cite

Attruk, M. F. H., & Mustapha, N. H. (2026). Generative AI in Arabic Grammar Learning: A Critical Review of Pedagogical Benefits and Linguistic Limitations. Takuana: Jurnal Pendidikan, Sains, Dan Humaniora, 5(1), 577–594. https://doi.org/10.56113/takuana.v5i1.493

License


Creative Commons License

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

All published content in Takuana: Jurnal Pendidikan, Sains, dan Humaniora is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY NC SA 4.0). This license allows others to share, copy, redistribute, and adapt the work for non-commercial purposes, as long as proper credit is given to the original author(s) and source, and any derivative works are distributed under the same license.

Attribution must include a clear citation of the original work and a statement indicating whether any changes were made. Commercial use is not permitted under this license and there is no additional legal or technological restrictions may be applied. For more information about the license terms and permissible use, please refer to the full license text available here.