Reviving the Arabic Language Instinct: A Psycholinguistic and AI Synergy
DOI:
https://doi.org/10.58223/al-wazan.v3i1.338Keywords:
AI in education, Psycholinguistics, Arabic language instinctAbstract
The integration of artificial intelligence (AI) in education has sparked new possibilities for enhancing language acquisition; however, its rapid advancement poses challenges when not harmonized with cognitive and psychological readiness. This study investigates how psycholinguistic principles, when paired with AI tools, can foster the development of Arabic language instinct among advanced learners. The research focuses on 50 participants from Pondok Pesantren Darullughah Wadda’wah, utilizing a mixed-methods approach that combines quantitative data collection with qualitative classroom observations and interviews. The results show significant linguistic improvements: grammar proficiency increased from 68% to 85%, vocabulary retention improved by 40%, and learners’ speaking confidence rose by 30%. A critical finding of this study is the role of dzauq—a form of linguistic and cultural intuition—in enhancing language depth and sensitivity. AI-based applications, such as adaptive feedback systems and speech simulators, proved effective in improving learner engagement, responsiveness, and self-correction capabilities. Nonetheless, the tools still face limitations, especially in accurately capturing dialectal variety and cultural semantics inherent in Arabic. This research contributes to the growing body of literature on language pedagogy and artificial intelligence by proposing a model that integrates psycholinguistic insight with AI-enabled learning. It highlights the necessity of balancing technological advancement with human-centered strategies rooted in linguistic identity and cultural authenticity. Ultimately, the study offers a transformative framework for Arabic language education that prioritizes both intuitive fluency and ethical, context-aware technology integration.
References
Al-Qatawneh, S. S., Alsalhi, N. R., Eltahir, Mohd. E., & Siddig, O. A. (2021). The representation of multiple intelligences in an intermediate Arabic-language textbook, and teachers’ awareness of them in Jordanian schools. Heliyon, 7(5), e07004. https://doi.org/10.1016/j.heliyon.2021.e07004
Bakkalbasioglu, E. (2020). How to Access Elites When Textbook Methods Fail? Challenges of Purposive Sampling and Advantages of Using Interviewees as “Fixers.” The Qualitative Report. https://doi.org/10.46743/2160-3715/2020.3976
Candra Susanto, P., Yuntina, L., Saribanon, E., Panatap Soehaditama, J., & Liana, E. (2024). Qualitative Method Concepts: Literature Review, Focus Group Discussion, Ethnography and Grounded Theory. Siber Journal of Advanced Multidisciplinary, 2(2), 262–275. https://doi.org/10.38035/sjam.v2i2.207
Creswell, J. W. (2021). A Concise Introduction to Mixed Methods Research. SAGE Publications, Inc.
Godfroid, A., & Hopp, H. (2023). The Routledge Handbook of Second Language Acquisition and Psycholinguistics. Routledge.
Hanifansyah, N., & Mahmudah, M. (2024). Enhancing Arabic Vocabulary Mastery Through Communicative Strategies: Evidence from Malaysia. Al-Ta’rib : Jurnal Ilmiah Program Studi Pendidikan Bahasa Arab IAIN, 12((2)), 263–278. https://doi.org/10.23971/altarib.v12i2.9082
Haque, M. U., Dharmadasa, I., Sworna, Z. T., Rajapakse, R. N., & Ahmad, H. (2022). “I think this is the most disruptive technology”: Exploring Sentiments of ChatGPT Early Adopters using Twitter Data (Version 1). arXiv. https://doi.org/10.48550/ARXIV.2212.05856
Mahmudah, M., & Hanifansyah, N. (2024). Implementation of the Jigsaw Learning Method for Maharah Qiro’ah Learning at MA As-Sholach, Kejeran Boyeman, Gondangwetan, Pasuruan. Lughawiyah: Journal of Arabic Education and Linguistics, Universitas Islam Negeri Mahmud Yunus Batusangkar, Indonesia, Vol 6(No 2), 165–184. http://dx.doi.org/10.31958/lughawiyah.v6i2.13456
Nur Hanifansyah, Mahmudah, M., & Syakur, S. A. (2024). Peer Tutoring as a Collaborative Approach in Arabic Language Learning. Lahjatuna: Jurnal Pendidikan Bahasa Arab, 4(1), 26–43. https://doi.org/10.38073/lahjatuna.v4i1.2181
Shahbari-Kassem, A., Schiff, R., & Saiegh-Haddad, E. (2024). Development of morphological awareness in Arabic: The role of morphological system and morphological distance. Reading and Writing. https://doi.org/10.1007/s11145-024-10581-0
Solehudin, M., & Arisandi, Y. (2024). Language Interference in Arabic Learning: A Case Study of Islamic Boarding Schools in Indonesia. Al-Ta’rib : Jurnal Ilmiah Program Studi Pendidikan Bahasa Arab IAIN Palangka Raya, 12(2), 423–438. https://doi.org/10.23971/altarib.v12i2.9170
Soliman, R., & Khalil, S. (2024). The teaching of Arabic as a community language in the UK. International Journal of Bilingual Education and Bilingualism, 27(9), 1246–1257. https://doi.org/10.1080/13670050.2022.2063686
Xu, W., Dainoff, M. J., Ge, L., & Gao, Z. (2023). Transitioning to Human Interaction with AI Systems: New Challenges and Opportunities for HCI Professionals to Enable Human-Centered AI. International Journal of Human–Computer Interaction, 39(3), 494–518. https://doi.org/10.1080/10447318.2022.2041900
Antoun, W., Baly, F., & Hajj, H. (2020). AraBERT: Transformer-based Model for Arabic Language Understanding. arXiv preprint arXiv:2003.00104. https://arxiv.org/abs/2003.00104arXiv
Aziz, M. T., Al-Firdausy, M. K. H., & Syafi'i, M. (2022). Learning Listening and Reading Skills from the Arabic Language in a Psycholinguistic Perspective. AL-ISHLAH: Jurnal Pendidikan, 14(4). https://journal.staihubbulwathan.id/index.php/alishlah/article/view/2296Jurnal STAI Hubbulwathan+1Jurnal STAI Hubbulwathan+1
El Zahraa, F. (2024). Leveraging Artificial Intelligence and Digital Technologies to Enhance Sociolinguistic Competence and Arabic Language Skills. Proceedings of ICRECCU. https://prosiding.aripafi.or.id/index.php/ICRECCU/article/view/22prosiding.aripafi.or.id
Inoue, G., Khalifa, S., & Habash, N. (2021). Morphosyntactic Tagging with Pre-trained Language Models for Arabic and its Dialects. arXiv preprint arXiv:2110.06852. https://arxiv.org/abs/2110.06852arXiv
Mushtofa, T., & Rosyadi, F. I. (2022). The Role of Language Acquisition Device Theory in Second Language Learning: A Case Study of Arabic Language Learners. IMRECS Journal, 2(1). https://imrecsjournal.com/journals/index.php/bsscd/article/view/159imrecsjournal.com+1ResearchGate+1
Tager, M. (2024). AI in Arabic Teaching and Learning. Alefb. https://www.alefb.org/ai-in-arabic-teaching-and-learning/alefb.org
Terbeh, N., & Zrigui, M. (2012). Arabic Language Learning Assisted by Computer, based on Automatic Speech Recognition. arXiv preprint arXiv:1205.3316. https://arxiv.org/abs/1205.3316arXiv
Zulkhairi, Z., Azwir, A., & Zulhelmi, Z. (2024). Using Artificial Intelligence in Arabic Learning: Opportunities and Challenges. EL-MAQALAH: Journal of Arabic Language Teaching and Linguistics, 5(2). https://journal.ar-raniry.ac.id/MAQALAH/article/view/6219
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Nur Hanifansyah

This work is licensed under a Creative Commons Attribution 4.0 International License.
Al-Wazan: Journal of Arabic Education diterbitkan berdasarkan ketentuan Creative Commons Attribution 4.0 International License / CC BY 4.0 Lisensi ini mengizinkan setiap orang untuk menyalin dan menyebarluaskan kembali materi ini dalam bentuk atau format apapun, menggubah, mengubah, dan membuat turunan dari materi ini untuk kepentingan apapun, termasuk kepentingan komersial, selama mereka mencantumkan kredit kepada Penulis atas ciptaan asli.
