Integrating Artificial Intelligence into Arabic Language Education: Socio-Technical Perspectives from Islamic Institutions in Southeast Asia

Ridha Darmawaty; Nur Aina  Faqihah; Asep  Sunarko; Yusuf Arisandi

doi:10.23971/jallt.v4i2.536

Authors

Ridha Darmawaty Universitas Islam Negeri Antasari Banjarmasin
Nur Aina Faqihah International Islamic University Malaysia
Asep Sunarko Universitas Sains Al-Quran
Yusuf Arisandi Universitas Islam Internasional Darullughah Wadda’wah

DOI:

https://doi.org/10.23971/jallt.v4i2.536

Keywords:

Arabic education, artificial intelligence, Islamic education, mixed methods, natural language processing

Abstract

This study examines the integration of artificial intelligence (AI) into Arabic language education in Islamic institutions through a multi-site mixed-methods design across Indonesia and Malaysia. Addressing the limited empirical attention to socio-technical, cultural, and religious dimensions of AI-mediated Arabic learning, the study investigates how AI shapes linguistic development, pedagogical practice, learner autonomy, and institutional decision-making. Data were collected from five educational settings: pesantren in Wonosobo and Bangil, UIN Antasari Banjarmasin, UII Darullughah Wadda’wah Pasuruan, and an Islamic institution in Kedah, Malaysia. Classroom observations, interviews, focus group discussions, surveys, digital artifacts, and learning documents were analyzed through triangulation. The findings show that AI supports Arabic learning most effectively as a micro-scaffolding tool for grammar feedback, vocabulary practice, pronunciation support, error detection, and guided interaction. However, its effectiveness depends on teacher mediation, clear learning objectives, and ethical-pedagogical boundaries. Three main constraints emerged: goal diffusion and over-reliance when AI tasks lack guardrails; uneven digital readiness and infrastructure; and persistent inaccuracies in literary, poetic, and classical Arabic texts requiring dzawq lughawī, rhetorical nuance, and religious interpretation. Comparative findings indicate that Indonesian sites adopted AI more progressively through pesantren-based filters, whereas Kedah applied a selective, needs-based approach grounded in traditional learning preferences. Theoretically, this study proposes a socio-technical model that positions AI as a cognitive accelerator within a teacher-led, value-anchored Arabic learning ecosystem. Practically, it offers principles for guardrailed prompting, ethical AI use, teacher capacity-building, and institutionally grounded AI integration.

References

Alasmari, T. (2025). Artificial Intelligence and M-Learning in Arabic Countries: Innovations, Trends, and Regional Perspectives. International Journal of Interactive Mobile Technologies (iJIM), 19(05), 170–194. https://doi.org/10.3991/ijim.v19i05.52735

Alfredo, R., Echeverria, V., Jin, Y., Yan, L., Swiecki, Z., Gašević, D., & Martinez-Maldonado, R. (2024). Human-centred learning analytics and AI in education: A systematic literature review. Computers and Education: Artificial Intelligence, 6, 100215. https://doi.org/10.1016/j.caeai.2024.100215

Alkaabi, M. H., & Almaamari, A. S. (2025). Generative AI Implementation and Assessment in Arabic Language Teaching: International Journal of Online Pedagogy and Course Design, 15(1), 1–18. https://doi.org/10.4018/IJOPCD.368037

Alnajjar, K., & Hämäläinen, M. (2024). Normalization of Arabic Dialects into Modern Standard Arabic using BERT and GPT-2. Journal of Data Mining & Digital Humanities, NLP4DH, 13146. https://doi.org/10.46298/jdmdh.13146

Baxter, G., & Sommerville, I. (2011). Socio-technical systems: From design methods to systems engineering. Interacting with Computers, 23(1), 4–17. https://doi.org/10.1016/j.intcom.2010.07.003

Chan, C. K. Y., & Hu, W. (2023). Students’ voices on generative AI: Perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20(1), 43. https://doi.org/10.1186/s41239-023-00411-8

Chen, L., Chen, P., & Lin, Z. (2020). Artificial Intelligence in Education: A Review. IEEE Access, 8, 75264–75278. https://doi.org/10.1109/ACCESS.2020.2988510

Chiu, T. K. F., Xia, Q., Zhou, X., Chai, C. S., & Cheng, M. (2023). Systematic literature review on opportunities, challenges, and future research recommendations of artificial intelligence in education. Computers and Education: Artificial Intelligence, 4, 100118. https://doi.org/10.1016/j.caeai.2022.100118

Creswell, J. W. (2021). A Concise Introduction to Mixed Methods Research. SAGE Publications, Inc.

Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: The state of the field. International Journal of Educational Technology in Higher Education, 20(1), 22. https://doi.org/10.1186/s41239-023-00392-8

Darvishi, A., Khosravi, H., Sadiq, S., Gašević, D., & Siemens, G. (2024). Impact of AI assistance on student agency. Computers & Education, 210, 104967. https://doi.org/10.1016/j.compedu.2023.104967

Farrokhnia, M., Banihashem, S. K., Noroozi, O., & Wals, A. (2024). A SWOT analysis of ChatGPT: Implications for educational practice and research. Innovations in Education and Teaching International, 61(3), 460–474. https://doi.org/10.1080/14703297.2023.2195846

Godwin-Jones, R. (2022). Partnering with AI: Intelligent Writing Assistance and Instructed Language Learning. Language Learning & Technology, 26(2), 5–24.

Godwin-Jones, R. (2023). Emerging Spaces for Language Learning: AI Bots, Ambient Intelligence, and the Metaverse. Language Learning & Technology, 27(2), 6–27.

Grigoryan, L., Karpov, N., Albasiri, E., Lavrukhin, V., & Ginsburg, B. (2025). Open Automatic Speech Recognition Models for Classical and Modern Standard Arabic. ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 1–5. https://doi.org/10.1109/ICASSP49660.2025.10889643

Hooda, M., Rana, C., Dahiya, O., Rizwan, A., & Hossain, M. S. (2022). Artificial Intelligence for Assessment and Feedback to Enhance Student Success in Higher Education. Mathematical Problems in Engineering, 2022, 1–19. https://doi.org/10.1155/2022/5215722

Hwang, G.-J., & Chang, C.-Y. (2023). A review of opportunities and challenges of chatbots in education. Interactive Learning Environments, 31(7), 4099–4112. https://doi.org/10.1080/10494820.2021.1952615

Kasmaluddin. (2026). Duolingo-Based Arabic Vocabulary Acquisition in Islamic Educational Contexts. Al-Muhawaroh: Jurnal Pendidikan Bahasa Arab, 2(1), 1–11. https://doi.org/10.38073/almuhawaroh.v2i1.4358

Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., … Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274

Kohnke, L., Moorhouse, B. L., & Zou, D. (2023). ChatGPT for Language Teaching and Learning. RELC Journal, 54(2), 537–550. https://doi.org/10.1177/00336882231162868

Levelt, W. (2012). A History of Psycholinguistics: The Pre-Chomskyan Era. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199653669.001.0001

Liang, J.-C., Hwang, G.-J., Chen, M.-R. A., & Darmawansah, D. (2023). Roles and research foci of artificial intelligence in language education: An integrated bibliographic analysis and systematic review approach. Interactive Learning Environments, 31(7), 4270–4296. https://doi.org/10.1080/10494820.2021.1958348

Lo, C. K. (2023). What Is the Impact of ChatGPT on Education? A Rapid Review of the Literature. Education Sciences, 13(4), 410. https://doi.org/10.3390/educsci13040410

Miao, F., & Holmes, W. (2023). Guidance for Generative AI in Education and Research. UNESCO.

Mishra, P., & Koehler, M. J. (2006). Technological Pedagogical Content Knowledge: A Framework for Teacher Knowledge. Teachers College Record: The Voice of Scholarship in Education, 108(6), 1017–1054. https://doi.org/10.1111/j.1467-9620.2006.00684.x

Muhith, M., & Batrisya, N. A. (2026). ‘Lepak’ as a Sociolinguistic Arena: Oral Interaction and Arabic L2 Fluency in Northern Malaysia. Farasyah: Journal of Linguistics and Language Education, 1(1), 19–29.

Mukhasibi, A., & Wahyudi, I. (2026). Immersive Arabic Islamic Environment and Student Engagement: Evaluating the Linguistic Impact of World Arabic Language. Farasyah: Journal of Linguistics and Language Education, 1(1), 1–12.

Ouyang, F., & Jiao, P. (2021). Artificial intelligence in education: The three paradigms. Computers and Education: Artificial Intelligence, 2, 100020. https://doi.org/10.1016/j.caeai.2021.100020

Priyanda, R., Herman, T., Amalia, R., & Ihsan, I. R. (2025). Exploring teachers’ pedagogical reasoning in mathematics education using the TPACK framework. Frontiers in Education, 10, 1552760. https://doi.org/10.3389/feduc.2025.1552760

Sahrir, M. S., Muharom Albantani, A., Arifin, F., & Din, F. (2025). The Use of Generative Artificial Intelligence (AI) in Arabic Language Education: Insights and Implications between Malaysia and Indonesia. International Journal of Research and Innovation in Social Science, IX(III), 3638–3646. https://doi.org/10.47772/IJRISS.2025.90300288

Shi, H., & Aryadoust, V. (2024). A systematic review of AI-based automated written feedback research. ReCALL, 36(2), 187–209. https://doi.org/10.1017/S0958344023000265

Strzelecki, A. (2024). Students’ Acceptance of ChatGPT in Higher Education: An Extended Unified Theory of Acceptance and Use of Technology. Innovative Higher Education, 49(2), 223–245. https://doi.org/10.1007/s10755-023-09686-1

Su, J., & Yang, W. (2023). Unlocking the Power of ChatGPT: A Framework for Applying Generative AI in Education. ECNU Review of Education, 6(3), 355–366. https://doi.org/10.1177/20965311231168423

Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang, B. (2023). What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education. Smart Learning Environments, 10(1), 15. https://doi.org/10.1186/s40561-023-00237-x

Wang, B., Rau, P.-L. P., & Yuan, T. (2023). Measuring user competence in using artificial intelligence: Validity and reliability of artificial intelligence literacy scale. Behaviour & Information Technology, 42(9), 1324–1337. https://doi.org/10.1080/0144929X.2022.2072768

Wang, X., Xu, X., Zhang, Y., Hao, S., & Jie, W. (2024). Exploring the impact of artificial intelligence application in personalized learning environments: Thematic analysis of undergraduates’ perceptions in China. Humanities and Social Sciences Communications, 11(1), 1644. https://doi.org/10.1057/s41599-024-04168-x

Wardhaugh, R., & Fuller, J. M. (2014). An Introduction to Sociolinguistics. Wiley.

Weng, Z., & Fu, Y. (2025). Generative AI in Language Education: Bridging Divide and Fostering Inclusivity. International Journal of Technology in Education, 8(2), 395–420. https://doi.org/10.46328/ijte.1056

Xiao, Y. (2025). The impact of AI-driven speech recognition on EFL listening comprehension, flow experience, and anxiety: A randomized controlled trial. Humanities and Social Sciences Communications, 12(1), 425. https://doi.org/10.1057/s41599-025-04672-8

Zou, B., Du, Y., Wang, Z., Chen, J., & Zhang, W. (2023). An Investigation Into Artificial Intelligence Speech Evaluation Programs With Automatic Feedback for Developing EFL Learners’ Speaking Skills. Sage Open, 13(3), 21582440231193818. https://doi.org/10.1177/21582440231193818

Zubaidi, A., Munip, A., Widodo, S. A., & Zerrouki, T. (2025). Enhancing Arabic writing skills using Chat GPT-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