Book
AI-Enhanced Arabic Second Language Acquisition an Integrated Linguistic and Computational Framework
Abdelrahman Mudawi
About This Book
AI-Enhanced Arabic Second Language Acquisition: An Integrated Linguistic and Computational Framework investigates the transformative impact of Artificial Intelligence (AI) on the acquisition of Arabic as a second language. The book develops a unified theoretical and computational model that synthesizes Second Language Acquisition (SLA) theory, Arabic applied linguistics, and AI-driven educational technologies—including Natural Language Processing (NLP), Machine Learning (ML), and Intelligent Tutoring Systems (ITS).
Research ID
Universal Unique Research ID
References
Second Language Acquisition (SLA) & Linguistics
Alhawary, M. (2021). Arabic applied linguistics. Cambridge University Press.
Black, P., & Wiliam, D. (2009). Developing the theory of formative assessment. Educational Assessment, Evaluation and Accountability, 21(1), 5–31.
Canale, M., & Swain, M. (1980). Theoretical bases of communicative approaches to second language teaching and testing. Applied Linguistics, 1(1), 1–47.
Ferguson, C. (1959). Diglossia. Word, 15(2), 325–340.
Krashen, S. (1985). The input hypothesis: Issues and implications. Longman.
Long, M. (1996). The role of the linguistic environment in second language acquisition. In W. Ritchie & T. Bhatia (Eds.), Handbook of second language acquisition. Academic Press.
Ryding, K. (2013). A reference grammar of Modern Standard Arabic. Cambridge University Press.
Selinker, L. (1972). Interlanguage. International Review of Applied Linguistics, 10(3), 209–231.
Swain, M. (2005). The output hypothesis: Theory and research. In E. Hinkel (Ed.), Handbook of research in second language teaching and learning. Routledge.
Taima, R. (2006). Teaching Arabic as a foreign language: Theory and practice. Dar Al-Fikr.
Vygotsky, L. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.
Arabic Linguistics & Arabic NLP
Guellil, I., et al. (2019). Arabic NLP: A survey. Journal/Proceedings.
Habash, N. (2010). Introduction to Arabic natural language processing. Morgan & Claypool.
Madkour, M. (2010). Approaches to teaching Arabic grammar. Journal of Arabic Linguistics, 12(3), 45–67.
Ryding, K. (2013). A reference grammar of Modern Standard Arabic. Cambridge University Press.
AlKhamissi, M., et al. (2024). Advances in Arabic speech recognition and diacritic restoration using transformer models. ACL Proceedings.
Mashaabi, M., et al. (2024). Arabic large language models: A comprehensive survey. arXiv.
Jais 2 Team. (2025). Jais 2: Next generation Arabic large language model. Inria & G42 Research Report.
Artificial Intelligence in Education (AIEd) & Learning Analytics
Baker, R., & Inventado, P. (2014). Educational data mining and learning analytics. In J. Larusson & B. White (Eds.), Learning analytics. Springer.
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.
Kasneci, E., et al. (2023). ChatGPT for good? On opportunities and challenges of large language models for education.
Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. (2016). Intelligence unleashed: An argument for AI in education. Pearson.
Siemens, G. (2013). Learning analytics: The emergence of a discipline. American Behavioral Scientist, 57(10), 1380–1400.
VanLehn, K. (2011). The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems. Educational Psychologist, 46(4), 197–221.
Zawacki-Richter, O., et al. (2024). AI in higher education: Emerging trends and future directions. Springer.
OECD. (2022). AI in education: Policy and practice. OECD Publishing.
Natural Language Processing (NLP) & Machine Learning
Goldberg, Y. (2017). Neural network methods for natural language processing. Morgan & Claypool.
Jurafsky, D., & Martin, J. (2023). Speech and language processing (3rd ed.). Pearson.
Digital Pedagogy & Educational Technology
ALECSO. (2024). Digital transformation in Arabic education.
UNESCO. (2025). Human-centered AI in education: Global policy framework.
Williamson, B., & Eynon, R. (2020). Datafication and education: Critical questions for learning, teaching, and technology. Learning, Media and Technology, 45(1), 3–23.
Ethics, Governance & AI Policy
Floridi, L., & Cowls, J. (2019). A unified framework of five principles for AI in society. Harvard Data Science Review.
Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence, 1(9), 389–399.
OECD. (2019). OECD principles on artificial intelligence. OECD Publishing.
UNESCO. (2021). Recommendation on the ethics of artificial intelligence.
Copyright
© 2026 Mudawi. This is an open-access book distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Abdelrahman Mudawi
Disclaimer
All claims expressed in this book are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this book or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.