Jul 2026· EDUCATUM: Scientific Journal of Education· Vol 4, pp. 65-76· 0 citations
TL;DR
The findings suggest that effective AI integration in Arabic grammar instruction requires a Human-in-the-Loop approach, targeted teacher training, and the development of critical AI literacy among learners.
Abstract
Generative artificial intelligence is increasingly used in Arabic language education, yet its performance in understanding and processing Arabic grammar remains markedly inconsistent. This narrative review examines why AI systems struggle with Arabic grammar and explores the pedagogical implications of these computational limitations. Drawing on 26 primary studies published between 2020 and 2026, the review identifies five interconnected linguistic challenges: the non-linear root-and-pattern morphology of Arabic, the routine omission of diacritics that obscures grammatical case, extensive dialectal diversity, persistent data scarcity, and the syntactic complexity of the i'rab case system. Empirical evidence shows that even advanced models perform substantially worse on morphological and syntactic tasks than on surface-level tasks, with GPT-4o achieving only 67 percent accuracy on Arabic grammar benchmarks and Arabic-specific models scoring considerably lower. The review demonstrates that the structural features of Arabic that make natural language processing difficult are precisely the features that pose risks for learners who depend on AI without critical oversight. These risks include the formation of misconceptions, overreliance on AI-generated outputs, and the erosion of critical thinking and teacher expertise. The findings suggest that effective AI integration in Arabic grammar instruction requires a Human-in-the-Loop approach, targeted teacher training, and the development of critical AI literacy among learners
The results demonstrate that linear discriminative models and appropriate lexical feature engineering can provide a very accurate and interpretable baseline for the development of natural language processing algorithms for Arabic.
Hamood Mohammed Alrumhi, Muhammad Asshad, Amjed Abbas Ahmed et al.· JOIV: International Journal...· 0 citations
The study comes to the conclusion that AI is a powerful instrument for confirming frequency-based linguistic theory but does not model the human cognitive journey.
Assis. lect. Batool Abdul-Mohsin Miri· Journal of College of Educat...· 0 citations
The growing demand for Arabic as a professional language, along with the rapid advancement of Artificial Intelligence (AI) technologies such as ChatGPT, Gemini, and Perplexity, has led to their widespread use among students for translating and composing Arabic assignments. However, these AI tools are often used without critically evaluating the accuracy of their output. Rather than serving merely as learning aids, AI applications are increasingly overused, creating excessive dependence that may ultimately hinder the achievement of Arabic-language-learning objectives. This study aimed to examine the capability and accuracy of ChatGPT, Gemini, and Perplexity in improving the grammatical structure of Arabic writing. This study employed a descriptive quantitative approach to measure and describe the performance of the three AI systems in refining Arabic text structures. The research data consisted of one Arabic composition (insyā’) text, which was revised using ChatGPT, Gemini, and Perplexity. The revised outputs were evaluated by three Arabic language experts using an assessment rubric, and the resulting scores were descriptively analyzed to compare the accuracy levels of the three AI systems. The findings revealed that ChatGPT achieved the highest accuracy score (96.5%), followed by Gemini (75%), while Perplexity obtained the lowest score (63%). These results indicate that ChatGPT demonstrates superior and more consistent performance in improving the grammatical structure of Arabic writing compared to Gemini and Perplexity. Therefore, ChatGPT is considered more suitable as a supporting tool for learning Arabic grammar. Nevertheless, AI-generated corrections should be critically reviewed by users, particularly in formal academic and professional contexts.
Ulfa Muna Kamila, Agus Yasin, C. Rochmat et al.· Priviet Social Sciences Jour...· 0 citations
Investigating Macedonian university students’ perceptions and experiences with AI as a feedback and correction mechanism in the context of L2 grammar mastery revealed that both groups achieved higher accuracy when supported by AI, though language-oriented students showed greater consistency, while non-language-oriented students displayed more variable outcomes.
The findings show that AI-generated texts exhibit greater lexical diversity and syntactic complexity; however, they often exhibit structural uniformity, overuse of cohesive devices, and limited pragmatic depth, and should not replace professionally designed educational materials.
V. Smaglii, T. Korolova, Svitlana Yukhymets et al.· Arab World English Journal· 0 citations
A narrative review compares contemporary Latin Natural Language Processing tools and their use cases for pedagogical applications and concludes that an integrated, multi-tool approach is most effective for supporting Latin pedagogy.
Aidan Han· American Journal of Student...· 0 citations
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