Fa’aliyah al-Dzaka al-Isthina’iy fi al-Kasyfi ‘an al-Akhta’ al-Nahwiyyah fi al-Kitabat al-Akadimiyyah li Thalabah Marhalah al-Jami’ah al-Uwla / The Effectiveness of Artificial Intelligence in Detecting Arabic Grammatical Errors in Academic Writing among Undergraduate Students

Alfan Putra, Naidin Syamsuddin

Abstract


The teaching of Arabic as a foreign language is undergoing rapid transformation due to advances in artificial intelligence, particularly in natural language processing. The significance of this development lies in the need for effective linguistic assessment tools that enable learners to improve their academic writing performance. This study aims to evaluate the performance of an AI-based system in detecting grammatical errors in academic writings produced by undergraduate students in the Department of Arabic Language. A descriptive-analytical approach was employed, in which thirty samples of student research papers were analyzed automatically using a natural language processing tool, and the results were compared with evaluations made by linguistic experts. Errors were categorized into syntax, morphology, conjunctions, and grammatical consistency. The findings revealed that the AI tool was effective in identifying simple and recurrent errors but faced challenges in handling complex structures and rhetorical expressions. The study highlights the potential of AI as a supportive tool in linguistic assessment, provided that more specialized models are developed to reflect the grammatical and contextual features of Arabic.

يشهد تعليم اللغة العربية للناطقين بغيرها تحوّلات متسارعة بفعل التقدّم التقني في مجالات الذكاء الاصطناعي، خصوصًا أدوات معالجة اللغة الطبيعية. وتبرز أهمية هذا التطور في الحاجة إلى أدوات تقويم لغوي فعالة تمكّن المتعلمين من تحسين إنتاجهم الكتابي الأكاديمي. تهدف هذه الدراسة إلى تقييم أداء نظام ذكاء اصطناعي في الكشف عن الأخطاء النحوية في كتابات أكاديمية لطلبة المرحلة الجامعية الأولى بقسم اللغة العربية. اعتمد البحث المنهج الوصفي التحليلي، حيث خضعت ثلاثون عينة من البحوث الجامعية للتحليل الآلي باستخدام أداة تعتمد تقنيات معالجة اللغة الطبيعية، ثم قورنت النتائج مع تقييمات لغويين مختصين. تم تصنيف الأخطاء إلى فئات تشمل: الإعراب، التراكيب، أدوات الربط، والاتساق النحوي. أظهرت النتائج قدرة الأداة على اكتشاف الأخطاء البسيطة والمتكررة، وصعوبتها في معالجة التراكيب المعقدة والأساليب البلاغية. وتؤكد النتائج إمكانية توظيف الذكاء الاصطناعي في التقويم اللغوي بشرط تطوير نماذج تراعي خصوصية اللغة العربية.


Keywords


Grammatical Errors; Academic Writing; Natural Language Processing

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DOI: https://doi.org/10.36915/la.v6i1.615

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Loghat Arabi: Jurnal Bahasa Arab dan Pendidikan Bahasa Arab,  E-ISSN:2722-1180 | E-ISSN:2722-1199

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