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Generative AI Implementation and Assessment in Arabic Language Teaching

Author

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  • Mozah H. Alkaabi

    (Mohammed bin Zayed University of Humanities, UAE)

  • Asma Saeed Almaamari

    (Mohamed bin Zayed University for Humanities, UAE)

Abstract

Artificial intelligence (AI) models struggle to reach performance levels due to the complex nature of Arabic grammar and diverse regional dialects. This study investigated how generative AI (GenAI) functions as a teaching assistant in Arabic language classrooms. Using qualitative methods, semi-structured interviews were conducted with 15 instructors; the data was then analyzed using thematic analysis. Results revealed that instructors used GenAI to create material, assess students' work, and create personalized learning plans. Instructors struggled, however, with AI accuracy in dialect processing, cultural authenticity, and ensuring accurate assessment methods. The analysis raised significant gaps in teacher training, assessment strategies, and institutional guidelines. Instructors found it challenging to evaluate AI-generated Arabic content across different dialects and maintain academic integrity in student assignments. This study recommends developing instructor training, specifically on using GenAI tools for Arabic dialect variations and creating culturally appropriate Arabic language learning materials.

Suggested Citation

  • Mozah H. Alkaabi & Asma Saeed Almaamari, 2025. "Generative AI Implementation and Assessment in Arabic Language Teaching," International Journal of Online Pedagogy and Course Design (IJOPCD), IGI Global, vol. 15(1), pages 1-18, January.
    • Handle: RePEc:igg:jopcd0:v:15:y:2025:i:1:p:1-18
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