This study aims to analyze the development of scientific publications on Arabic grammar in language learning, identify trends, patterns, and main themes in related research, and identify opportunities and directions for future research. It applies a descriptive quantitative method using scientific publication data collected from the Scopus database through the Publish or Perish application. The search conducted on April 9, 2026, identified 152 documents with a total of 419 citations. After a filtering process, 10 highly cited articles were selected as the main objects of analysis. The bibliometric analysis follows the Fahimnia framework, including data identification, screening, analysis, and visualization. VOSviewer software was used to map research networks through keyword co-occurrence analysis. The results show that Arabic grammar studies in language learning are still dominated by theoretical and analytical approaches, mainly focusing on aspects such as approach, grammar, and analysis. The visualization reveals several research clusters that highlight connections between learning approaches, language structures, and linguistic analysis, although practical implementation and evaluation aspects remain limited. Additionally, there is a growing trend in the use of technology, including artificial intelligence, machine learning, and digital learning systems in teaching Arabic grammar. The study concludes that this field is still developing, with broad opportunities for innovation, especially in practical applications and technology-based learning models.
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