<![CDATA[This study aims to map the development and research trends in Arabic language learning through a contrastive analysis using a bibliometric approach. The data were obtained from the Scopus database for the period 2020–2025 using the keywords "contrastive analysis" and "Arabic learning." The analysis was conducted using VOSviewer to identify publication trends, leading contributors, collaboration patterns, and the conceptual structure of the research field. The results indicate a significant increase in publications since 2023, reflecting growing academic interest in this area. Research contributions are predominantly led by Middle Eastern countries, particularly Saudi Arabia, with a strong pattern of collaborative authorship. Thematically, the studies focus on contrastive analysis and error analysis in comparisons between Arabic and English. In addition, there is an emerging trend toward integrating technologies such as artificial intelligence and deep learning. These findings suggest that the field is evolving toward a more interdisciplinary and data-driven approach. These findings indicate that research on contrastive-analysis-based Arabic language learning is evolving toward a more interdisciplinary and data-driven approach. Beyond providing an overview of current research trends and future directions, this study contributes to the development of more effective, evidence-based, and technology-enhanced Arabic language learning practices through the integration of linguistic theory, digital innovation, and learner-centered approaches.]]>
