<![CDATA[Background. The integration of Artificial Intelligence (AI) and Big Data in education holds the promise of personalizing learning experiences and improving learning outcomes. The Arabic language, with its unique linguistic structure and complexities, poses specific challenges that these technologies could address. This study explores how AI and Big Data can be leveraged to enhance Arabic language learning, focusing on their potential to improve personalization and effectiveness across both formal and informal learning environments. Purpose. This research aims to investigate the impact of AI and Big Data on Arabic language learning, with an emphasis on the personalization of learning experiences and the enhancement of learning outcomes in both formal and informal educational settings. Method. A mixed-methods approach was employed, involving students from schools, universities, and language learning centers. Participants were divided into two groups: an experimental group utilizing AI and Big Data tools, and a control group relying on traditional teaching methods. Data were collected through pre- and post-test assessments, surveys, and interviews to evaluate learning outcomes and levels of student engagement. Results. The findings indicate a notable improvement in learning outcomes in both formal and informal settings. In formal learning environments, students demonstrated a 22% increase in test scores, while in informal settings, the increase was 18%. Engagement levels were higher in formal settings, with 85% of learners reporting high involvement, compared to 75% in informal settings. Conclusion. AI and Big Data significantly enhance Arabic language learning, particularly in formal educational contexts. The study underscores the importance of tailoring AI and Big Data applications to suit different learning environments for optimal effectiveness. These technologies offer a promising avenue for improving both the personalization and efficacy of language learning.]]>
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