Navigating Student Autonomy: A Review of AI-Integrated Web-Based Strategies in Arabic Language Learning - Iswatun Hasanah; Andre Saputra; Anwar Syafi’i; Fathul Maujud (Sustainable, 2025)
Web-based learning and Artificial Intelligence (AI) have rapidly reshaped Arabic language education in the digital era. This study aims to synthesize findings from national and international literature regarding the role of AI within web-based learning media in strengthening students’ Arabic learning strategies and outcomes. Using a traditional literature review approach, this research analyzes studies focusing on AI applications such as chatbots, Natural Language Processing (NLP), adaptive platforms, and intelligent tutoring systems. The review reveals that AI supports interactivity, personalization, independent learning, and motivation, enabling students to learn Arabic beyond classroom boundaries. However, challenges remain, including limited linguistic resources, dialect variation, ethical concerns, data privacy, and low digital literacy among teachers and students. The study does not develop a learning ecosystem, but instead provides conceptual insights and recommendations for future research and practice. The findings are expected to guide educators, developers, and policymakers in designing more inclusive, adaptive, and ethical AI-supported Arabic language learning environments