Digital Learning to Prevent Arabic Language Fossilization: A Systematic Review

Fossilization is one of the main problems in learning Arabic as a foreign language. It happens when phonological, lexical, and grammatical errors stay in the learner's language even after many corrections. At the same time, the use of digital learning is growing, but its direct potential to prevent fossilization has not been fully explained. This study aims to analyze the role of digital learning strategies in preventing fossilization through a Systematic Literature Review of 30 selected publications from 2015 to 2024. The results show three main trends. The first is the use of LMS and e learning platforms. The second is the integration of artificial intelligence-based tools, such as translanguaging chatbots. The third is the readiness of institutional policies. Further analysis reveals that digital learning can help prevent fossilization through automatic feedback that enhances noticing, adaptive practice that breaks repeated error patterns, and learning environments that provide rich input. The main contribution of this study is the mapping of the direct relationship between digital features such as automatic correction, learning analytics, and AI-based translanguaging and the cognitive mechanisms that support the restructuring of the learner's interlanguage. These findings give a conceptual basis for teachers and institutions to design digital Arabic learning that is more effective and more responsive to linguistic errors.