Artificial Intelligence as Linguistic Scaffolding in Mahārah Kalām Learning: Addressing Lexical and Morphosyntactic Challenges
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Abstract
The rapid development of generative artificial intelligence (AI) has created new opportunities for supporting foreign language learning, including Arabic speaking (Mahārah Kalām). However, empirical evidence explaining how students utilize AI to address linguistic challenges during oral language production remains limited. This study explores the use of AI in supporting university students' Arabic speaking learning, focusing on linguistic challenges, AI-assisted learning practices, and perceived changes in learning experiences. A qualitative case study was conducted with ten undergraduate students enrolled in the Arabic Language Education Program at Universitas Islam Negeri Salatiga, Indonesia. Data were collected through semi-structured interviews and participant observation and analyzed using thematic analysis. The findings reveal three dominant forms of AI utilization: supporting vocabulary retrieval, assisting sentence construction based on nahwu and ṣarf, and facilitating students' preparation before speaking activities. The study also indicates that AI helps students access linguistic support more efficiently and enhances their readiness for classroom speaking practices. Nevertheless, lecturer mediation remains essential to validate AI-generated outputs and prevent excessive reliance on technology. These findings suggest that AI should be integrated as a pedagogical support tool rather than a substitute for language instruction in Arabic speaking classrooms.
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