Exploring Arabic Language Learning in the Age of AI Chatbots: A Conceptual Framework

Abstract

Today’s advancement of artificial intelligence (AI) has brought up conversational chatbots as emerging tools in language education, yet their pedagogical role in Arabic language learning is still lacking theoretical grounding. Arabic language presents unique instructional challenges, including diglossia, complex morphology, and limited opportunities for authentic interaction, particularly for learners of Arabic as a foreign language. This conceptual paper aims at determining the pedagogical potential of AI chatbots in supporting Arabic language learning as well as proposing a conceptual framework that integrates AI chatbots into Arabic language education based on established language learning theories that integrates pedagogical, linguistic, and affective dimensions. Drawing on established theories in second language acquisition, including sociocultural theory, communicative language teaching, and affective filter hypothesis, this study adopts a systematic conceptual analysis of prior literature on AI-assisted language learning and Arabic pedagogy. This study proposes a conceptual framework illustrating how AI chatbots can function as scaffolding agents, interactional partners, and personalised learning facilitators. The findings feature the potential of AI chatbots to enhance learner engagement, reduce anxiety, and support communicative competence in Arabic, while also acknowledging pedagogical and ethical considerations.

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