An Artificial Intelligence-Driven Role-Play-Based Communicative Learning Model for Enhancing Speaking Skills in Arabic Language Education - Mamluatun Ni'mah (Al-Muyassar: Journal of Arabic Education, 2026)
This study aims to enhance students’ Arabic speaking skills through the development and implementation of an Artificial Intelligence (AI)-Driven Role-Playing Communicative Learning model. Conducted through Classroom Action Research (CAR) involving 40 undergraduate students at Zainul Hasan Genggong Islamic University, the study integrates AI-supported role-playing activities via the MemBot feature in the Memrise application. Data were collected through observation, questionnaires, and speaking performance assessments, and analyzed qualitatively. The results reveal that AI-driven role-playing significantly increases students’ motivation and oral proficiency. Crucially, the MemBot feature facilitates a student-centered environment by providing adaptive, real-time feedback and personalized pronunciation correction, allowing learners to engage in authentic conversational contexts without the anxiety often found in traditional settings. This finding confirms that integrating AI with Communicative Language Teaching (CLT) principles creates an interactive, responsive, and transformative pedagogical framework for modern Arabic language education.