Re-examining Quality in AI-Mediated Language Learning: A PLS-SEM Analysis of Pedagogical Alignment, Engagement, and Arabic Language Proficiency - Hendro Risbiyantoro; Nunu Mahnun; Aprijon Efendi; Miftah Hur Rahman Zh; Muhibuddin Fadhli; Zahid Zufar At Thaariq; Aldo Redho Syam; Jimly Assiddiqi (Yayasan Keluarga Guru Mandiri, 2026)
This study examines the effects of AI-based learning tools on Arabic language learning among Arabic students, with student engagement and educational content quality as mediators. This study used a quantitative causal-explanatory design and administered an online questionnaire to students, teachers, and education professionals (N=960). Using Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze the data, there was a large direct positive effect of AI tools on proficiency and an even stronger positive mediating effect of student engagement. Unexpectedly, perceptions of educational content quality were strongly negatively associated with proficiency, suggesting that a mismatch between content design and the learner’s sociocultural context may impede learning even when the pedagogical design is sound. The results highlight that the success of AI in language learning is not merely a function of the state of the technology, but, more importantly, a function of pedagogically sound content and its continued capacity to promote profound engagement. This research enhances the science of technology-enhanced learning by proposing a refined model for English language education in Egypt and by providing implementation-oriented suggestions for furthering practice, calling for a shift from technocentric implementation to learner-centric orchestration of AI in Arabic language education.