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The ‘AI-Powered’ Madrasa: Efficacy of Personalized AI Tutors for Qur’anic Memorization and Arabic Language Learning Zarfi, Syarifatul Hayati; Omar, Ali; Mohammed, Samira
Islamic Studies in the World Vol. 2 No. 5 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/isw.v2i5.2940

Abstract

The integration of artificial intelligence (AI) into Islamic education has introduced new opportunities for enhancing Qur’anic memorization (tahfiz) and Arabic language learning through personalized, adaptive technologies. Traditional madrasa models rely heavily on direct teacher–student interaction, repetition-based practice, and individualized correction, yet often face constraints related to limited teaching time, large class sizes, and diverse learner abilities. Recent advancements in AI-driven tutoring systems provide alternative pathways for supporting memorization accuracy, pronunciation refinement, and grammar acquisition, offering a scalable solution aligned with contemporary educational needs. This study aims to evaluate the efficacy of personalized AI tutors in improving Qur’anic memorization performance and foundational Arabic language competency among madrasa students. The research investigates how AI-generated feedback, adaptive pacing, and real-time voice recognition contribute to learner progress, motivation, and error reduction within tahfiz and language-learning contexts. A quasi-experimental design was employed involving two groups: an experimental group using AI-powered tutoring applications and a control group engaging in conventional instructional methods. Data were collected through pre-tests and post-tests in Qur’anic memorization fluency, tajw?d accuracy, and basic Arabic vocabulary and grammar assessments. Additional qualitative data were gathered from student reflections and teacher interviews. The results demonstrate that students in the AI-assisted group achieved significantly higher gains in memorization retention, pronunciation accuracy, and vocabulary mastery compared to the control group. Learners also reported increased engagement, reduced anxiety, and enhanced autonomy in their study routines. The findings highlight the pedagogical value of AI tutors in complementing traditional madrasa teaching practices. The study concludes that AI-powered personalized tutoring systems can serve as effective supplementary tools for Qur’anic and Arabic instruction, provided that implementation aligns with ethical, pedagogical, and cultural considerations.
Structural Engineering Analysis and Seismic Retrofitting of Historical Mosque Minarets in the Indonesian Archipelago Setyobudi, Risang; Mohammed, Samira; Bakker, Anna
Journal of Moeslim Research Technik Vol. 2 No. 6 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/technik.v2i6.2629

Abstract

Historical mosque minarets in the Indonesian archipelago, vital components of cultural heritage, are situated in a high-seismicity region. Their unreinforced masonry (URM) construction presents a significant, yet unquantified, vulnerability, posing threats to public safety and heritage preservation. This study provides a quantitative structural engineering analysis to assess this seismic vulnerability and establish a methodological framework for evaluating seismic retrofitting interventions. A diagnosis-led approach was employed, integrating in-situ non-destructive diagnostics (NDT), ambient vibration testing (AVT) for dynamic characterization, and advanced non-linear finite element modeling (FEM) on representative case-study structures. Results reveal a critical gap between structural capacity and seismic demand. The models predict catastrophic failure at low peak ground accelerations (0.15g), far below the 500-year hazard level (>0.40g). Unique Indonesian materials (volcanic stone, weak mortar) render existing international fragility models inadequate for this typology. Indonesian minarets possess critical seismic deficiencies requiring urgent, scientifically-grounded intervention. The validated models serve as essential tools for designing and testing culturally appropriate, minimally invasive retrofitting strategies to ensure the preservation of this irreplaceable built heritage.