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All Journal Al-Hijr: Journal of Adulearn World Journal International of Lingua and Technology Journal International Inspire Education Technology (JIIET) World Psychology Islamic Studies in the World
Syarifatul Hayati Zarfi
Universitas Islam Negeri Mahmud Yunus Batusangkar
Religion Computer Science & IT Education Languange, Linguistic, Communication & Media Social Sciences Other

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The ‘AI-Powered’ Madrasa: Efficacy of Personalized AI Tutors for Qur’anic Memorization and Arabic Language Learning Syarifatul Hayati Zarfi; Ali Omar; Samira Mohammed
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.
EXPLORING THE ROLE OF EMOTIONAL INTELLIGENCE IN ADOLESCENT DEVELOPMENT: IMPLICATIONS FOR EDUCATIONAL PRACTICES Rinovian Rais; Syarifatul Hayati Zarfi; Nina Anis
World Psychology Vol. 5 No. 1 (2026)
Publisher : Sekolah Tinggi Agama Islam Al-Hikmah Pariangan Batusangkar, West Sumatra, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55849/wp.v5i1.1222

Abstract

Emotional intelligence (EI) is increasingly recognized as a critical factor in adolescent development, influencing various aspects of social, emotional, and academic growth. Adolescence is a developmental stage marked by significant emotional and social changes, which makes the role of EI in shaping behavior and decision-making particularly important. Understanding how EI contributes to adolescent development can help inform educational practices aimed at fostering emotional and social competencies. This study explores the role of EI in adolescent development and its implications for educational practices. The research employs a mixed-methods approach, combining quantitative assessments of EI using the Bar-On Emotional Quotient Inventory (EQ-i:YV) and qualitative interviews with teachers and students. The findings indicate that higher EI levels are associated with better academic performance, enhanced peer relationships, and improved emotional regulation. Adolescents with higher EI demonstrated greater resilience in managing stress and navigating social conflicts. The study concludes that incorporating EI-focused strategies into educational curricula can enhance students' emotional and social development, thereby improving both academic outcomes and overall well-being. The study suggests that emotional intelligence should be a central component of educational practices to support holistic adolescent development.
GENERATIVE AI FOR CONTENT CREATION IN EDUCATION: TAILORING LEARNING MATERIALS TO INDIVIDUAL NEEDS Roni Subhan; Syarifatul Hayati Zarfi; Pong Krit
Al-Hijr: Journal of Adulearn World Vol. 5 No. 3 (2026)
Publisher : Sekolah Tinggi Agama Islam Al-Hikmah Pariangan Batusangkar, West Sumatra, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55849/alhijr.v5i3.1315

Abstract

Growing diversity in learner characteristics, educational backgrounds, cognitive abilities, and learning preferences has increased the demand for adaptive instructional materials capable of supporting personalized learning experiences. Rapid advances in Generative Artificial Intelligence (Generative AI) provide new opportunities to automate educational content creation while tailoring learning resources to individual learner needs, although questions concerning instructional quality, pedagogical effectiveness, and responsible implementation remain unresolved. This study aimed to examine the effectiveness of Generative AI for developing personalized educational content and to evaluate its contribution to teaching and learning within higher education. A mixed-methods sequential explanatory design was employed, integrating quantitative evidence from learning analytics, standardized academic assessments, instructional quality measures, and technology acceptance surveys with qualitative data collected through interviews, classroom observations, reflective journals, and instructional document analysis. Findings revealed that AI-generated personalized learning materials significantly improved academic achievement, learner engagement, creativity, self-regulated learning, instructional quality, learning satisfaction, and course completion when supported by educator supervision and curriculum alignment. Qualitative evidence further demonstrated that adaptive content generation strengthened learner autonomy, instructional flexibility, and educational accessibility while emphasizing the continuing importance of human judgment, ethical oversight, and pedagogical expertise. Results indicate that Generative AI functions most effectively as a collaborative instructional design partner rather than a replacement for educators. Human-centered implementation supported by responsible governance and evidence-based instructional design provides a sustainable pathway for advancing personalized education across diverse learning environments.
SELF-EFFICACY AND METACOGNITION AS MEDIATING EFFECTS OF GROWTH MINDSET ON STUDENTS’ WRITING SKILLS Amrina; Syarifatul Hayati Zarfi; Daniyar Satybaldy
Journal International of Lingua and Technology Vol. 4 No. 3 (2025)
Publisher : Sekolah Tinggi Agama Islam Al-Hikmah Pariangan Batusangkar, West Sumatra, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55849/jiltech.v4i3.1152

Abstract

In the field of education, writing skills represent a vital competency that university students must possess. These skills are closely interrelated with self-efficacy and metacognition. Self-efficacy refers to an individual’s belief in their capability to execute the actions required to achieve specific goals, while metacognition involves an individual’s awareness of their own thinking processes. Both elements are essential for the development of effective writing proficiency. This study aims to examine and observe students’ writing skills, which are crucial for academic success in higher education, as an effort to analyze the mediating effects of a growth mindset on students’ writing performance. This research employs a quantitative method using a survey design. Data were collected via questionnaires distributed to a sample of students from the Arabic Language Education and English Language Education programs at the State Islamic University (UIN) Mahmud Yunus Batusangkar. Data were analyzed using mediation analysis techniques. The findings indicate that self-efficacy and metacognition significantly function as mediating variables in the relationship between a growth mindset and students’ writing skills. These components are proven to be fundamental factors in the educational process. This study demonstrates that writing skill is a critical competence for students. A growth mindset enhances self-efficacy and metacognitive awareness, both of which strongly influence writing effectiveness. When students possess the ability to write effectively, they feel more confident in their abilities. Furthermore, when students utilize metacognitive awareness to construct their writing alongside high self-efficacy, they experience a significant improvement in their overall writing skills.
CULTURALLY-RESPONSIVE LEARNING TECHNOLOGY: INTEGRATING LOCAL WISDOM AND MOTHER TONGUES INTO DIGITAL LEARNING PLATFORMS FOR INDIGENOUS STUDENTS Andi Asrijal; Raden Ajeng Indrawati; Syarifatul Hayati Zarfi; Fathimath Saida
Journal International Inspire Education Technology Vol. 4 No. 3 (2025)
Publisher : Sekolah Tinggi Agama Islam Al-Hikmah Pariangan Batusangkar, West Sumatra, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55849/jiiet.v4i3.1151

Abstract

Indigenous students across diverse regions continue to experience inequitable learning outcomes due to digital learning platforms that insufficiently reflect their cultural identities, local wisdom, and mother tongues. Conventional EdTech systems often adopt universalized content structures that overlook indigenous epistemologies, resulting in decreased motivation, limited comprehension, and reduced learning engagement. These challenges highlight the need for culturally-responsive digital learning models capable of integrating local narratives, linguistic heritage, and community-based knowledge systems into technology-supported education. This study aims to develop and analyze a culturally-responsive learning technology framework that embeds local wisdom and mother tongues within digital learning platforms to enhance accessibility, inclusivity, and meaningful learning for indigenous students. The research employs a mixed-methods design involving qualitative ethnographic documentation of indigenous cultural practices and quantitative usability testing of a prototype platform. Data are collected from indigenous teachers, students, and community leaders through interviews, observations, and structured questionnaires. Findings indicate that integrating culturally grounded content—such as traditional stories, regional ecological knowledge, and local vocabulary—significantly improves learning relevance, cognitive connection, and emotional engagement. Quantitative analysis shows measurable gains in comprehension and task completion accuracy when learning materials incorporate mother-tongue scaffolding and culturally familiar representations. The study concludes that culturally-responsive learning technology fosters deeper identity affirmation, strengthens intergenerational knowledge transmission, and reduces digital learning barriers among indigenous students. The incorporation of local wisdom and mother tongues not only enhances academic outcomes but also promotes cultural sustainability within digital ecosystems. Future implementations should prioritize community co-design, adaptive language features, and scalable platform architectures to ensure long-term impact and cross-regional applicability.
Co-Authors Ali Omar Amrina Andi Asrijal Daniyar Satybaldy Fathimath Saida Nina Anis Pong Krit Raden Ajeng Indrawati Rinovian Rais Roni Subhan Samira Mohammed