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Adam Mudinillah
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Al-Hijr: Journal of Adulearn World
Published by Sekolah Tinggi Agama Islam Al-Hikmah Pariangan Batusangkar
ISSN : 28293894     EISSN : 28294351     DOI : https://doi.org/10.55849/alhijr
Core Subject : Science, Education,
Computer Science & IT Education Languange, Linguistic, Communication & Media Other
Al-Hijr: Journal of Adulearn World is a multi-disciplinary, peer-refereed open-access international journal which has been established for the dissemination of state-of-the-art knowledge in the field of education, teaching, development, instruction, educational projects and innovations, learning methodologies, and new technologies in education and learning. The journal publishes state-of-art papers in fundamental theory, experiments, and simulation, as well as applications, with a systematic proposed method, sufficient review on previous works, expanded discussion, and concise conclusion. As our commitment to the advancement of science and technology, the Al-Hijr follows the open access policy that allows the published articles freely available online without any subscription. Submitted papers must be written in English for initial review stage by editors and further review process by minimum two international reviewers.
Arjuna Subject : Umum - Umum
Articles 155 Documents
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BUILDING TRUST IN AI-POWERED EDUCATION SYSTEMS: ETHICAL GUIDELINES AND RESPONSIBILITIES FOR EDUCATORS Siti Sulaiha B. Abbas; Ethan Tan; Priya Patel
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.v5i3.1313

Abstract

Rapid adoption of Artificial Intelligence (AI) in education has transformed teaching, learning, assessment, and academic administration by enabling personalized instruction, intelligent feedback, and data-driven decision-making. Expanding implementation of AI-powered educational systems has simultaneously intensified concerns regarding transparency, fairness, privacy, accountability, and educator responsibility, making trust a fundamental prerequisite for sustainable educational innovation. This study aimed to examine the determinants of trust in AI-powered education systems by investigating the relationships among ethical governance, algorithmic transparency, educator responsibility, institutional accountability, and learner perceptions. A mixed-methods sequential explanatory design was employed, integrating quantitative data collected from 520 participants through validated questionnaires and Structural Equation Modeling with qualitative evidence obtained from interviews, classroom observations, reflective journals, and institutional policy documents. Results demonstrated that algorithmic transparency, educator ethical competence, institutional accountability, and privacy protection significantly strengthened trust in AI-supported education, while educator responsibility partially mediated the relationship between ethical governance and learner trust. Qualitative findings further revealed that transparent communication, professional judgment, and continuous human oversight enhanced acceptance of AI-assisted instructional practices. Findings indicate that trust emerges through the interaction of technological reliability, ethical governance, and pedagogical professionalism rather than technological capability alone. Human-centered implementation supported by transparent institutional policies provides a sustainable foundation for responsible Artificial Intelligence adoption across contemporary educational ecosystems.
THE FUTURE OF GENERATIVE AI IN EDUCATION: OPPORTUNITIES FOR ENHANCING TEACHING AND LEARNING Akbar Syaiful Luneto; Kim Minho; Nurul Inayah Bachmid
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.v5i3.1314

Abstract

Rapid advancements in Generative Artificial Intelligence (Generative AI) have transformed educational practice by enabling intelligent content generation, personalized learning support, adaptive tutoring, automated feedback, and innovative instructional design. Expanding adoption of these technologies has created substantial opportunities for improving teaching and learning while simultaneously raising concerns regarding academic integrity, ethical governance, information reliability, and the evolving role of educators. This study aimed to examine the future potential of Generative AI for enhancing educational processes by investigating its pedagogical opportunities, instructional effectiveness, and broader implications for teaching and learning. A mixed-methods sequential explanatory design was employed, integrating quantitative evidence from learning analytics, academic performance, and standardized educational measures with qualitative data collected through interviews, classroom observations, reflective journals, and institutional document analysis. Findings demonstrated that Generative AI significantly improved academic achievement, learner engagement, creativity, critical thinking, self-regulated learning, instructional effectiveness, and course completion when implemented within well-structured pedagogical environments supported by active educator facilitation. Qualitative evidence further indicated that responsible integration depended on human oversight, ethical guidance, transparent institutional policies, and the development of learners' critical digital literacy. Results suggest that Generative AI functions most effectively as a collaborative pedagogical partner rather than a substitute for educators. Human-centered implementation supported by responsible governance provides a sustainable pathway for educational innovation and future digital transformation across diverse learning environments.
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.
RELIGIOUS MODERATION IN TAFSIR NUSANTARA: BALANCING SYARIAT AND HAKIKAT IN AL-QAUL AL-BAY?N BY SYEKH SULAIMAN AR-RASULI Melisa Rezi; Zulkifli; Eka Putra Wirman; Abrar
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.v5i3.1320

Abstract

The discourse on religious moderation in contemporary Islamic studies is generally understood within a socio-political framework or as a form of normative tolerance, thereby paying insufficient attention to the theological and spiritual foundations that sustain it. Within this landscape of previous studies, this research offers a distinctive and novel perspective by positioning religious moderation (wasathiyyah) as a conceptual integration between syariat and hakikat, constructed directly through Qur’anic exegetical narratives within the Tafsir Nusantara tradition. This study aims to examine how Syekh Sulaiman ar-Rasuli (Inyiak Canduang) formulates the concept of religious moderation through his interpretation of Juz 30 in Tafsir al-Qaul al-Bay?n f? Tafs?r al-Qur’?n, and how this construction reflects the distinctive wasathiyyah orientation of Nusantara scholars. This research employs a qualitative method using a textual study approach (library research), through a thematic analysis of eight surahs in Juz ‘Amma as the primary data source, supported by classical tafsir literature and contemporary studies on religious moderation. The findings show that religious moderation in Inyiak Canduang’s tafsir is constructed through four main dimensions: moderation in creed, worship, social life, and psycho-spiritual life. Moderation is not understood as a compromise of religious teachings, but as a balance between firmness of faith, inner sincerity, consistency in worship, social concern, and spiritual tranquility. This study contributes to strengthening the discourse on religious moderation in Indonesia by emphasizing the importance of a theological-spiritual foundation rooted in Qur’anic exegesis as the basis for fostering authentic, contextual, and sustainable religious life.
BUILDING ADAPTIVE CURRICULUM MODELS WITH AI: INNOVATIONS AND IMPLICATIONS FOR TEACHING AND LEARNING Dame Siregar; Zain Nizam; Syafiq Amir
Al-Hijr: Journal of Adulearn World Vol. 5 No. 4 (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.v5i4.1300

Abstract

The integration of artificial intelligence (AI) into education is rapidly transforming traditional curriculum models, offering new opportunities for personalized learning. AI-powered adaptive curriculum models have the potential to provide real-time, personalized learning experiences that cater to individual student needs. This study explores the role of AI in developing adaptive curricula and its impact on teaching and learning processes. The research aims to evaluate the effectiveness of AI-driven adaptive curriculum models in improving student engagement, academic performance, and overall learning outcomes. A mixed-methods approach was used, combining quantitative assessments of student performance with qualitative feedback from both students and teachers. The findings indicate that students in AI-powered learning environments exhibited a 20% improvement in academic outcomes and a 25% increase in engagement compared to students using traditional curricula. Additionally, teachers reported positive feedback regarding the adaptability and effectiveness of AI tools in addressing diverse student needs. The study concludes that AI-enhanced adaptive curriculum models offer significant potential for improving educational practices by providing more personalized, dynamic, and engaging learning experiences. Future research should explore the long-term impacts of AI-driven curricula and address ethical concerns related to data privacy and algorithmic biases.

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