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All Journal Atta'dib Jurnal Pendidikan Agama Islam Journal of Deep Learning, Computer Vision and Digital Image Processing
Siti Suryanih
Universitas Islam Depok
Religion Computer Science & IT Education Languange, Linguistic, Communication & Media Other

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A Conceptual Framework for Digital-Ethical Literacy and Social Responsibility in Islamic Religious Education in the Generative AI Era Ridha Aulia; Siti Suryanih; Aproni; Syahrul Arya Fatahuddin; Jupri
Journal of Deep Learning, Computer Vision, and Digital Image Processing Volume 4 Issue 2 June 2026
Publisher : CV. Sakura Digital Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61255/decoding.v4i2.1551

Abstract

Purpose – This study develops a conceptual framework of digital-ethical literacy and social responsibility for responsible Generative Artificial Intelligence (GenAI) use in Islamic Religious Education by integrating AI literacy, digital pedagogy, Islamic ethics, and digital citizenship.Methods – A conceptual literature review was conducted using a purposive corpus of 110 sources selected for thematic relevance, conceptual contribution, and argumentative strength. The literature was analyzed through thematic-conceptual synthesis to identify recurring constructs and relationships.Findings – The synthesis produced four progressive operational components: AI awareness, critical verification, ethical academic use, and socially responsible digital participation. Islamic moral orientation functions as a cross-cutting normative dimension guiding all components through amanah, tabayyun, adab, ‘adl, responsibility, and maslahah. The framework is progressive but non-rigid and context-sensitive, emphasizing educator guidance, authoritative sources, prior learner knowledge, institutional policy, and topic sensitivity. Research implications – The framework provides a basis for curriculum design, educator guidance, assessment development, institutional policy, and future empirical validation.Originality – The study offers an integrated mechanism linking technological understanding, epistemic verification, academic integrity, Islamic moral judgment, and digital social responsibility in one context-sensitive model.
RESEARCH LANDSCAPE OF ARTIFICIAL INTELLIGENCE IN ISLAMIC EDUCATION: A BIBLIOMETRIC ANALYSIS RIDHA AULIA; Siti Suryanih; Annory Langga'o; Raihand Ramadhani Abdul Sayeed; Muhammad Rizqiy
Atta'dib Jurnal Pendidikan Agama Islam Vol. 7 No. 2 (2026)
Publisher : IAIN Bone

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30863/attadib.v7i2.12497

Abstract

The rapid development of Artificial Intelligence (AI) has expanded research interest in Islamic education; however, the field's intellectual structure, thematic development, and research trajectory remain insufficiently understood. This study examines the research landscape of Artificial Intelligence in Islamic Education through a bibliometric analysis. We analysed 102 Scopus-indexed documents published between 2020 and 15 August 2026. The PRISMA framework guided the systematic identification and selection of documents. At the same time, bibliometric analysis used Bibliometrix/Biblioshiny and VOSviewer through performance analysis and science mapping techniques, including keyword co-occurrence, thematic mapping, co-authorship, bibliographic coupling, and co-citation analysis. The findings indicate significant publication growth, particularly since 2024, with Indonesia and Malaysia emerging as major contributors to scientific production and collaboration. Artificial intelligence, machine learning, deep learning, speech recognition, and Qur’anic learning technologies dominate the conceptual structure. At the same time, research themes have expanded to include AI literacy, personalised learning, technology acceptance, ethics, and governance. Generative AI and ChatGPT have emerged as new research directions but have not yet become dominant themes. This study contributes an integrated knowledge map by revealing the publication development, thematic evolution, collaboration structures, research fronts, and intellectual foundations of AI research in Islamic education, providing a foundation for future scholarly development.
Co-Authors Annory Langga'o Aproni Jupri Muhammad Rizqiy Raihand Ramadhani Abdul Sayeed RIDHA AULIA Ridha Aulia Syahrul Arya Fatahuddin