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Reconstructing AI-Integrated PAI Learning Plans and Modules for Digital Natives Muhamad Sulaeman; Misnawar Misnawar
Journal of Knowledge and Collaboration Vol. 3 No. 1 (2026): Journal of Knowledge and Collaboration
Publisher : Arbain Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59613/d95h8h09

Abstract

The primary objective of this Research and Development (R&D) study is to reconstruct the Islamic Religious Education (PAI) Semester Learning Plan (RPS) and teaching modules through the integration of Generative Artificial Intelligence (AI) technology. This innovative initiative is intended to address learning burnout among digital native learners while mitigating teachers’ limitations in designing adaptive instructional materials within the Kurikulum Merdeka framework. Employing the 4D procedural model (Define, Design, Develop, and Disseminate), theoretical validation was conducted by experts in Islamic education content and instructional media. The results of the content validation indicated a feasibility score of 92% (Highly Feasible), while the instructional media design validation achieved 94% (Highly Feasible). A limited-scale empirical trial involving members of the Islamic Religious Education Teachers’ Working Group (MGMP PAI) confirmed a functionality and module-development time-efficiency rate of 89%. The findings demonstrate that AI-driven automation effectively aligns Learning Outcomes (CP) with dynamically differentiated learning trajectories, transforming conventional administrative documentation into an interactive and future-oriented instructional instrument.