Readiness Profile of Islamic Religious Education Teachers in Integrating Artificial Intelligence: A Four-Dimensional Descriptive Study

Abstract

The rapid development of artificial intelligence (AI) requires teachers to integrate it meaningfully into their instructional practice, including in Islamic Religious Education (Pendidikan Agama Islam, PAI), a subject whose knowledge content is inseparable from religious values. Research on AI readiness among PAI teachers in Indonesia remains dominated by literature reviews and small-scale qualitative studies, leaving a gap in quantitative mapping that systematically decomposes readiness into empirically measurable dimensions. This study aims to describe the self-reported readiness profile of PAI teachers who are currently enrolled as students in the Master of Islamic Religious Education (MPAI) program at the Faculty of Islamic Studies, Universitas Muhammadiyah Sumatera Utara (UMSU), for integrating AI into PAI instruction, across four dimensions: (1) basic AI literacy and skills, (2) pedagogical competence in AI–PAI integration, (3) attitudes and perceptions toward AI, and (4) institutional and facility support. This quantitative descriptive study used a 15-item, five-point Likert questionnaire distributed openly to the entire eligible population of MPAI students at the UMSU Faculty of Islamic Studies (eligible population ≈300) via WhatsApp groups, direct distribution, and assistance from the MPAI study program. Seventy-four responses were received (response rate ≈24.7%). All four dimensions fell into the High category. Attitudes/perceptions toward AI recorded the highest mean score (M = 4.19; SD = 0.96), followed by basic AI literacy (M = 4.01; SD = 1.05), institutional support (M = 3.87; SD = 1.00), and pedagogical competence in AI–PAI integration recorded the lowest score (M = 3.86; SD = 1.07). Instrument reliability was excellent across all dimensions (Cronbach's alpha 0.871–0.973). A descriptive gap was found between teachers' highly positive affective attitudes toward AI and their applied pedagogical competence in designing AI-based PAI instruction, without accompanying inferential statistical testing of the significance of this difference. This study offers a baseline readiness map that contextually applies a technology-readiness framework to the domain of PAI, and may serve as an initial reference for MPAI curriculum development and for AI training policies more specifically targeted at strengthening pedagogical competence, rather than attitude alone.