Artificial Intelligence in Islamic Studies Courses: Opportunities and Limitations in Islamic Higher Education from Student Perspectives - Mainuddin; Hermawansyah; Irfan, Muhammad; Junaidin; Zulkifli, Muh. (Al-Hayat: Journal of Islamic Education, 2025)
This study examines AI's dual impact in Islamic Studies courses at PTIs, addressing the gap in student perspectives on benefits/limitations. Amidst digital transformation and the need to align technology with Islamic values, this study examines how AI facilitates or impedes spiritually deep learning, thereby guiding ethical integration that preserves core pedagogical principles. A qualitative case study design approach was used, with data collected through semi-structured interviews with 11 active AI student users, participant observation of AI use in lectures, and analysis of AI-assisted lecture documents. Braun and Clarke's thematic data analysis model was applied, with cross-source triangulation to ensure validity. Five key benefits emerged: enhanced efficiency (e.g., rapid drafting), broader access to references, improved conceptual understanding, practical academic support, and enriched learning processes. Conversely, five limitations were identified: deficits in contextual religious knowledge (e.g., oversimplifying sacred texts), accuracy/reliability issues, inadequate referencing, academic dependency (reduced critical thinking), and technical barriers (e.g., internet instability). Findings reflect a single institution’s student cohort, limiting generalizability; variability in AI tool quality among participants may also influence results. Implications include the need for AI literacy modules, specialized Islamic datasets, and offline AI solutions to address inequities in resource-limited regions. This research pioneers two frameworks of AI-Ready Islamic Pedagogy (Critical Verification, Contextual Adaptation, Balanced Integration) and Hybrid Epistemology (combining AI pattern recognition with sanad-based knowledge validation).