Conceptualization of the Deep Learning Approach in Islamic Religious Education Learning for the Character Formation of the Alpha Generation - Fathurrahim, Wika Thariq; Mustofa, Triono Ali (Proceeding ISETH (International Summit on Science, Technology, and Humanity), 2025)
The rapid advancement of digital technology and the demands of 21st-century education have significantly influenced the implementation of Islamic Religious Education (IRE), particularly in responding to the characteristics of Generation Alpha. Conventional IRE learning, which largely emphasizes memorization and one-way instruction, is considered less effective in fostering meaningful understanding and character formation. This study aims to conceptualize the deep learning approach as a pedagogical framework for strengthening character education in Islamic Religious Education for Generation Alpha. The study employs a qualitative approach using library research methods by analyzing relevant academic journals, books, and policy documents related to deep learning, Islamic education, and character development. Data were analyzed using content analysis to identify conceptual patterns and theoretical relationships. The findings indicate that the deep learning approach emphasizes critical thinking, reflective learning, and contextual understanding of Islamic values, enabling students to internalize religious teachings more substantively. This approach is highly relevant to the learning characteristics of Generation Alpha and contributes positively to the development of religious awareness, critical thinking, and moral responsibility. However, challenges such as limited teacher competence, curriculum constraints, and inadequate learning facilities remain obstacles to its implementation. Therefore, strengthening teacher capacity and institutional support is essential for the effective application of deep learning in Islamic Religious Education.