Deep Learning Approach in Transforming Religious Moderation Education in the Digital Era

Abstract

This study aims to analyze the application of deep learning in the transformation of religious moderation education in the digital era and its implications for the development of modern Islamic education. The research employs a qualitative descriptive approach using library research, reviewing literature on Islamic education, religious moderation, and artificial intelligence in learning contexts. Data were collected from academic books, scientific journals, articles, and other credible sources, then analyzed using content analysis to identify patterns, concepts, and relationships between technology and the strengthening of moderation values. The results indicate that the implementation of deep learning can transform Islamic education from a traditional rote-based model to a reflective, contextual, and interactive learning process. This technology enables the analysis of students’ thinking patterns and behaviors, the reinforcement of moderation values, character formation, and the development of moderate digital literacy in a personalized and adaptive manner. The integration of technology and spirituality in digital Islamic education creates transformative learning experiences that strengthen empathy, ethical awareness, and students’ reflective capacities. The study implies the importance of developing curricula, learning strategies, and teacher competencies based on artificial intelligence to produce a generation of students who are moderate, tolerant, and competent in facing the challenges of the digital era.