<![CDATA[Islamic Religious Education (PAI) in the digital age faces a pedagogical paradox: while it aims to cultivate faithful and rational individuals, its instructional models often prioritize rote memorization over higher-order thinking. This disconnect leaves learners unable to critically engage with Islamic doctrines amid contemporary socio-religious challenges such as extremism, secularism, and misinformation.This study aims to analyze the theoretical and practical implementation of the Deep Learning (DL) framework—an emerging pedagogical model focused on critical analysis, integration, and transfer of knowledge—as a strategic alternative to enhance critical thinking skills (berpikir kritis) within PAI. Employing a qualitative library research design, this study systematically analyzes literature from national (SINTA-accredited) and international (Scopus-indexed) journals published between 2021 and 2025. Data were collected through documentation and analyzed using Miles, Huberman, and Saldaña’s interactive model (data condensation, display, verification), supplemented by thematic synthesis and critical hermeneutic analysis. The analysis reveals that surface learning dominates PAI classrooms due to time constraints, assessment systems focused on low-level recall, and teacher-centered approaches. Deep Learning—characterized by the three syntaxes: connecting, constructing, and active application —directly aligns with Islamic epistemological principles ( tafakkur , tadabbur , ijtihad ). The study constructs a synthesized model of Deep Learning-based PAI consisting of: (1) Authentic Problematization of faith issues, (2) Multidimensional Reasoning (naqli, aqli, and empirical), (3) Collaborative Dialogic Inquiry , and (4) Reflective Metacognitive Assessment . Implementing Deep Learning transforms PAI from doctrinal transmission into a critical-humanistic discipline. It significantly fosters students’ abilities to analyze, evaluate, synthesize, and create arguments rooted in Islamic sources while engaging with modern challenges. The study recommends teacher training redesign, curriculum modification, and assessment reform toward process-oriented evaluation.]]>
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