Deep Learning-Based Islamic Religious Education: Transforming Higher-Order Thinking Skills in Contemporary Classrooms
DOI:
https://doi.org/10.67899/ar.v2i2.220Keywords:
Deep Learning, Islamic Religious Education, Contemporary ClassroomsAbstract
This study examines the potential of deep learning pedagogy to transform Higher-Order Thinking Skills (HOTS) within contemporary Islamic Religious Education (IRE) classrooms. The study aims to synthesize recent scholarly evidence concerning the relationship between deep learning, meaningful engagement, critical thinking, problem solving, reflection, creativity, and Islamic value formation. A library research method was employed by systematically identifying, selecting, comparing, interpreting, and synthesizing relevant peer-reviewed journal articles published predominantly during the last five to ten years. The findings indicate that deep learning is most effective when IRE moves beyond memorization toward meaningful, mindful, joyful, contextual, collaborative, inquiry-oriented, problem-based, and reflective learning. The synthesis further demonstrates that HOTS development is strengthened when students are required to interpret Islamic sources, examine contemporary problems, evaluate arguments, formulate ethical judgments, and create contextual solutions. The principal novelty of this study is the formulation of an integrated Deep Learning HOTS framework for IRE that connects cognitive depth with Islamic ethical reasoning, contextual relevance, reflective awareness, and meaningful action. The framework positions IRE not merely as a subject for transmitting religious knowledge but as a transformative learning environment for cultivating intellectually rigorous, ethically responsible, spiritually grounded, and socially responsive learners
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Copyright (c) 2025 Husna Husna, Khalid Abdullah Al Muzaini, Maryam Rashid Saleh Al Tamimi, Muneera Mohammed Al Dossary (Author)
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