Pedagogical Transformation in Islamic Religious Education: Integrating Deep Learning and Coding for Elementary School Students
Abstract
The rapid growth of digital technology has created challenges for Islamic Religious Education (IRE) in elementary schools, which often remain dominated by conventional, teacher-centered approaches. This study aimed to develop and examine the effectiveness of an Islamic Techno-Pedagogy model integrating Deep Learning and Coding to support students’ cognitive, spiritual, and digital development. The research employed a Research and Development (R&D) approach, combining Design-Based Research (DBR) with a Pretest–Posttest Control Group Design. Data were collected through observations, interviews, questionnaires, tests, and documentation, and analyzed using qualitative and quantitative techniques. The findings revealed that the developed model significantly improved students’ active participation from 42% to 85%, their understanding of Islamic concepts from 62% to 88%, and their interest in digital Islamic learning from 55% to 90% across three DBR cycles. Experimental testing also showed significant differences between the experimental and control groups, with a cognitive N-Gain score of 0.75. The study concludes that integrating Deep Learning and Coding into IRE effectively strengthens students’ knowledge, character, and digital competencies. This research contributes a novel Islamic Techno-Pedagogy framework that bridges technological literacy and spiritual development in elementary education.
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DOI: https://doi.org/10.33852/jurnalnu.v10i1.730
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