Deep Learning in Christian Religious Education: A Systematic Review of Pedagogical Models and Digital Challenges
DOI:
https://doi.org/10.17977/um039v10i22025p120-132Keywords:
Learning Models, Deep Learning, Christian Religious Education, Learning Motivation, Digital Age, Systematic Literature Review.Abstract
This study aims to examine the development of a deep learning model in Christian Religious Education (PAK), assess the effectiveness of its integration in improving student motivation and understanding, and identify implementation challenges facing the digital era. The method used is a Systematic Literature Review (SLR) by examining ten scientific articles published between 2020 and 2025. Articles were obtained from Google Scholar, Publish or Perish (PoP), and Research Rabbit databases, then selected based on inclusion criteria: relevance to the topic of deep learning and PAK, publication recency, and journal quality. The results of the study indicate that the deep learning model in PAK develops through a project-based approach, digital interactive media, and spiritual personalization assisted by artificial intelligence. This integrated model has proven effective in increasing students' intrinsic motivation, deepening their understanding of faith texts, and fostering 21st-century skills. However, the implementation of deep learning still faces challenges such as limited digital infrastructure, low teacher technology literacy, reduced student access, and ethical and spiritual issues. Therefore, this study emphasizes the need for collaborative strategies between teachers, schools, parents, and churches so that the implementation of deep learning truly supports the growth of faith and the quality of Christian Education learning
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