Integrating Pedagogical Deep Learning in Islamic Education: A Systematic Literature Review

Syalsa Nur Saputri, Abd. Madjid

Abstract


This study aims to analyze the effectiveness of the deep learning learning model in improving students' academic achievement in Islamic Religious Education (PAI) subjects. This research method is through the Systematic Literature Review (SLR) approach. A total of 1,512 articles from the Scopus, Google Scholar, Emerald, and Springer databases were selected using the PRISMA table, until 30 articles met the final criteria. The results of the study show that deep learning is able to strengthen conceptual understanding, learning motivation, student involvement, as well as critical thinking and problem-solving skills. The integration of digital technology plays a significant role in improving the prediction of academic achievement, personalization of learning, and the effectiveness of learning process evaluation. However, the application of deep learning is still influenced by the factors of teacher readiness, the availability of digital infrastructure, and the characteristics of students. The results of the study revealed that although this model offers great opportunities in PAI learning innovation in the digital era, there are challenges in the form of limited facilities and pedagogic competence of teachers. Overall, deep learning has the potential to be a transformative approach in improving the quality of PAI learning if applied supported by adequate learning.

Keywords


Deep Learning, Islamic Religious Education, Digital Technology, Personalized Learning, Academic Achievement

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References


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DOI: https://doi.org/10.18860/abj.v11i2.40175

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