Deep Learning Pedagogy, Learning Motivation, and Conceptual Understanding in Islamic Religious Education: Evidence from Senior High School Students in Bandung

Abstract

This study examines the relationships between deep learning pedagogy, learning motivation, and conceptual understanding in Islamic Religious Education (IRE) among senior high school students in Bandung, Indonesia. A quantitative approach with a cross-sectional survey design was employed, involving 130 respondents selected from students participating in Islamic Religious Education. Data were collected using a structured questionnaire with a five-point Likert scale, and multiple linear regression was performed using SPSS version 25. The results showed a positive and statistically significant relationship between deep learning and conceptual understanding (B = 0.465, β = 0.500, p = 0.001). A positive and significant relationship was also found between learning motivation (B = 0.368, β = 0.388, p = 0.001). At the same time, there is evidence that both variables contribute significantly to the variation in conceptual understanding (F = 65.947, p < 0.001), and the coefficient of determination (R²) of 0.509 indicates that the regression model accounts for 50.9% of the observed variation. Deep learning pedagogy showed a stronger standardized relationship with conceptual understanding than learning motivation. These results highlight the importance of combining effective teaching practices with motivational support to encourage students to better understand Islamic concepts. This study provides quantitative evidence for Islamic education research and practical implications for creating a reflective, engaging, and contextually relevant learning environment. The results indicate a statistical relationship, not a causal effect, as this study employs a cross-sectional design and measurements were conducted via self-reports.