This study investigates the integration of technology acceptance and pedagogical deep learning in Islamic Religious Education (IRE), where deep learning is conceptualized as a pedagogical approach that emphasizes meaningful understanding, reflective thinking, and enjoyable engagement, rather than artificial intelligence-based deep learning. Although previous studies have extensively examined technology acceptance and deep learning independently, empirical studies integrating the Technology Acceptance Model (TAM) with pedagogical deep learning in the context of Islamic education are still limited. To address this gap, this study uses a quantitative survey design involving 321 teachers and students selected through simple random sampling from a population of 1,287 participants. Data were collected using a validated Likert scale questionnaire (Cronbach's Alpha = 0.874) and analyzed through descriptive statistics and simple linear regression using SPSS version 25. The results of the study indicate that acceptance of TAM-based learning media has a significant and positive effect on the implementation of pedagogical deep learning (R² = 0.542, t = 12.884, p <0.001), showing that 54.2% of the variance in deep learning practices is explained by technology acceptance. Descriptive analysis shows that Perceived Usefulness recorded the highest average score among TAM constructs (M = 4.26), while Meaningful Learning emerged as the most dominant dimension in pedagogical learning (M = 4.23). Theoretically, this study expands TAM by positioning technology acceptance as a driver of deep, reflective, and value-oriented pedagogical learning in Islamic education. Practically, these findings provide evidence-based guidance for educators and schools in designing technology-supported IRE that promotes meaningful, attentive, and enjoyable learning experiences.
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