<![CDATA[This study aims to analyze the influence of the Deep Learning Approach within the framework of the Merdeka Curriculum on academic competence and self-directed learning among elementary school students in Tanjung Jabung Barat Regency. Employing a quantitative approach with a cross-sectional survey design, the study involved 450 fourth-, fifth-, and sixth-grade students from 120 elementary schools selected through a multistage cluster sampling technique. Data were collected using a deep learning implementation questionnaire, standardized academic achievement tests, and a self-directed learning scale that had undergone content validity, construct validity, and reliability testing. Descriptive analysis indicated that the level of Deep Learning implementation ranged from moderate to high, while the average academic competence and self-directed learning of students were in the high–moderately high category. Correlation and multiple linear regression analyses revealed a positive and significant relationship between Deep Learning implementation and academic competence (r ≈ 0.48) as well as self-directed learning (r ≈ 0.51), with Deep Learning emerging as a significant predictor after controlling for gender, grade level, and school characteristics. The regression model explained approximately 28% of the variance in academic competence and 32% of the variance in self-directed learning, demonstrating the substantive contribution of the approach to both cognitive and non-cognitive learning outcomes. These findings affirm that Deep Learning effectively supports the goals of the Merdeka Curriculum in strengthening conceptual understanding, critical thinking, and student autonomy, and recommend strengthening teacher competence, developing learning communities, and providing policy and resource support to ensure optimal and sustainable implementation.]]>
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