<![CDATA[Self-regulated learning is an essential competency that should be developed among elementary school students to support the successful implementation of the Merdeka Curriculum and 21st-century learning. However, preliminary observations at SD Negeri Sidomukti 02 revealed that many students still relied heavily on their teachers, showed limited learning initiative, and had not yet developed the ability to manage their own learning independently. This study aimed to examine the effectiveness of the Deep Learning approach in improving students' self-regulated learning in Natural and Social Sciences (IPAS). A quantitative approach with a pre-experimental one-group pretest–posttest design was employed. The participants consisted of 23 fifth-grade students at SD Negeri Sidomukti 02. Data were collected using a self-regulated learning questionnaire that had met the validity and reliability requirements, supported by observations and documentation. The data were analyzed using descriptive statistics, the Shapiro–Wilk normality test, a paired-samples t-test, and Cohen's d effect size analysis. The findings revealed that the mean score of students' self-regulated learning increased from 63.12 on the pretest to 84.47 on the posttest. The normality test indicated that both datasets were normally distributed (pretest: p = 0.121; posttest: p = 0.200). Furthermore, the paired-samples t-test showed a statistically significant difference between the pretest and posttest scores (t(22) = 12.487, p < .001), while the effect size (d = 1.21) indicated a large practical effect. These findings demonstrate that the Deep Learning approach effectively enhances students' self-regulated learning by promoting student-centered, contextual, collaborative, reflective, and meaningful learning experiences. Therefore, the Deep Learning approach can be considered an effective instructional strategy for strengthening elementary school students' self-regulated learning in IPAS.]]>
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