<![CDATA[The low level of self-regulated learning among elementary school students in science learning (IPAS) is a fundamental problem in 21st century education. Conventional learning approaches that emphasize rote memorization have caused students to remain highly dependent on teachers and have not yet developed the ability to manage, monitor, and evaluate their own learning process. This study aimed to examine the effect of gamification based on deep learning on students' self-regulated learning in IPAS learning at the elementary school level. The research employed a pre-experimental method with a One Group Pretest-Posttest Design. The subjects were 20 fifth-grade students at SD Negeri Sungguminasa V, Makassar City. Data were collected through a self-regulated learning questionnaire developed based on Zimmerman's self-regulation cycle, encompassing the forethought, performance, and self-reflection phases. Data analysis was conducted using descriptive analysis, normality test (Shapiro-Wilk), paired sample t-test, and N-Gain analysis. The results showed that the mean score increased from 56.15 (pretest) to 60.10 (posttest). The Shapiro-Wilk normality test yielded a significance value of 0.993 (p > 0.05), indicating normal data distribution. The paired sample t-test produced a t-value of −2.191 with a significance value of 0.041 (p < 0.05), indicating a significant difference between pretest and posttest scores. However, the N-Gain value of 0.09 classified the improvement as low. These findings suggest that gamification based on deep learning significantly influences students' self-regulated learning, although the magnitude of improvement still needs to be optimized. This study contributes empirical evidence for the integration of gamification with deep learning principles meaningful, mindful, and joyful as a strategic approach to developing self-regulated learning in science education at the elementary school level.]]>
