<![CDATA[Background: Self-regulated learning is a key determinant of successful inquiry-based science learning, yet little is known about how elementary students' regulatory behaviors interact dynamically throughout the inquiry process. Aims: This study examines self-regulated learning as a dynamic network of regulatory behaviors within inquiry-based elementary science education and evaluates changes in students' regulatory ability after instruction. Methods: An embedded mixed-methods design was employed during a six-week intervention involving 207 elementary students from three public schools in Bandung, Indonesia. Qualitative data from inquiry worksheets were transformed into network data to map self-regulated learning behaviors across five inquiry stages, while pretest–posttest self-regulated learning questionnaire data were analyzed using the Wilcoxon signed-rank test. Results: The results indicate that self-regulated learning operates as a dynamic and interconnected network. The self-regulated learning network consisted of 20 nodes and 29 directed edges, with a directed density of 0.076, modularity of 0.662, and directed clustering coefficient of 0.283. Forethought behaviors in the goal-setting stage showed strong weighted connectivity, while monitoring and reflection behaviors in the data-analysis stage acted as regulatory bridges. Wilcoxon signed-rank analysis showed a significant increase in self-regulated learning scores from pretest (M = 3.13, Mdn = 3.08, IQR = 0.37) to posttest (M = 3.32, Mdn = 3.24, IQR = 0.59), Z = -6.72, p < .001, r = .47. However, the N-gain value of 0.23 indicates low normalized improvement. Conclusion: These findings suggest that inquiry-based science learning contributes to measurable improvements in elementary students' self-regulated learning. However, the relatively low learning gain indicates that sustained and explicit scaffolding is necessary to strengthen self-regulatory processes throughout inquiry activities.]]>
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