<![CDATA[Self-regulated learning (SRL) is a crucial competency for students in the 21st century, enabling learners to plan, monitor, regulate, and reflect on their own learning processes. However, many junior high school students still experience difficulties in developing strong self-regulation skills. This study aims to examine the effect of Problem-Based Learning (PBL) integrated with Artificial Intelligence (AI) on students’ self-regulated learning tendencies. The research employed a quasi-experimental method using a one-group posttest-only design. The study was conducted at SMP Negeri 1 Telaga Biru during the first semester of the 2025/2026 academic year, involving 60 seventh-grade students selected through purposive sampling. Data were collected using a self-regulated learning questionnaire based on indicators of goal setting, learning strategies, self-monitoring, time and resource management, motivational control, and self-reflection. Data analysis was carried out using the Kolmogorov–Smirnov normality test, followed by a One-Sample t-Test for normally distributed data and the Wilcoxon Signed-Rank Test for non-normally distributed data. The results showed that students’ SRL scores after the implementation of PBL integrated with AI were in the good to high category and significantly exceeded the predetermined reference value (p < 0.05). Strong tendencies were observed in the forethought, motivational belief, and self-reflection dimensions, while help-seeking and collaboration showed relatively lower scores. These findings indicate that PBL integrated with AI has a positive and significant effect on students’ self-regulated learning tendencies. The study concludes that integrating AI as pedagogical scaffolding within PBL can effectively support the development of self-regulated learning, provided that social interaction and collaborative learning are intentionally strengthened.]]>
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