Scaffolds that support self-regulated learning (SRL) have been found to improve learning outcomes. The effects of scaffolds can differ depending on how learners use them and how specific scaffolds might influence learning processes differently. Personalized scaffolds have been proposed to be more beneficial for learning due to their adaptivity to learning progress and individualized content to learning needs. The present study investigated finer-grained effects of how personalized scaffolds driven by a rule-based artificial intelligence system influenced SRL processes, especially how students learned with them. Using a pre-post experimental design, we investigated personalized scaffolds based on university students' real-time learning processes in a technologically enhanced learning environment. Students in the experimental group (n = 30) received personalized scaffolds, while the control group (n = 29) learned without scaffolds. All students completed a 45-minute learning task with trace data recorded. Findings indicated scaffold effects on students' subsequent learning behaviour. Additionally, only scaffold interaction correlated to essay performance and suggests that the increase in frequencies of SRL activities alone does not contribute directly to learning outcomes. As guidelines for real-time SRL support are lacking, this study provides valuable insights to enhance SRL support with adaptive learning technologies.