Background: Computer-based scaffolding has been intensively used to facilitate students' self-regulated learning (SRL). However, most previous studies investigated how computer-based scaffoldings affected the cognitive aspect of SRL, such as knowledge gains and understanding levels. In contrast, more evidence is needed to examine the effects of scaffolding on the metacognitive dimension and efficiency outcome of SRL. Objectives: This study aims to examine the role of computer-based scaffolding in students' metacognitive monitoring and problem-solving efficiency. Methods: Seventy-two medical students completed two clinical reasoning tasks in BioWorld, an intelligent tutoring system (ITS) designed for promoting medical students' diagnostic expertise. During solving the tasks, students were asked to report their confidence judgements about proposed diagnoses. Computer trace data were used to identify task completion time (CT) and students' use of three scaffolding types, that is, conceptual, strategic, and metacognitive. Then we calculated students' metacognitive monitoring accuracy (i.e., calibration) and problem-solving efficiency. Results and Conclusions: One-sample t-test demonstrated that students inaccurately monitored their learning processes and were overconfident in both tasks. Linear mixed-effects models (LMMs) indicated that the intensive use of metacognitive scaffolding positively predicted students' metacognitive monitoring accuracy. Moreover, strategic scaffolding was negatively related to problem-solving efficiency, whereas metacognitive scaffolding positively influenced problem-solving efficiency. Takeaways: This study shows the importance of metacognitive scaffolding in improving the accuracy of metacognitive monitoring and problem-solving efficiency. Findings from this study provide new insights for instructors and ITS developers to optimise the design of scaffoldings.