Supporting self-regulated learning in clinical problem-solving with a computer-based learning environment: the effectiveness of scaffolds

Computer-supported scaffolding plays a pivotal role in advancing problem-solving skills and improving cognitive learning outcomes in self-regulated learning. However, there is limited research on the effectiveness of different types of scaffolds and the role they play in the context of clinical problem-solving. This study performed latent profile analysis on the use of different scaffolds of 86 medical students as they solved a clinical reasoning problem in a computer-based learning environment. Specifically, we profiled students' use of conceptual, strategic, and metacognitive scaffolding in clinical reasoning. We further examined whether the profiles of scaffolding use related to students' task performance. Findings indicated that there were four types of scaffolding use: highly metacognitive scaffolding usage, highly strategic scaffolding usage, moderate usage of all scaffolding, and low usage of all scaffolding. Learners who were highly metacognitive and those who used moderate scaffolding were more likely to solve the problem correctly, whereas learners who rarely used scaffolding were more likely to fail the task. Results also revealed that highly metacognitive learners had better efficacy and confidence than those with other profiles of scaffolding use. Moreover, students who used more strategic scaffolding had better efficacy than those who rarely used scaffolding. Findings from this study offer new insights into the effectiveness of computer-supported scaffolding, which could inform future studies and practice regarding how to support self-regulated learning.