Data extraction is a crucial, yet labor-intensive and error-prone part of evidence synthesis. To date, efforts to harness machine learning for enhancing efficiency of the data extraction process have fallen short of achieving sufficient accuracy and usability. With the release of large language models (LLMs), new possibilities have emerged to…

Problem-based learning (PBL) can take many different shapes but has as a common denominator that it builds on the principles of collaborative, constructive, contextual, and self-directed learning. Systematic review approaches that aim to provide insight in what features make PBL work generally fall short, as they tend to disregard the influential…