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…

This paper, presented at the 2016 [National Association for Research in Science Teaching] NARST Annual International Conference, summarizes the work to date of the Knowledge Assets to Support the Science Instruction of Elementary Teachers (ASSET) project. ASSET is exploring a method for collecting and synthesizing pedagogical content knowledge…

We studied the processes involved in synthesis writing, focusing on planning, editing and self-regulation strategies. The aims of the study were a) to analyse the temporal distribution of cognitive strategies and self-regulation across the different phases of writing, b) to identify different writing approaches (i.e., profiles), and c) to…