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…

This case study introduces critical interpretive synthesis (CIS) as a systematic approach for reviewing and synthesizing a diverse body of research evidence to develop fresh insights on an issue of concern. Unlike aggregative forms of systematic review, which are more familiar in the field of education, CIS does not require commensurability…

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…

Increasingly used in a variety of disciplines, evidence synthesis methods such as systematic reviews and meta-analysis can help researchers and practitioners identify trends and effective interventions and uncover theoretical gaps to address specific topics and issues (e.g., the effect of the gamification approach on learning outcomes). Based on a…

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…