Background: COVID-19 accentuated an evergreen dilemma in evidence-informed policy making--the imperative to synthesise the best available evidence with limited time to produce high quality synthesis. The pandemic prompted the adaptation of evidence synthesis practices to match the urgency of the crisis, and heightened demand by policy makers,…

Risk of bias (RoB) assessments are a core element of evidence synthesis but can be time consuming and subjective. We aimed to develop a decision rule-based algorithm for RoB assessment of seroprevalence studies. We developed the SeroTracker-RoB algorithm. The algorithm derives seven objective and two subjective critical appraisal items from the…

In evidence-based practice, new topics generally only have a few studies available for synthesis. As a result, the evidence of such meta-analyses raised substantial concerns. We investigated the robustness of the evidence from these earliest studies. Real-world data from the Cochrane Database of Systematic Reviews (CDSR) were collected. We…

Background: This paper explores K-12 interdisciplinary learning in the humanities (IL-Humanities), an area that, until now, has seen limited research focus compared to its STEM counterparts. We asked: (1) What are the outcomes of IL-Humanities in terms of interdisciplinary competences? (2) How do learners in these environments engage in…

This manuscript presents an exploratory mixed-methods case study examining the impact of artificial intelligence (AI) in the form of generative pretrained transformers (GPTs) and large language models on special education administrative practices in one school district in the Northeast United States. AI holds tremendous potential to positively…