Tools | MOSAIC
MOSAIC is committed to conducting high-quality research synthesis, improving research synthesis methods, and promoting the use and uptake of reviews and meta-analyses.
MOSAIC's tools range from assistance with collection of evidence synthesis information to exploration of data from completed meta-analyses to answer desired research questions.
Explore these interactive data tools, including evidence gap maps, box plots, and traditional forest plots to interpret and translate meta-analytic findings.
AIR conducted the largest systematic review and meta-analysis of mathematics intervention effects to date, sponsored by the Institute of Education Sciences.
Explore the pool of grade K-12 mathematics intervention effects from the last 25 years using this interactive web application.
BSCS Science Learning conducted a large-scale synthesis of effects from K-12 science education interventions. This work was funded by the National Science Foundation and published in AERA Open.
The web application allows users to explore intervention effects extracted from nearly 20 years of science education studies.
AIR, in collaboration with the University of North Carolina, Chapel Hill, conducted a comprehensive systematic review and meta-analysis of programs to decrease cyberbullying perpetration and victimization.
This web application allows users to explore intervention effects from the 50 studies and 320 effect sizes spanning 45,371 participants, that met our review protocol criteria.
Collecting evidence synthesis data from even a few studies presents numerous logistical and organizational challenges. To assist with the process, researchers often turn to proprietary software, but existing programs are expensive or lack important features.
To address this need, we developed a free, easy-to-use, collaborative software program called MetaReviewer, funded by the National Science Foundation.
Evidence Gap Maps provide a structured visual framework designed to identify areas where research has been conducted, and where more research is needed.
This web application allows users to upload their own dataset and create an evidence gap map to identify gaps in the research.
This calculator computes standardized mean difference effect sizes for two-level cluster assignment designs. Effect sizes can be adjusted for baseline covariates and may be based on within, between, or total variances.
This calculator computes differential alignment, a metric for quantifying the extent to which the content foci of an outcome measure favor one treatment condition over the other. A tutorial video is available on YouTube.