17:00 - 17:45
Room:
Chair/s:
Julian Scherhag
ELD CAMA platform for educational interventions
Mon-02
Presented by: Lucija Batinovic
Lucija Batinovic *, André Kalmendal
Background:
Community-augmented meta-analysis (CAMA) platforms have begun to set a new standard for promoting FAIR (findable, accessible, interoperable, reusable) data sharing. They allow dynamic and interactive meta-analysis of data and ensure reproducibility of results (Tsuji et al., 2014). As the area of disability research and education moves towards open science practices, the newly created CAMA platform sets to facilitate data sharing of meta-analyses and make evidence-based practice accessible to practitioners. Furthermore, we aim to promote high-quality standards in conducting evidence synthesis, which are still not readily implemented in the education research area (Nordström et al., 2022).

Objectives of the CAMA platform:
The Evidence in Learning and Didactics, and Disability research CAMA platform will provide meta-analytic tools to conduct both frequentist (http://194.47.110.50:3838/visualization/), and Bayesian meta-analyses (http://194.47.110.51:3838/) of educational interventions for typically developing and students with intellectual disability. Studies will be subdivided into categories of typically developing students and students with intellectual disability, with further subdivision of educational domains: writing, reading, math, science, and other.

First objective: Create a platform that facilitates sharing of high-quality meta-analyses. The platform will allow publication bias assessment, effect size aggregation and moderator analysis. One important feature of this CAMA platforms is the ability to do analyses based on risk of bias assessments. Quality assessment and risk of bias estimation will be mandatory for dataset inclusion and it will be possible to conduct analyses on studies with different risks of bias estimation.

Second objective: Create a platform that is valuable both as a pedagogical and research tool. Apps will allow high flexibility in model building and provide an interface that provides plain and technical explanations/summaries of statistical outputs. The goal is to have the apps become an easy-to-use tool for students and researchers aiming to conduct meta-analyses and serve as a guide on evidence based practices for practitioners.

References
Nordström, T., Kalmendal, A., & Batinovic, L. (2022, October 4). Risk of bias and open science practices in systematic reviews in education research: A meta-review. https://doi.org/10.31234/osf.io/5xumg
Tsuji, S., Bergmann, C., & Cristia, A. (2014). Community-Augmented Meta-Analyses: Toward Cumulative Data Assessment. Perspectives on Psychological Science, 9(6), 661–665. https://doi.org/10.1177/1745691614552498