projectgst: A Shiny Application for Generalizability Study Analysis in Nonformal Education Settings

Generalizability Theory (G-Theory) extends classical reliability estimation by simultaneously de-composing score variance into multiple sources of measurement error such as raters, occasions, and items within a single analytical framework. Despite its methodological advantages, G-Theory analyses typically require specialized programming expertise, limiting accessibility for applied researchers. This paper introduces projectGST, an open-source R Shiny application that provides a unified, code-free interface for conducting G-Theory analyses. The application integrates preliminary statistical analyses including descriptive statistics, normality tests, inter-rater correlation matrices, Cronbach's alpha, and intraclass correlation coefficients with G-Study variance component estimation and D-Study reliability optimization. projectgst supports both crossed and nested measurement designs and is illustrated using simulated datasets representative of nonformal education assessment contexts, including tutor evaluations at community learning centers and portfolio-based assessments in equivalency education programs. The application is openly accessible via a hosted Shiny interface and GitHub repository.