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

Area of Science:

• Psychometrics and Educational Measurement
• Statistical Software Development

Background:

• Generalizability Theory (G-Theory) offers a robust framework for decomposing score variance into multiple error sources.
• Traditional G-Theory analyses demand specialized programming skills, hindering adoption by applied researchers.
• There is a need for user-friendly tools to facilitate G-Theory application in diverse research settings.

Purpose of the Study:

• Introduce projectGST, an open-source R Shiny application designed for code-free Generalizability Theory analyses.
• To provide a unified interface for both preliminary statistical analyses and G-Theory (G-Study and D-Study) components.
• To enhance the accessibility of G-Theory methodologies for applied researchers in education and other fields.

Main Methods:

• Development of an R Shiny application, projectGST, offering a graphical user interface for G-Theory.
• Integration of essential statistical analyses: descriptive statistics, normality tests, correlation matrices, Cronbach's alpha, and intraclass correlation coefficients.
• Implementation of G-Study variance component estimation and D-Study reliability optimization for crossed and nested designs.

Main Results:

• projectGST provides a unified, code-free environment for conducting comprehensive G-Theory analyses.
• The application successfully integrates preliminary statistical assessments with G- and D-Study procedures.
• Demonstrated utility through simulated datasets relevant to nonformal education assessment contexts.

Conclusions:

• projectGST significantly lowers the barrier to entry for applying Generalizability Theory in research.
• The application democratizes advanced psychometric analysis, enabling wider use of G-Theory.
• projectGST supports researchers in optimizing measurement reliability through user-friendly G-Theory implementation.