Keywords
Rasch’s model
Suh-Bolt’s model
Rasch-Masters model
matrix’ modeling of the primary grades
testing
How to Cite
Abstract
The article researches methods of imitational modeling of matrixes containing primary grading obtained in educational testing by the means of statistical programming language R. Unique algorithms and functions were developed to allow generating of matrix of the primary grades according to corresponding test of the defined structure. The importance of this approach is defined by several reasons, specifically the needs to: create reference samples; analyze primary grades by means of CTT (Clasic Test Theory) and IRT; predict basic statistical test characteristics; clarify parameters for the calibrated tasks; model independent parameters for the test takers; increase and development educator’s competency. It should be noted that input parameters could be generated or set up manually. Comparable analysis was conducted for created functions against already existing function packages, such as eRm, ltm, mcIRT, as well as statistical analysis of the generated matrixes. This analysis took into consideration the following procedures: verification of hypothesis about compatibility between generated matrixes and set parameters for the testing tasks per criteria; verification of hypothesis about equivalence of average grades in entire matrix according Student criteriа; verification of hypothesis about equality for vectors of correct answers relative frequencies by columns according to Hotteling criteriа; comparison of theoretical characteristic curves with empirical probabilities; comparison of set parameters for task complexity and parameters graded by generated matrixes with consideration of errors in grading. An experimental system of imitational modeling and analysis for testing results was created. Such system combines contemporary methods of IRT and methods of Classical Testing Theory (CTT). It allows generating matrixes of primary testing grades and performing test results analysis; permits computation of basic statistical characteristics of the test, estimation of the latent parameters, construction of characteristic curves and informational functions. The system graphic shell was generated with the help of the package Shiny. The system utilizes modeling and analysis for testing results according to basic IRT models: Rasch, Birnbaum, Suh-Bolt, Rasch-Masters. A performance verification for algorithms and functions implemented into the system has been done by utilizing several noted statistical methods and procedures; and correct execution of these algorithms has been confirmed.References
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