Effectiveness and Efficiency Analysis of Education Systems in EU Countries Employing Secondary Big Data

L. Ringienė, J. Žilinskas, A. Jakaitienė

H. A. Le Thi, T. Pham Dinh, ir H. M. Le (Eds.), Modelling, Computation and Optimization in Information Systems and Management Sciences. Cham: Springer International Publishing: 2022, p. 271–282

DOI: 10.1007/978-3-030-92666-3_23


Abstract. High volume and special structure International Large-Scale Assessment data such as PISA (Programme for International Student Assessment), TIMSS (Trends in International Mathematics and Science Study), and others are of interest to social scientists around the world. Such data can be analysed using commercial software such as SPSS, SAS, Mplus, etc. However, the use of open-source R software for statistical calculations has recently increased in popularity. To encourage the social sciences to use open source R software, we overview the possibilities of five packages for statistical analysis of International Large-Scale Assessment data: BIFIEsurvey, EdSurvey, intsvy, RALSA, and svyPVpack. We test and compare the packages using PISA and TIMSS data. We conclude that each package has its advantages and disadvantages. To conduct a comprehensive data analysis of International Large-Scale Assessment surveys one might require to use more than one package.

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This project has received funding from European Social Fund (project No DOTSUT-39 (09.3.3-LMT-K-712-01-0018) / LSS-250000-57) under grant agreement with the Research Council of Lithuania (LMTLT).