RALSA: The R Analyzer for Large-Scale Assessments

Autor/in	Mirazchiyski, Plamen V.
Titel	RALSA: The R Analyzer for Large-Scale Assessments
Quelle	In: Large-scale Assessments in Education, 9 (2021), Artikel 21 (24 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Mirazchiyski, Plamen V.)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	2196-0739
DOI	10.1186/s40536-021-00114-4
Schlagwörter	Measurement; Data Analysis; Open Source Technology; Computer Software + Suchen Sie Ihr Suchwort? Messverfahren; Auswertung
Abstract	This paper presents the R Analyzer for Large-Scale Assessments (RALSA), a newly developed R package for analyzing data from studies using complex sampling and assessment designs. Such studies are, for example, the IEA's Trends in International Mathematics and Science Study and the OECD's Programme for International Student Assessment. The package covers all cycles from a broad range of studies. The paper presents the architecture of the package, the overall workflow and illustrates some basic analyses using it. The package is open-source and free of charge. Other software packages for analyzing large-scale assessment data exist, some of them are proprietary, others are open-source. However, RALSA is the first comprehensive R package, designed for the user experience and has some distinctive features. One innovation is that the package can convert SPSS data from large scale assessments into native R data sets. It can also do so for PISA data from cycles prior to 2015, where the data is provided in tab-delimited text files along with SPSS control syntax files. Another feature is the availability of a graphical user interface, which is also written in R and operates in any operating system where a full copy of R can be installed. The output from any analysis function is written into an MS Excel workbook with multiple sheets for the estimates, model statistics, analysis information and the calling syntax itself for reproducing the analysis in future. The flexible design of RALSA allows for the quick addition of new studies, analysis types and features to the existing ones. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01