Secondary analyses of international large-scale assessments (ILSA) commonly characterize relationships between variables of interest using correlations. However, the accuracy of correlation estimates is impaired by artefacts such as measurement error and clustering. Despite advancements in methodology, conventional correlation estimates or…

The article explores the importance of early reading proficiency and its long-term impact on academic and life outcomes, particularly in Romania. Analyzing PISA data, the article highlights significant literacy gaps between advantaged and disadvantaged students, as well as urban and rural learners. These disparities perpetuate intergenerational…

Data analysis is a significant methodological component when conducting quantitative education studies. Guidelines for conducting data analyses in quantitative education studies are common but often underemphasize four important methodological components impacting the validity of inferences: quality of constructed measures, proper handling of…

Mechanisms causing item nonresponses in large-scale assessments are often said to be nonignorable. Parameter estimates can be biased if nonignorable missing data mechanisms are not adequately modeled. In trend analyses, it is plausible for the missing data mechanism and the percentage of missing values to change over time. In this article, we…

The purpose of this study is to compare decision trees obtained by data mining algorithms used in various areas in recent years according to different criteria. In the study, similar and different aspects of the decision trees obtained by different methods for classifying the students as successful and unsuccessful in terms of science literacy…

Comparing group is one of the key uses of large-scale assessment results, which are used to gain insights to inform policy and practice and to examine the comparability of scores and score meaning. Such comparisons typically focus on examinees' final answers and responses to test questions, ignoring response process differences groups may engage…

This paper examines the Organisation for Economic Cooperation and Development's (OECD) PISA for Schools, a local variant of the more-renowned 'main PISA' test that measures and compares individual school performance on reading, mathematics and science against international schooling systems. Here, I address the governance implications of how PISA…

Science literacy, which is included in Programme for International Student Assessment (PISA) as an assessment area, is an important research and discussion area of science education literature with all its dimensions. In this study, the clustering results of the students from 34 Organization for Economic Cooperation and Development (OECD)…

Purpose: Fabricated data jeopardize the reliability of large-scale population surveys and reduce the comparability of such efforts by destroying the linkage between data and measurement constructs. Such data result in the loss of comparability across participating countries and, in the case of cyclical surveys, between past and present surveys.…

This article examines emerging techniques of educational governance--based on time, difference and potential--enabled by the Organisation for Economic Cooperation and Development's PISA-based Test for Schools ('PISA for Schools'). I show how PISA for Schools facilitates the production of difference through comparative test data, allowing educators…

Two separate data searches underlie this analysis of how references to educational research and to PISA are used in the Swedish education debate. The data consist of 380 newspaper articles from the eight largest print media outlets in Sweden and 200 protocols from parliamentary debates (2000 to 2016) that made explicit reference to 'PISA' and/or…

Educational institutions and governing practices are increasingly augmented with digital database technologies that function as new kinds of policy instruments. This article surveys and maps the landscape of digital policy instrumentation in education and provides two detailed case studies of new digital data systems. The Learning Curve is a…

The Australian Institute of Health and Welfare developed a national data standards strategy and implementation plan to enhance the comparability, quality and coherence of information across the Australian education and training sectors, including early childhood education, school education, vocational education and training (VET) and higher…

Certain stereotypes can be associated with people from different countries. For example, the Italians are expected to be emotional, the Germans functional, and the Chinese hard-working. In this study, we cluster all 15-year-old students representing the 68 different nations and territories that participated in the latest Programme for…

Multiple imputation (MI) can be used to address missing data at Level 2 in multilevel research. In this article, we compare joint modeling (JM) and the fully conditional specification (FCS) of MI as well as different strategies for including auxiliary variables at Level 1 using either their manifest or their latent cluster means. We show with…