The issue of model uncertainty has been gaining interest in education and the social sciences community over the years, and the dominant methods for handling model uncertainty are based on Bayesian inference, particularly, Bayesian model averaging. However, Bayesian model averaging assumes that the true data-generating model is within the…

For assessment scales applied to different groups (e.g., students from different states; patients in different countries), multigroup differential item functioning (MG-DIF) needs to be evaluated in order to ensure that respondents with the same trait level but from different groups have equal response probabilities on a particular item. The…

The paper investigates the potential of using international large-scale assessment studies for conducting follow-up studies testing models of educational effectiveness. The impact of teacher factors coming from the "dynamic model of educational effectiveness" and the "dialogic education theory" on student literacy achievement…

When analyzing large-scale assessments (LSAs) that use complex sampling designs, it is important to account for probability sampling using weights. However, the use of these weights in multilevel models has been widely debated, particularly regarding their application at different levels of the model. Yet, no consensus has been reached on the best…

Hierarchical linear modeling (HLM) is often used to estimate the effects of socioeconomic status (SES) on academic achievement at different levels of an educational system. However, if a prior academic achievement measure is missing in a HLM model, biased estimates may occur on the effects of student SES and school SES. Phantom effects describe…

Background: Standard methods for analysing data from large-scale assessments (LSA) cannot merely be adopted if hierarchical (or multilevel) regression modelling should be applied. Currently various approaches exist; they all follow generally a design-based model of estimation using the pseudo maximum likelihood method and adjusted weights for the…

The importance of the opportunity to learn (OTL) for mathematics achievement has been extensively researched. However, there were still unanswered questions regarding OTL's measurement, analytical level, and relationship with motivational beliefs. To fill in the gaps, we aimed to (1) scrutinize the reliability and validity of OTL, (2) investigate…

This study analyzed the latest four PISA surveys, 2009, 2012, 2015, and 2018, to explore the association between students' ICT-related use and math and science performance. Using ICT Engagement Theory as a theoretical framework and a three-level hierarchical linear modeling approach, while controlling for confounding effects, ICT-related…

The purpose of the current study was to investigate both studentlevel and school-level factors influencing reading literacy of students in Turkey by using PISA 2018 data. The study focused on reading literacy since the main subject of PISA 2018 was selected as reading literacy. The design of the study is a correlational research examining the…

The Program for International Student Assessment (PISA) is a research project conducted by the Organization for Economic Co-operation and Development, which evaluates the knowledge and skills gained by 15-year-old students over three-year terms. Within this study's' scope, the PISA 2015 data were analysed to determine whether school-related…

Background: Research has shown that achievement goals and reading instruction play important roles in students' reading performance. However, little is known about the specific effects of different types of achievement goals and reading instructional practices on reading performance in mainland China. Methods: This study used Programme of…

Using the nationally representative sample from the United States in the 2012 Programme for International Student Assessment (N = 7,429 students from 240 schools), the present study examined the effects of student help-seeking behaviors on eight measures of student mathematics achievement. To account for the multilevel structure of the data with…

Information and communication technology (ICT) is key to educational development. This study explores the mechanism influencing the use of ICT on students' science literacy. We utilized two-level hierarchical linear models and structural equation models to analyze data collected from the 2015 Program for International Student Assessment (PISA) in…

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…

This study, drawing on data from the third cycle of the Program for International Student Assessment (PISA) and employing three-level hierarchical linear modeling (HLM) as an analytic strategy, examined the relations of inquiry-based science teaching to science achievement and dispositions toward science among 170,474 15-year-old students from…