Bayesian Networks (BNs) are probabilistic graphical statistical models that have been widely used in many fields over the last decade. This method, which can also be used for educational data mining (EDM) purposes, is a fairly new method in education literature. This study models students' science success using the BN approach. Science is one of…

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…

The purpose of the current study is to examine malleable school practices and norms that contribute to inequitable school learning environments based on student background. Using multilevel structural equation modeling (SEM) with the U.S. sample of PISA 2015, this study examines the extent to which student-level access to inquiry-based science…

The present study ascertains the relationship between socioeconomic status (SES) and students' science self-efficacy using data involving 509,182 15-year-old students and 17,678 school principals in 69 countries/regions who participated in the Programme for International Student Assessment (PISA) 2015. Hierarchical linear modelling results show…

The objective of the present study was to investigate item-, examinee-, and country-level correlates of rapid guessing (RG) in the context of the 2018 PISA science assessment. Analyzing data from 267,148 examinees across 71 countries showed that over 50% of examinees engaged in RG on an average proportion of one in 10 items. Descriptive…

Determining the ethnic differences in academic performance among immigrant students is important in terms of adapting them into the system they live in. Examining the variables related to students' performance will be a guide in overcoming the issue. The purpose of this study is to examine the direct effect of economic, social, and cultural status…

This research intended to identify key contextual factors that synergistically influence high- and low-performing students' science outcomes by drawing upon a dynamic model of educational effectiveness. The dataset, the Programme for International Student Assessment (PISA) 2015, consisted of 79,963 science scores for secondary students (49,924…

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…

Seen as one of the essential domains for active citizenship, examining how students relate to science has become crucial. Based on a person-centered approach, this article investigates self-related dispositions and motivation in science using the 2015 Programme for International Student Assessment (PISA) data set. By employing a latent profile…

The present study explores the antecedents of first- and second-generation (1G and 2G) immigrant students' academic performance using PISA 2018 data. The study draws on an international sample of 11,582 students from 534 schools in 20 countries and focuses on PISA schools that catered to a mix of 1G and 2G students. The study explores the role…

Large scale educational assessments conducted in the United Arab Emirates (UAE) show a substantial gap between the performance of different types of schools. This study used the 2015 Program of International Student Assessment (PISA) to investigate how student- and school-related variables accounted for the variation among schools. The results…

This study examines the data of students from the United States (n = 2,592) who participated in the 2018 Programme for International Student Assessment (PISA). The purpose of this study is to probe the relationship between students' use of information and communication technologies (ICT) and their academic performance in mathematics and science.…

In 2021, an OECD team undertook analysis of Republic of Türkiye's data from two international assessments--the OECD Programme for International Student Assessment (PISA) and the International Association for the Evaluation of Educational Achievement (IEA)'s Trends in International Mathematics and Science Study (TIMSS). The analysis aimed to…

The advantages and disadvantages of single-sex schooling continue to be a source of policy and public debate. Previous empirical evidence is somewhat ambiguous, with some studies finding a positive impact of single-sex schooling on education achievement and others finding no differences across school types. The relationship between single-sex…

In our age of big data and growing computational power, versatility in data analysis is important. This study presents a flexible way to combine statistics and machine learning for data analysis of a large-scale educational survey. The authors used statistical and machine learning methods to explore German students' attitudes towards information…