Background: Life satisfaction is a key component of students' subjective well-being due to its impact on academic achievement and lifelong health. Although previous studies have investigated life satisfaction through different lenses, few of them employed machine learning (ML) approaches. Objective: Using ML algorithms, the current study predicts…

Objective: Existing research demonstrates that being mastery oriented is associated with several academic outcomes such as better engagement and achievement. To date, however, there is a dearth of research evidence on the emotional payoffs of mastery orientation. The current study explored the link between mastery orientation, subjective…

This study examines the relationship between instructional quality and mathematics achievement, taking into account socioeconomic status. Data from ten European countries participating in PISA 2012 and 2022 were analysed using the framework of the Dynamic Modelling of Educational Effectiveness. In PISA 2012, instructional quality was defined by…

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…

The concept of growth mindset has been touted as a promising tool to empower learning, but mixed effects emerge. Growth mindset advocates are calling for more attention to the heterogeneity of growth mindset, namely, the interference of other factors at individual or contextual levels (e.g., teacher variables) with the relationship between growth…

The purpose of this study is to examine the effect of missing data imputation methods, namely regression imputation (RI), multiple imputation (MI) and k-nearest neighbor (kNN) on differential item functioning (DIF). In this regard, the datasets used in the research were created by deleting some of the data via the missing completely at random…

Brazil's education system lags behind international standards, with two-fifths of students scoring below the minimum level of proficiency in mathematics, science, and reading. Thus, this study combined machine learning with traditional statistics to identify the most important predictors and to interpret their effects on proficiency in the PISA…

This study explores structural relations among learning environment, achievement goals and reading achievement in China. The sample contains 12,058 Chinese students from the Programme for International Student Assessment (PISA) 2018 study. Multilevel Structural Equation Modeling (Multilevel SEM) is used for data analysis. The results indicate that…

Mathematical literacy is becoming increasingly important and needs to be developed. However, various factors can affect students with different mathematical literacy patterns. This study aims to investigate the effects of students' backgrounds, attitudes toward mathematics, and information and communication technology (ICT) familiarity on the…

Although education is arguably one of the most central institutions in contemporary European societies, only recently scholars have started to study opinions that relate to the perceived legitimacy of education among the public at large. This paper contributes to this emerging literature. Based on data from the most recent wave of the European…

The purpose of this study is to examine the predictive effects of epistemological beliefs about science and informal reading of scientific texts on students' future-oriented optimism on the issue of climate change. Future-oriented climate change optimism is defined as encompassing "hope" and "anticipation" about the climate…

The main purpose of this study was to explore major factors at student and teacher/school levels affecting middle-school students' science self-efficacy among countries with high science academic performance levels in PISA 2015 data by using various regression algorithms of machine learning and multilevel latent profile analysis (MLPA). Out of…

The education system strives to help students from low-income families achieve academic success. Academic resilience is related to not only individuals but also classrooms and schools. This study aimed to construct a comprehensive resilience model in science domains that presents the image of resilient students and describes the mechanisms by…

This study explores the factors influencing mathematics performance, teacher satisfaction, and school environment across six economies using data from PISA 2022. Employing hierarchical linear modeling, the research examines individual and institutional variables at the student, teacher, and school levels. Key findings reveal significant…

The study investigates the academic resilience of Swedish students, focusing on how school-level factors contribute to achievement differences between resilient and non-resilient students. Using data from PISA cycles from 2000 to 2015, the study employs propensity score matching and hierarchical linear modeling to examine the impact of individual,…