Cultivating students' enjoyment of science is one of the significant aims of science education. However, it seems challenging to achieve this goal in most countries or economies. Using the Trends in International Mathematics and Science Study (TIMSS) 2019 Hong Kong data, this study aims to identify multiple configurations of school conditions to…

The jigsaw model is a dynamic cooperative learning approach where students become experts on different segments of the material and teach their peers, thereby enhancing engagement accountability, team work, and ultimately improving academic achievement. This study investigated the effectiveness of a cooperative learning strategy on secondary…

Persistent concerns exist regarding the relationship between socioeconomic status (SES) and science achievement, prompting ongoing research into the factors enabling some low-SES students to excel in science despite the odds. This study seeks to identify multiple combinations of individual, family, and school conditions that contribute to…

Predicting student performance in international large-scale assessments (ILSAs) is crucial for understanding educational outcomes on a global scale. ILSAs, such as the Program for International Student Assessment and the Trends in International Mathematics and Science Study, serve as vital tools for policymakers, educators, and researchers to…

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…

International large-scale assessments (ILSA) are an important source of information for education policymakers across the globe. Despite sponsors' warnings, when results are published, media attention focuses on country rankings and changes in scores. Score changes are evaluated using a two-sided z-statistic, with statistical significance declared…

In this quasi-experimental study, we examined STEMscopes program impacts on science achievement in Longhorn ISD. The report specifically analyzed STEMscopes impacts on STAAR and MAP Growth scores. The present study used a school-level quasi-experimental design, where 8 STEMscopes schools were selected for inclusion and 8 comparison schools (using…

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…

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 focused on the relationships between teacher characteristics and students' mathematics achievement in EU countries, including Hungary, Italy, Lithuania, Malta, Slovenia, Sweden, and Turkey, which are the only EU countries participated in TIMSS 2015 at the eighth-grade level. The data consisted of the sample of 31,969 eighth-grade…

Previous research has indicated that attitudes influence various factors contributing to scientific achievement. Inadequate performance in science can limit career opportunities, underscoring the importance of comprehending how attitudes towards science can enhance overall scientific achievement. This study explored the mediating effect of…

This study examines the relationship between instructional clarity in physics lessons and students' motivation and self-confidence to learn physics. We conducted a secondary analysis of data from the Trends in International Mathematics and Science Study (TIMSS) 2019. Using data from six countries, whose students' science achievement scores were…

The purpose of this study is to demonstrate clustering methods within a functional data analysis (FDA) framework for identifying subgroups of individuals that may be exhibiting categories of misfit. Person response functions (PRFs) estimated within a FDA framework (FDA-PRFs) provide graphical displays that can aid in the identification of persons…

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…

A school's emphasis on academic success (SEAS) is a crucial aspect of school climate that can be rated by different informants, such as teachers or principals, and with respect to their perception of different groups' emphasis on academic success, such as parents or students. We know little about whether there is agreement between these ratings.…