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…

Our research aims to predict students' academic performance by considering the variables affecting academic performance in science courses using the deep learning method from machine learning algorithms and to determine the importance of independent variables affecting students' academic performance in science courses. 445 students from 5th, 6th,…

Science, technology engineering, and mathematics (STEM) professions offer competitive earnings, tend to be compatible with technological advances, and are predicted to remain in high demand in the future. Many countries, including Greece, have prioritised STEM education on their educational agendas, aiming to prepare students for careers in these…

Adaptive science dispositions (epistemology, enjoyment, interest, and self-efficacy) have been shown to be related to schools' science climate and science literacy. School stratification may promote positive linkages among science dispositions, science literacy, and science climate. To examine the association between school stratification and such…

Inequality in the shadow? Cross-national comparisons of the effects of additional instruction on math and science performance based on PISA 2018 data Background Many educational systems worldwide are experiencing a growing demand for shadow education, which often takes the form of outside-school educational activities such as private tutoring…

Educational Data Mining (EDM) is an important tool in the field of classification of educational data that helps researchers and education planners analyse and model available educational data for specific needs such as developing educational strategies. Trends International Mathematics and Science Study (TIMSS) which is a notable study in…

This article is a response to an article written by Wang and Ma "An Examination of Plausible Score Correlation from the Trend in Mathematics and Science Study", published in the Athens Journal of Education. The purpose of this paper is to address issues with Wang's and Ma's suggestion to use analysis method for correlating plausible…

Multidimensional item response theory (MIRT) models have generated increasing interest in the psychometrics literature. Efficient approaches for estimating MIRT models with dichotomous responses have been developed, but constructing an equally efficient and robust algorithm for polytomous models has received limited attention. To address this gap,…

The aim of this study was to conduct a systematic literature review on the use of serious games in science education between 2016 and 2020 years. A total of 39 articles were included from Science Citation Index-Expanded (SCI-Expanded), Social Science Citation Index (SSCI), Arts & Humanities Citation Index (A&HCI) and Emerging Sources…

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…

Trends in International Mathematics and Science Study (TIMSS) is an international comparative study designed to measure trends in mathematics and science achievement at grades 4 and 8, as well as to collect information about educational contexts (such as students' schools, teachers, and homes) that may be related to student achievement. TIMSS has…

There is a severe shortage of Black scientists in the United States. Amid the recent national movement to dismantle systemic racism and racial injustices, many scientists publicly highlighted the prevalence of racist learning environments in STEM, contributing to the underrepresentation of Black students in STEM fields. Acknowledging this…

Large-scale assessment programs, such as the Trends in International Mathematics and Science Study (TIMSS) and the Progress in International Reading Literacy Study (PIRLS), employ item response theory (IRT) and marginal estimation methods to estimate student proficiency in specific subjects such as mathematics, science, or reading. Each of these…

Large-scale assessments (LSAs) use Mislevy's "plausible value" (PV) approach to relate student proficiency to noncognitive variables administered in a background questionnaire. This method requires background variables to be completely observed, a requirement that is seldom fulfilled. In this article, we evaluate and compare the…

Previous research has demonstrated the potential of examining log-file data from computer-based assessments to understand student interactions with complex inquiry tasks. Rather than solely providing information about what has been achieved or the accuracy of student responses ("product data"), students' log files offer additional…