The aim of the study is to examine the effect of polytomous item ratio on ability estimation in different conditions in multistage tests (MST) using mixed tests. The study is simulation-based research. In the PISA 2018 application, the ability parameters of the individuals and the item pool were created by using the item parameters estimated from…

There is ongoing debate regarding what performance on the number line estimation task represents and its role in mathematics learning. The patterns followed by children's estimates on the number line task could provide insight into this. This study investigates children's estimation patterns on the number line task and assesses whether mathematics…

The Mantel-Haenszel estimator is one of the most popular techniques for measuring differential item functioning (DIF). A generalization of this estimator is applied to the context of DIF to compare items by taking the covariance of odds ratio estimators between dependent items into account. Unlike the Item Response Theory, the method does not rely…

In this new era, computational thinking is becoming increasingly intriguing for indepth study. The 2022 PISA framework illustrates that computational thinking can play a significant role in solving real-world mathematical problems, both in formulating problems and in mathematical reasoning processes. Many countries have integrated computational…

The introduction of computing education into curricula worldwide requires multi-year assessments to evaluate the long-term impact on learning. However, no single Computational Thinking (CT) assessment spans primary school, and no group of CT assessments provides a means of transitioning between instruments. This study therefore investigated…

This paper extends existing work on teacher weighting in student-centered surveys by looking into aspects of practical implementation of deriving and using weights for teacher-centered analysis in the Trends in International Mathematics and Science Study (TIMSS) and the Progress in International Reading Literacy Study (PIRLS). The formal…

With the growing attention on large-scale educational testing and assessment, the ability to process substantial volumes of response data becomes crucial. Current estimation methods within item response theory (IRT), despite their high precision, often pose considerable computational burdens with large-scale data, leading to reduced computational…

This dissertation in practice explores the intersection of computer science education, specifically computational thinking and programming, with mathematics achievement among 15- year-old students in selected English-speaking countries. The research addresses a gap in understanding whether skills developed through computer science can positively…

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…

This article presents a latent class model for multilevel data to identify latent subgroups and estimate heterogeneous treatment effects. Unlike sequential approaches that partition data first and then estimate average treatment effects (ATEs) within classes, we employ a Bayesian procedure to jointly estimate mixing probability, selection, and…

In this paper, six mathematics curriculum changes in Iran will be reviewed, spanning from 1900 until the present time. At first, change forces, barriers, and the main features of each curriculum reform will be represented. The first five curriculum changes are described briefly and the sixth and most recent curriculum reform will be elaborated. In…

One major aim of international large-scale assessments (ILSAs) is to monitor changes in student performance over time. To accomplish this task, a set of common items is repeatedly administered in each assessment and linking methods are used to align the results from the different assessments on a common scale. The present article introduces a…

There has been increasing interest in exploring heterogeneous treatment effects using machine learning (ML) methods such as causal forests, Bayesian additive regression trees, and targeted maximum likelihood estimation. However, there is little work on applying these methods to estimate treatment effects in latent classes defined by…

The aim of this study was to investigate current trends in research of math anxiety (MA) through bibliometric perspective. Three main clusters were formed based on author keywords: cognitive correlates (working memory, attention, numerical cognition, mental arithmetic), psychological factors and effects (self-concept and self-efficacy, motivation,…

The goal of this study was to provide normative scores and examine the psychometric properties of the Math Computation subtest of the Wide Range Achievement Test--IV (WRAT-IV) for Mexican adolescents after the completion of junior high school. We group-administered this subtest to 1,318 first-year Mexican high school students. We then obtained its…