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…

The Teaching and Learning International Survey (TALIS) and the Programme for International Student Assessment (PISA) are large-scale measurements about teaching and learning. There is a link between TALIS indicators and PISA results. We investigated which countries are effective according to TALIS indicators as inputs and PISA 2015 mathematics,…

The purpose of this paper is to briefly introduce two most common applications of multiple group item response theory (IRT) models, namely detecting differential item functioning (DIF) analysis and nonequivalent group score linking with a simultaneous calibration. We illustrate how to conduct those analyses using the "Stata" item…

Automated scoring of free drawings or images as responses has yet to be used in large-scale assessments of student achievement. In this study, we propose artificial neural networks to classify these types of graphical responses from a TIMSS 2019 item. We are comparing classification accuracy of convolutional and feed-forward approaches. Our…

Cheating detection is an important issue in standardized testing, especially in large-scale settings. Statistical approaches are often computationally intensive and require specialised software to conduct. We present a two-stage approach that quickly filters suspected groups using statistical testing on an IRT-based answer-copying index. We also…

The current analysis aims to research the impact of ICT usage on students' achievement in the 2018 PISA assessment, specifically achievement in mathematics, science and reading scales. In this assessment, a total of 5,058 randomly selected students from 224 schools across Kosovo took part in the study. In addition, to the subscales assessing…

Educational data mining (EDM) has been a rapidly growing research field over the last decade and enabled researchers to discover patterns and trends in education with more sophisticated methods. EDM offers promising solutions to complex educational problems. Given the rapid increase in the availability of big data in education and software…

New changes to the school curriculum by enacting a minimum competency assessment (MCA) with PISA criteria in 2021 have led to confusion over the form of MCA questions among teachers and students due to limited learning resources at schools. This study aimed to produce valid and practical PISA COVID-19 mathematics tasks (PISAComat) potentially…

This paper explores third-wave post-neoliberalism as an assemblage, fractured and dis/embodied, a mobile tool of governance articulated in various shapes across geopolitical sites. Post-neoliberalism is assembled alongside other key cultural shifts, such as post-truth, posthuman and the computational turn. In light of this Special Issue, this…

The aim of the study is to compare TIMSS 2011 proficiency levels with the proficiency levels defined by the researchers using cluster analysis for Turkey, Korean, Norway, and Morocco in 4th and 8 th grades in the fields of science and mathematics. Therefore, it is tried to be reached that these cut-off scores for each country can serve the…

TIMSS (Trends in International Mathematics and Science Study) is a long-standing international assessment of mathematics and science at the fourth and eighth grades that has been collecting trend data every four years since 1995. About 70 countries use TIMSS trend data for monitoring the effectiveness of their education systems in a global…

The purpose of this article is to introduce and review the capability and performance of the Stata item response theory (IRT) package that is available from Stata v.14, 2015. Using a simulated data set and a publicly available item response data set extracted from Programme of International Student Assessment, we review the IRT package from…

International Large Scale Assessments have been producing data about educational attainment for over 60 years. More recently however, these assessments as tests have become digitally and computationally complex and increasingly rely on the calculative work performed by algorithms. In this article I first consider the coordination of relations…

Item Response Theory (IRT) is a ubiquitous model for understanding humans based on their responses to questions, used in fields as diverse as education, medicine and psychology. Large modern datasets offer opportunities to capture more nuances in human behavior, potentially improving test scoring and better informing public policy. Yet larger…

When dealing with missing responses, two types of omissions can be discerned: items can be skipped or not reached by the test taker. When the occurrence of these omissions is related to the proficiency process the missingness is nonignorable. The purpose of this article is to present a tree-based IRT framework for modeling responses and omissions…