PISA aims to serve as a "global yardstick" for educational success, as measured by student performance. For comparisons to be meaningful across countries or over time, PISA samples must be representative of the population of 15-year-old students in each country. Exclusions and non-response can undermine this representativeness and…

Background: In the context of large-scale educational assessments, the effort required to code open-ended text responses is considerably more expensive and time-consuming than the evaluation of multiple-choice responses because it requires trained personnel and long manual coding sessions. Aim: Our semi-supervised coding method eco (exploring…

International large-scale assessments provide cross-national data on students' cognitive and non-cognitive characteristics. A critical methodological issue that often arises in comparing data from cross-national studies is ensuring measurement invariance, indicating that the construct under investigation is the same across the compared groups.…

The purpose of this paper is to demonstrate and evaluate the use of "Bayesian dynamic borrowing"(Viele et al, in Pharm Stat 13:41-54, 2014) as a means of systematically utilizing historical information with specific applications to large-scale educational assessments. Dynamic borrowing via Bayesian hierarchical models is a special case…

This study seeks to compare fixed and mixed effects models for the purposes of predictive classification in the presence of multilevel data. The first part of the study utilizes a Monte Carlo simulation to compare fixed and mixed effects logistic regression and random forests. An applied examination of the prediction of student retention in the…

Group differences in test scores are a key metric in education policy. Response time offers novel opportunities for understanding these differences, especially in low-stakes settings. Here, we describe how observed group differences in test accuracy can be attributed to group differences in latent response speed or group differences in latent…

The prevalence and serious consequences of noneffortful responses from unmotivated examinees are well-known in educational measurement. In this study, we propose to apply an iterative purification process based on a response time residual method with fixed item parameter estimates to detect noneffortful responses. The proposed method is compared…

This paper reviews overall student performance as well as the performance of student subgroups on the assessment system developed in response to the Massachusetts Education Reform Act of 1993 (MERA), the Massachusetts Comprehensive Assessment System (MCAS). Comparing students in Massachusetts to students in the rest of the United States or against…

The present paper investigates and examines the conditional dependencies between cognitive responses (RA; Response Accuracy) and process data, in particular, response times (RT) in large-scale educational assessments. Using two prominent large-scale assessments, NAEP and PISA, we examined the RA-RT conditional dependencies within each item in the…

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…

The aim of the current research was to provide recommendations to facilitate the development and use of anchoring vignettes (AVs) for cross-cultural comparisons in education. Study 1 identified six factors leading to order violations and ties in AV responses based on cognitive interviews with 15-year-old students. The factors were categorized into…

Response process data have the potential to provide a rich description of test-takers' thinking processes. However, retrieving insights from these data presents a challenge for educational assessments and educational data mining as they are complex and not well annotated. The present study addresses this challenge by developing a computational…

It is crucial to examine the alignment of different exam results conducted by various organizations to improve the quality of assessment. The research used a document analysis method with recent, publicly available national and international reports addressing the research question. The following main question was examined through the document…

The purpose of this research was to determine classification accuracy of the factors affecting the success of students' reading skills based on PISA 2018 data by using Artificial Neural Networks, Decision Trees, K-Nearest Neighbor, and Naive Bayes data mining classification methods and to examine the general characteristics of success groups. In…

Large-scale assessments such as the Programme for International Student Assessment (PISA) have field trials where new survey features are tested for utility in the main survey. Because of resource constraints, there is a trade-off between how much of the sample can be used to test new survey features and how much can be used for the initial item…