We analyse the PISA-reported convergence in the performance of private and public schools in Portugal. When PISA sampling weights are used, the number of students enrolled in those types of schools and specific grades/tracks of study differs significantly from official population figures. To account for those differences, we apply a…

The use of multistage adaptive testing (MST) has gradually increased in large-scale testing programs as MST achieves a balanced compromise between linear test design and item-level adaptive testing. MST works on the premise that each examinee gives their best effort when attempting the items, and their responses truly reflect what they know or can…

Many international large-scale assessments (ILSAs) have switched to multistage adaptive testing (MST) designs to improve measurement efficiency in measuring the skills of the heterogeneous populations around the world. In this context, previous literature has reported the acceptable level of model parameter recovery under the MST designs when the…

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…

This study investigates the impact of violating the local item independence assumption by loading certain items onto a second dimension on test equating errors in unidimensional and dichotomous tests. The research was designed as a simulation study, using data generated based on the PISA 2018 mathematics exam. Analyses were conducted under 36…

We examined the performance of coefficient alpha and its potential competitors (ordinal alpha, omega total, Revelle's omega total [omega RT], omega hierarchical [omega h], greatest lower bound [GLB], and coefficient "H") with continuous and discrete data having different types of non-normality. Results showed the estimation bias was…

Process data are becoming more and more popular in education research. In the field of computer-based assessments of collaborative problem solving (ColPS), process data have been used to identify students' test-taking strategies while working on the assessment, and such data can be used to complement data collected on accuracy and overall…

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…

In this study, it was aimed to compare different normalization methods employed in model developing process via artificial neural networks with different sample sizes. As part of comparison of normalization methods, input variables were set as: work discipline, environmental awareness, instrumental motivation, science self-efficacy, and weekly…

Mixture Rasch (MixRasch) models conventionally assume normal distributions for latent ability. Previous research has shown that the assumption of normality is often unmet in educational and psychological measurement. When normality is assumed, asymmetry in the actual latent ability distribution has been shown to result in extraction of spurious…

When there are no personal consequences associated with test performance for examinees, rapid guessing (RG) is a concern and can differ between subgroups. To date, the impact of differential RG on item-level measurement invariance has received minimal attention. To that end, a simulation study was conducted to examine the robustness of the…

This study aims to compare the performances of the artificial neural network, decision trees and discriminant analysis methods to classify student achievement. The study uses multilayer perceptron model to form the artificial neural network model, chi-square automatic interaction detection (CHAID) algorithm to apply the decision trees method and…

Measures of variability are successfully used in predictive modeling in research areas outside of education. This study examined how standard deviations can be used to address research questions not easily addressed using traditional measures such as group means based on index variables. Student survey data were obtained from the Organisation for…

The Programme for International Student Assessment (PISA) is an important international study of 15-year-olds' academic achievement. Although PISA has traditionally been used to draw comparisons across countries, there is growing interest in the production of regional (i.e. city,state, or provincial level) results. In this paper we present the…

Automatic coding of short text responses opens new doors in assessment. We implemented and integrated baseline methods of natural language processing and statistical modelling by means of software components that are available under open licenses. The accuracy of automatic text coding is demonstrated by using data collected in the "Programme…