This paper reports a validation study based on descriptive multidimensional item response theory (DMIRT), implemented in the R package "D3mirt" by using the ERS-C, an extended version of the Relevance subscale from the Moral Foundations Questionnaire including two new items for collectivism (17 items in total). Two latent models are…

Survey instruments and assessments are frequently used in many domains of social science. When the constructs that these assessments try to measure become multifaceted, multidimensional item response theory (MIRT) provides a unified framework and convenient statistical tool for item analysis, calibration, and scoring. However, the computational…

Educational large-scale assessments (LSAs) often provide plausible values for the administered competence tests to facilitate the estimation of population effects. This requires the specification of a background model that is appropriate for the specific research question. Because the "German National Educational Panel Study" (NEPS) is…

Most researchers investigate the corrected item-total correlation of items when analyzing item discrimination in multi-dimensional structures under the Classical Test Theory, which might lead to underestimating item discrimination, thereby removing items from the test. Researchers might investigate the corrected item-total correlation with the…

We analyze a 12-item version of Raven's Standard Progressive Matrices test, traditionally scored with the sum score. We discuss some important differences between assessment in practice and psychometric modelling. We demonstrate some advanced diagnostic tools in the freely available R package, dexter. We find that the first item in the test…

The study focuses on assessing the proficiency levels of higher education students, specifically the physics achievement test (PHY 101) at the National Open University of Nigeria (NOUN). This test, like others, evaluates various aspects of knowledge and skills simultaneously. However, relying on traditional models for such tests can result in…

This study aims to examine the effects of mixture item response theory (IRT) models on item parameter estimation and classification accuracy under different conditions. The manipulated variables of the simulation study are set as mixture IRT models (Rasch, 2PL, 3PL); sample size (600, 1000); the number of items (10, 30); the number of latent…

Among current state-of-art estimation methods for multilevel IRT models, the two-stage divide-and-conquer strategy has practical advantages, such as clearer definition of factors, convenience for secondary data analysis, convenience for model calibration and fit evaluation, and avoidance of improper solutions. However, various studies have shown…

This study investigated the scalability of a cognitive multiple-choice test through the Mokken package in the R programming language for statistical computing. A 2019 mathematics West African Examinations Council (WAEC) instrument was used to gather data from randomly drawn K-12 participants (N = 2866; Male = 1232; Female = 1634; Mean age = 16.5…

The "extended Rasch modeling" (eRm) package in R provides users with a comprehensive set of tools for Rasch modeling for scale evaluation and general modeling. We provide a brief introduction to Rasch modeling followed by a review of literature that utilizes the eRm package. Then, the key features of the eRm package for scale evaluation…

Language learners are underserved if there are unlearned meanings of a word that they think they have already learned. For example, "circle" as a noun is well known, whereas its use as a verb is not. For artificial-intelligence-based support systems for learning vocabulary, assessing each learner's knowledge of such atypical but common…

Stan is a flexible probabilistic programming language providing full Bayesian inference through Hamiltonian Monte Carlo algorithms. The benefits of Hamiltonian Monte Carlo include improved efficiency and faster inference, when compared to other MCMC software implementations. Users can interface with Stan through a variety of computing…

Background and Context: Despite the increasing implementation of coding in early curricula, there are few valid and reliable assessments of coding abilities for young children. This impedes studying learning outcomes and the development and evaluation of curricula. Objective: Developing and validating a new instrument for assessing young…

This paper attempts to bridge the gap between classical test theory and item response theory. It is demonstrated that the familiar and popular statistics used in classical test theory can be translated into a Bayesian framework where all of the advantages of the Bayesian paradigm can be realized. In particular, prior opinion can be introduced and…

Readers will find several papers that address high-level issues in the use of technology in education, for example architecture and design frameworks for building online education materials or tools. Several other chapters report novel approaches to intelligent tutors or adaptive systems in educational settings. A number of chapters consider many…