Profile analysis is one of the main tools for studying whether differential item functioning can be related to specific features of test items. While relevant, profile analysis in its current form has two restrictions that limit its usefulness in practice: It assumes that all test items have equal discrimination parameters, and it does not test…

Conducting a fair test is important for educational research. Unfair assessments can lead to gender disparities in academic achievement, ultimately resulting in disparities in opportunities, wages, and career choice. Differential Item Function [DIF] analysis is presented to provide evidence of whether the test is truly fair, where it does not harm…

Writing assessments often consist of students responding to multiple prompts, which are judged by more than one rater. To establish the reliability of these assessments, there exist different methods to disentangle variation due to prompts and raters, including classical test theory, Many Facet Rasch Measurement (MFRM), and Generalizability Theory…

Economic efficiency demands accurate assessment of individual ability for selection purposes. This study investigates Classical Test Theory (CTT) and Item Response Theory (IRT) for estimating true ability and ranking individuals. Two Monte Carlo simulations and real data analyses were conducted. Results suggest a slight advantage for IRT, but…

Learning strategies have been recognized as important predictors of mathematical achievement. In recent studies, it has been found that Asian students use combined learning strategies, primarily including metacognitive strategies, rather than rote memorization. To the best of the authors' knowledge, there is only one prior study including South…

The investigation delves into examining the influence of 2-parameter logistic (PL) and 3-parameter logistic models on the ability estimates of students in mathematical binary items. It ascertained the parameters of the items in the 2-PL and 3-PL models. We employed Item Response Theory (IRT) in the design of this research survey, with a sample…

Determining the most appropriate method of scoring an assessment is based on multiple factors, including the intended use of results, the assessment's purpose, and time constraints. Both the dichotomous and partial credit models have their advantages, yet direct comparisons of assessment outcomes from each method are not typical with constructed…

The focus of this study is to use the mixture item response theory (MixIRT) model while implementing the no-U-turn sampler as a technique for investigating the presence of latent classes (i.e., subpopulations) among eighth-grade students who were administered TIMSS 2019 mathematics subtest in paper format from the gulf cooperation council (GCC)…

Common indicator-based approaches to identifying careless and insufficient effort responding (C/IER) in survey data scan response vectors or timing data for aberrances, such as patterns signaling straight lining, multivariate outliers, or signals that respondents rushed through the administered items. Each of these approaches is susceptible to…

Assessments built on a theory of learning progressions are promising formative tools to support learning and teaching. The quality and usefulness of those assessments depend, in large part, on the validity of the theory-informed inferences about student learning made from the assessment results. In this study, we introduced an approach to address…

Persistence represents a crucial trait in learning. A lack of persistence prevents learners from fully mastering their current skills and makes it difficult for them to acquire new skills. It further hinders the administration of effective interventions by learning systems. Although most studies have focused on identifying non-persistence and…

The Programme for International Student Assessment (PISA) student questionnaire, despite being designed for low cognitive demand, may induce test burden due to its 306-item length, resulting in increased item nonresponse toward the questionnaire's end. Using the PISA 2018 response data from 80 countries and a cross-classified mixed effects model,…

Science, Technology, Engineering, and Math (STEM) skills are increasingly required of students to be successful in higher education and the workforce. Therefore, modeling assessment outcomes accurately, often using more types of student data to get a complete picture of student learning, is increasingly relevant. The Program for International…

Local Item Dependence (LID) is a desecration of Local Item Independence (LII) which can lead to overestimating or underestimating a candidate's ability in mathematics items and create validity problems. The study investigated the intra and inter-LID of mathematics items. The study made use of ex-post facto research. The population encompassed all…

Because non-cognitive constructs can influence student success in education beyond academic achievement, it is essential that they are reliably conceptualized and measured. Within this context, there are several gaps in the literature related to correctly interpreting the meaning of scale scores when a non-standard response option like I do not…