Recent developments in the use of large-language models have led to substantial improvements in the accuracy of content-based automated scoring of free-text responses. The reported accuracy levels suggest that automated systems could have widespread applicability in assessment. However, before they are used in operational testing, other aspects of…

Equating error is usually small relative to the magnitude of measurement error, but it could be one of the major sources of error contributing to mean scores of large groups in educational measurement, such as the year-to-year state mean score fluctuations. Though testing programs may routinely calculate the standard error of equating (SEE), the…

The study presents multivariate sequential monitoring procedures for examining test-taking behaviors online. The procedures monitor examinee's responses and response times and signal aberrancy as soon as significant change is identifieddetected in the test-taking behavior. The study in particular proposes three schemes to track different…

Abstract This study proposes a new Bayesian differential item functioning (DIF) detection method using posterior predictive model checking (PPMC). Item fit measures including infit, outfit, observed score distribution (OSD), and Q1 were considered as discrepancy statistics for the PPMC DIF methods. The performance of the PPMC DIF method was…

The residual differential item functioning (RDIF) detection framework was developed recently under a linear testing context. To explore the potential application of this framework to computerized adaptive testing (CAT), the present study investigated the utility of the RDIF[subscript R] statistic both as an index for detecting uniform DIF of…

Orlando and Thissen (2000) introduced the "S - X[superscript 2]" item-fit index for testing goodness-of-fit with dichotomous item response theory (IRT) models. This study considers and evaluates an alternative approach for computing "S - X[superscript 2]" values and other factors associated with collapsing tables of observed…

Explanatory item response models (EIRMs) have been applied to investigate the effects of person covariates, item covariates, and their interactions in the fields of reading education and psycholinguistics. In practice, it is often assumed that the relationships between the covariates and the logit transformation of item response probability are…

Despite the growing interest in incorporating response time data into item response models, there has been a lack of research investigating how the effect of speed on the probability of a correct response varies across different groups (e.g., experimental conditions) for various items (i.e., differential response time item analysis). Furthermore,…