Psychometrics has recently seen the development of complex measurement models to better represent test and item data. Item Response Theory (IRT), in particular, comprises a set of non-linear latent variable models that appear to have several conceptual and empirical properties that make them more valuable in practice than classical test theory methods. However, IRT-based models typically requir...

The popularity of intelligent tutoring systems (ITSs) is increasing rapidly. In order to make learning environments more efficient, researchers have been exploring the possibility of an automatic adaptation of the learning environment to the learner or the context. One of the possible adaptation techniques is adaptive item sequencing by matching the difficulty of the items to the learner’s know...

A version of sequential mastery testing is studied in which response behavior is modeled by an item response theory (IRT) model. First, a general theoretical framework is sketched that is based on a combination of Bayesian sequential decision theory and item response theory. A discussion follows on how IRT based sequential mastery testing can be generalized to adaptive item and testlet selectio...

There are two currently popular statistical frameworks for addressing measurement problems namely Classical Test Theory (CTT) and Item Response Theory (IRT). This study is aimed empirically to examine the similarities and differences in the parameters estimated using these two frameworks. For this purpose, firstly the model assumptions and the goodness of fit analyses were checked for IRT. The ...

This study aimed at examining the issues affecting the use of IRT models in investigating differential item functioning in high stakes testing. It specifically focused on the Iranian National University Entrance Exam (INUEE) Special English Subtest. A sample of 200,000 participants was randomly selected from the candidates taking part in the INUEE 2003 and 2004 respectively. The data collected ...

This article provides analytic evaluations of population true-score measures for binary items given their item response theory (IRT) calibration. Under the assumption of normal trait distribution, the expected values of marginalized true scores, error variance, true score variance, and reliability for norm-referenced and criterion-referenced interpretations are presented as a function of the it...

The authors discuss the applicability of nonparametric item response theory (IRT) models to the construction and psychometric analysis of personality and psychopathology scales, and they contrast these models with parametric IRT models. They describe the fit of nonparametric IRT to the Depression content scale of the Minnesota Multiphasic Personality Inventory--2 (J. N. Butcher, W. G. Dahlstrom...

This article shows the application of Item Response Theory (IRT) for educational evaluation using games. The article proposes a computational model to create user profiles, called Psychometric Profile Generator (PPG). PPG uses the IRT mathematical model for exploring the levels of skills and behaviors in the form of items and/or stimuli. The model was integrated with an educational game. The ga...

Item response theory (IRT) models are factor for dichotomous or polytomous variables (i.e., item responses). The symmetric logistic probit link functions most frequently utilized modeling items. In this article, we propose an IRT model and items using the asymmetric generalistic function that covers a lot of functions. Compared to based on function, generalized additionally estimates two parame...