Item response theory (IRT) models are commonly used in the realm of educational and psychological testing. The three commonly used IRT models for responses that are graded as either correct or incorrect are the One-parameter, Two-parameter, and Three parameter IRT models. These models are used to calibrate standardized tests and to assess human latent traits such as student’s overall intelligen...

The evolution from static to dynamic electronic learning environments has stimulated the research on adaptive item sequencing. A prerequisite for adaptive item sequencing, in which the difficulty of the item is constantly matched to the knowledge level of the learner is to have items with a known difficulty level. The difficulty level can be estimated by means of the item response theory (IRT),...

1 Abstract Item response theory (IRT) has arguably been one of the most successful and widely used statistical modeling techniques in psychometrics, with applications in developmental, social, educational and cognitive psychology for example, as well as in medical research, demography and other social science settings. In this paper I will try to briefly summarize some of the important research...

In this research, we use Item Response Theory based model for computing procedural knowledge of a sample of primary school children solving fraction addition exercises. For each exercise, the model needs to automatically construct a solution graph. We have explored different strategies for building such graphs and the effects they have on the quality of the model predictions. The results obtain...

In a typical questionnaire testing situation, examinees are not allowed to choose which items they answer because of a technical issue in obtaining satisfactory statistical estimates of examinee ability and item difficulty. This paper introduces a new item response theory (IRT) model that incorporates information from a novel representation of questionnaire data using network analysis. Three sc...

The issue of latent trait granularity in diagnostic models is considered, comparing and contrasting latent trait and latent class models used for diagnosis. Relationships between conjunctive cognitive diagnosis models (CDMs) with binary attributes and noncompensatory multidimensional item response models are explored, leading to a continuous generalization of the Noisy Input, Deterministic ‘‘An...

BACKGROUND The International Classification of Functioning, Disability and Health (ICF) proposes three main health outcomes, Impairment (I), Activity Limitation (A) and Participation Restriction (P), but good measures of these constructs are needed The aim of this study was to use both Classical Test Theory (CTT) and Item Response Theory (IRT) methods to carry out an item analysis to improve me...

We introduce a new skew-probit link for item response theory (IRT) by considering an accumulated skew-normal distribution. The model extends the symmetric probit-normal IRT model by considering a new item (or skewness) parameter for the item characteristic curve. A special interpretation is given for this parameter, and a latent linear structure is indicated for the model when an augmented like...

This note provides a direct, elementary proof of the fundamental result on monotone likelihood ratio of the total score variable in unidimensional item response theory (IRT). This result is very important for practical measurement in IRT, because it justifies the use of the total score variable to order participants on the latent trait. The proof relies on a basic inequality for elementary symm...

Abstract: In this paper we consider the well known two-parameter logistic model from the Item Response Theory (IRT) and suppose the presence of several latent classes among the test population which classes differ each other in the item parameter structure. We give a computer implementation of this model and also empirically examine the model by means of a software test simulator. Parameters ar...