Item difficulty and dimensionality often correlate, implying that unidimensional IRT approximations to multidimensional data (i.e., reference composites) can take a curvilinear form in the multidimensional space. Although this issue has been previously discussed in the context of vertical scaling applications, we illustrate how such a phenomenon…

Purpose: Listening effort is a broad construct, and there is no consensus on how to subdivide listening effort into dimensions. This project focuses on the subjective experience of effortful listening and tests if cognitive workload, mental fatigue, and mood are interrelated dimensions. Method: Two online studies tested young adults (n = 74 and n…

Measuring cognitive load is important in virtual learning environments (VLE). Thus, valid and reliable measures of cognitive load are important to support instructional design in VLE. Through three studies, we investigated the validity and reliability of Leppink's Cognitive Load Scale (CLS) and developed the extraneous cognitive load (EL)…

School psychologists use intelligence and academic achievement test scores to understand individual differences in abilities that may be directed towards learning and the learning that has already occurred. To make ethical and effective decisions regarding individualized educational programs and interventions, test users must understand the…

This research aimed to explore the upper-secondary school chemistry teachers' and students' conceptual structures of atomic structure by using multidimensional scaling. Atomic structure is considered to be one of the most difficult concepts in upper-secondary school chemistry course so that the conceptual structure regarding atomic structure held…

An essential feature of the linear logistic test model (LLTM) is that item difficulties are explained using item design properties. By taking advantage of this explanatory aspect of the LLTM, in a mixture extension of the LLTM, the meaning of latent classes is specified by how item properties affect item difficulties within each class. To improve…

Modeling multidimensional test data with a unidimensional model can result in serious statistical errors, such as bias in item parameter estimates. Many methods exist for assessing the dimensionality of a test. The current study focused on DIMTEST. Using simulated data, the effects of sample size splitting for use with the ATFIND procedure for…

Spearman's factor-analytic model has been proposed as a unidimensional linear item response theory (IRT) model for continuous item responses. This article first proposes a reexpression of the model that leads to a form similar to that of standard IRT models for binary responses and discusses the item indices of difficulty discrimination and…

This study linked nonlinear profile analysis (NPA) of dichotomous responses with an existing family of item response theory models and generalized latent variable models (GLVM). The NPA method offers several benefits over previous internal profile analysis methods: (a) NPA is estimated with maximum likelihood in a GLVM framework rather than…