This article is concerned with a subset of numerically stable and scalable algorithms useful to support computationally complex psychometric models in the era of machine learning and massive data. The subset selected here is a core set of numerical methods that should be familiar to computational psychometricians and considers whitening transforms…

This study shows that residual variation can cause problems related to scaling in exponential random graph models (ERGM). Residual variation is likely to exist when there are unmeasured variables in a model--even those uncorrelated with other predictors--or when the logistic form of the model is inappropriate. As a consequence, coefficients cannot…

Value-added assessment methods have been criticized by researchers and policy makers for a number of reasons. One issue includes the sensitivity of model results across different outcome measures. This study examined the utility of incorporating multivariate latent variable approaches within a traditional value-added framework. We evaluated the…

In this paper we present a series of item response models of data collected using the Force Concept Inventory. The Force Concept Inventory (FCI) was designed to poll the Newtonian conception of force viewed as a multidimensional concept, that is, as a complex of distinguishable conceptual dimensions. Several previous studies have developed…

The combination of different item formats is found quite often in large scale assessments, and analyses on the dimensionality often indicate multi-dimensionality of tests regarding the task format. In ICILS 2013, three different item types (information-based response tasks, simulation tasks, and authoring tasks) were used to measure computer and…

An automated item selection procedure in Mokken scale analysis partitions a set of items into one or more Mokken scales, if the data allow. Two algorithms are available that pursue the same goal of selecting Mokken scales of maximum length: Mokken's original automated item selection procedure (AISP) and a genetic algorithm (GA). Minimum…

Complexity thinking is relatively new to education research and has rarely been used to examine complex issues in physics and engineering education. Issues in higher education such as student retention have been approached from a multiplicity of perspectives and are recognized as complex. The complex system of student retention modelling in higher…

There are two primary challenges for instructors in offering a high-quality course at large scale. The first is scaling educational experiences to such a large audience. The second major challenge encountered is that of enabling adaptivity of the educational experience. This thesis addresses both major challenges in the way of high-quality…

Educational interventions are often evaluated and compared on the basis of their impacts on test scores. Decades of research have produced two empirical regularities: interventions in later grades tend to have smaller effects than the same interventions in earlier grades, and the test score impacts of early educational interventions almost…

G. T. Fechner (1860/1966) famously described two kinds of psychophysics: "Outer psychophysics" captures the black box relationship between sensory inputs and perceptual magnitudes, whereas "inner psychophysics" contains the neural transformations that Fechner's outer psychophysics elided. The relationship between the two has never been clear.…

The aim of the research presented here is the use of extensions of longitudinal item response theory (IRT) models in the analysis and comparison of group-specific growth in large-scale assessments of educational outcomes. A general discrete latent variable model was used to specify and compare two types of multidimensional item-response-theory…

Limited studies have investigated the latent autistic traits in the mainland Chinese population for autism spectrum conditions (ASC). This study explored the psychometric properties of a Mandarin Chinese version of the CAST in a sample consisting of 737 children in mainstream schools and 50 autistic cases. A combination of categorical data factor…

When Item Response Theory (IRT) is operationally applied for large scale assessments, unidimensionality is typically assumed. This assumption requires that the test measures a single latent trait. Furthermore, when tests are vertically scaled using IRT, the assumption of unidimensionality would require that the battery of tests across grades…

Over the past decade, educational policy trends have shifted to a focus on examining students' growth from kindergarten through twelfth grade (K-12). One way states can track students' growth is with a vertical scale. Presently, every state that uses a vertical scale bases the scale on a unidimensional IRT model. These models make a…