This study proposes a Bayesian method for diagnostic classification models (DCMs) for a partially known Q-matrix setting between exploratory and confirmatory DCMs. This Q-matrix setting is practical and useful because test experts have pre-knowledge of the Q-matrix but cannot readily specify it completely. The proposed method employs priors for…

Previous studies have demonstrated evidence of latent skill continuity even in tests intentionally designed for measurement of binary skills. In addition, the assumption of binary skills when continuity is present has been shown to potentially create a lack of invariance in item and latent ability parameters that may undermine applications. In…

Eye tracking research technologies are often used to study how individuals attend visually to different types of AAC displays (e.g. visual scene displays, grid displays). The assumption is that efficiency of visual search may relate to efficiency of motor selection necessary for communication via aided AAC; however, this assumption has not…

Although item response models have grown in popularity in many areas of educational and psychological assessment, there are relatively few applications of these models in experimental psychopathology. In this article, we explore the use of item response models in the context of a computerized cognitive task designed to assess visual working memory…

Autistic people experience social communication difficulties alongside specific memory difficulties than impact their ability to recall episodic events. Police interviewing techniques do not take account of these differences, and so are often ineffective. Here we introduce a novel Witness-Aimed First Account interview technique, designed to better…

In confirmatory factor analysis quite similar models of measurement serve the detection of the difficulty factor and the factor due to the item-position effect. The item-position effect refers to the increasing dependency among the responses to successively presented items of a test whereas the difficulty factor is ascribed to the wide range of…

The item-position effect describes how an item's position within a test, that is, the number of previous completed items, affects the response to this item. Previously, this effect was represented by constraints reflecting simple courses, for example, a linear increase. Due to the inflexibility of these representations our aim was to examine…

Understanding and characterizing treatment effect variation in randomized experiments has become essential for going beyond the "black box" of the average treatment effect. Nonetheless, traditional statistical approaches often ignore or assume away such variation. In the context of randomized experiments, this paper proposes a framework…

The present study employed data simulation techniques to investigate the 1-year stability of alternative classification schemes for identifying children with reading disabilities. Classification schemes investigated include low performance, unexpected low performance, dual-discrepancy, and a rudimentary form of constellation model of reading…

The purpose of this study was to examine the use of an emerging technology called augmented reality to teach science vocabulary words to college students with intellectual disability and autism spectrum disorders. One student with autism and three students with an intellectual disability participated in a multiple probe across behaviors (i.e.,…

An application of a hierarchical IRT model for items in families generated through the application of different combinations of design rules is discussed. Within the families, the items are assumed to differ only in surface features. The parameters of the model are estimated in a Bayesian framework, using a data-augmented Gibbs sampler. An obvious…

In administration of individually administered intelligence tests, items are commonly presented in a sequence of increasing difficulty, and test administration is terminated after a predetermined number of incorrect answers. This practice produces stochastically censored data, a form of nonignorable missing data. By manipulating four factors…

Individuals scoring high in fluid intelligence tasks generally perform very efficiently in problem solving tasks and analogical reasoning tasks presumably because they are able to select the task-relevant information very quickly and focus on a limited set of task-relevant cognitive operations. Moreover, individuals with high fluid intelligence…

These proceedings contain the papers of the 11th International Conference on Cognition and Exploratory Learning in the Digital Age (CELDA 2014), October 25-27, 2014, which has been organized by the International Association for Development of the Information Society (IADIS) and endorsed by the Japanese Society for Information and Systems in…

Gignac [Gignac, G. E. (2006). "Evaluating subtest "g" saturation levels via the single trait-correlated uniqueness (STCU) SEM approach: Evidence in favor of crystallized subtests as the best indicators of "g"." "Intelligence," 34, 29-46.] used a single-trait correlated uniqueness (STCU) CFA approach to…