Cultural Domain in Development and Validation of Tests on Arts to Assess the Skills of Student Graphic Designers

The purpose of the study was to examine whether the presence of items that covered cultural questions in the test оn arts for student graphic designers influenced the fairness of the test across different ethnic and social groups. The reason for the study was to address the gap in the development and validation of tests оn arts that include a cultural domain to assess the skills of undergraduate graphic designers. The research design was based on DIF and DTF methods to examine the factorial structure of test data and to identify whether the factorial structure of the test was the same across ethnic and social groups. A one-factor CFA model was applied to perform measurements for categorised ethnic and social status groups to identify whether the factorial structure was similar or identical for them. The goodness-of-fit measures were calculated using the chi-square statistics, CFI, TLI, and RMSEA to identify how the obtained data is consistent with the hypothesised model. The inclusion of local culture-related questions in the tests оn arts to assess the skills of student graphic designers influences the individuals' latent traits which lead to an increase in DIF values. Though there were detected seven items with the DIF for the whole test, the DTF measurements showed that the DIF effect eliminated each out at test level which is related to the fact the certain ethnic groups performed better in answering some specific test items, while certain status groups performed better in answering some other test items. It is noteworthy that DTF for the Ukrainian art (miscellaneous) section was between 0.07 and 0.14 meaning a moderate DTF effect. However, the DTF variance values for the sections of principles of design and principles of art were lower than 0.07 meaning a small effect. Therefore, it could be concluded that small DTF effects found in both the whole test and each test section separately indicated that DIF effects eliminate each other at the test level.

A Bifactor Model of Trait Trust, Distrust, and Suspicion

We explored competing models using bifactor item response theory (IRT) analyses to determine the relationship between trait measures of trust, distrust, and suspicion. The model with a general factor for all three scales fits the data best. We explored the relationship of the emergent general factor by correlating it with two latent traits: Agreeableness and the Trust facet of Agreeableness. The exploratory findings showed evidence that the general factor from the best-fitting model was practically identical to the Trust facet of Agreeableness. We concluded that trait trust, distrust, and suspicion reside on a continuum represented by the general factor, which is dispositional trust.

The Brief Form of the Test of Gross Motor Development-3 for Individuals with Visual Impairments

Children with visual impairments (VI) tend to struggle with their fundamental motor skills (FMS), and these difficulties often persist across the lifespan, requiring frequent assessment. The Test of Gross Motor Development (TGMD) shows robust psychometric properties for children with VI. The TGMD, which includes 13 skills, is time-consuming to administer and score, warranting the need to explore brief versions. Therefore, the purpose of this study was to explore the psychometric properties of three, six-skill versions of the TGMD-3 with children with VI. Children (n = 302; Boys = 58%, Girls = 42%; Mage = 13.00, SD = 2.50 years) with VI (B1 = 27%, B2 = 20%, B3 = 38%, B4 = 15%) participated in this study. We examined three different models using confirmatory factor analyses on the relationships between the motor skills and latent traits across the models. Scores from all three brief versions had acceptable global fit. Although further research should be conducted, practitioners can adopt a brief version of the TGMD to assess children with VI.

Estimating latent traits from expert surveys: an analysis of sensitivity to data-generating process

Models for converting expert-coded data to estimates of latent concepts assume different data-generating processes (DGPs). In this paper, we simulate ecologically valid data according to different assumptions, and examine the degree to which common methods for aggregating expert-coded data (1) recover true values and (2) construct appropriate coverage intervals. We find that the mean and both hierarchical Aldrich–McKelvey (A–M) scaling and hierarchical item-response theory (IRT) models perform similarly when expert error is low; the hierarchical latent variable models (A-M and IRT) outperform the mean when expert error is high. Hierarchical A–M and IRT models generally perform similarly, although IRT models are often more likely to include true values within their coverage intervals. The median and non-hierarchical latent variable models perform poorly under most assumed DGPs.

Assessing Cognitive Abilities Using the WAIS-IV: An Item Response Theory Approach

Background: The Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV) has been adapted to 28 different cultures and there has been considerable interest in examining its structure through exploratory and confirmatory factor analysis. This study investigates item and scale properties of the Egyptian WAIS-IV using item response theory (IRT) models. Methods: The sample consisted of 250 adults from Egypt. The item-level and subtest statistical properties of the Egyptian WAIS-IV were established using a combination of four dichotomous IRT models and four polytomous IRT models. In addition, factor analysis was performed to investigate the dimensionality of each subtest. Results: Factor analysis indicated the unidimensionality of each subtest. Among IRT models, the two-parameter logistic model provided a good fit for dichotomous subtests, while the graded response model fitted the polytomous data. Most items of the Egyptian WAIS-IV showed high discrimination, and the scale was adequately informative across the levels of latent traits (i.e., cognitive variables). However, each subtest included at least some items with limited ability to distinguish between individuals with differing levels of the cognitive variable being measured. Furthermore, most subtests have items that do not follow the difficulty rank they are ascribed in the WAIS-IV manual. Conclusions: Overall, the results suggest that the Egyptian WAIS-IV offers a highly valid assessment of intellectual abilities, despite the need for some improvements.

RESIDUAL ANALYSIS IN RASCH POISSON COUNTS MODELS

A Rasch Poisson counts (RPC) model is described to identify individual latent traits and facilities of the items of tests that model the error (or success) count in several tasks over time, instead of modeling the correct responses to items in a test as in the dichotomous item response theory (IRT) model. These types of tests can be more informative than traditional tests. To estimate the model parameters, we consider a Bayesian approach using the integrated nested Laplace approximation (INLA). We develop residual analysis to assess model t by introducing randomized quantile residuals for items. The data used to illustrate the method comes from 228 people who took a selective attention test. The test has 20 blocks (items), with a time limit of 15 seconds for each block. The results of the residual analysis of the RPC were promising and indicated that the studied attention data are not well tted by the RPC model.

Standardized Achievement Testing, Aptitude Testing, and Attitude Testing: How Similar or Different are these Concepts in Educational Assessment?

Testing is an inevitable issue in educational and psychological measurement and assessment. Over the years, several tests and testing mechanisms have been developed to assess different latent traits of learners or examinees. Of these testing forms, standardized achievement, aptitude and attitude testing have taken the forefronts in education, psychology, and research. Whereas these concepts are distinct, they, however, play similar roles which have been misconceived by many, especially those without expertise in educational assessment and measurement. The aim of this paper is to compare standardized achievement testing, aptitude testing, and attitude testing, using a narrative literature review approach. The paper provides a synthesis of gathered information that delineates conditions necessary for the utilization of each testing approach.

Latent traits of lung tissue patterns in former smokers derived by dual channel deep learning in computed tomography images

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease and the traditional variables extracted from computed tomography (CT) images may not be sufficient to describe all the topological features of lung tissues in COPD patients. We employed an unsupervised three-dimensional (3D) convolutional autoencoder (CAE)-feature constructor (FC) deep learning network to learn from CT data and derive tissue pattern-clusters jointly. We then applied exploratory factor analysis (EFA) to discover the unobserved latent traits (factors) among pattern-clusters. CT images at total lung capacity (TLC) and residual volume (RV) of 541 former smokers and 59 healthy non-smokers from the cohort of the SubPopulations and Intermediate Outcome Measures in the COPD Study (SPIROMICS) were analyzed. TLC and RV images were registered to calculate the Jacobian (determinant) values for all the voxels in TLC images. 3D Regions of interest (ROIs) with two data channels of CT intensity and Jacobian value were randomly extracted from training images and were fed to the 3D CAE-FC model. 80 pattern-clusters and 7 factors were identified. Factor scores computed for individual subjects were able to predict spirometry-measured pulmonary functions. Two factors which correlated with various emphysema subtypes, parametric response mapping (PRM) metrics, airway variants, and airway tree to lung volume ratio were discriminants of patients across all severity stages. Our findings suggest the potential of developing factor-based surrogate markers for new COPD phenotypes.