Thurstonian forced-choice modeling is considered to be a powerful new tool to estimate item and person parameters while simultaneously testing the model fit. This assessment approach is associated with the aim of reducing faking and other response tendencies that plague traditional self-report trait assessments. As a result of major recent…

Diagnostic classification models (DCMs) are psychometric models that can be used to estimate the presence or absence of psychological traits, or proficiency on fine-grained skills. Critical to the use of any psychometric model in practice, including DCMs, is an evaluation of model fit. Traditionally, DCMs have been estimated with maximum…

Binary item response theory (IRT) models are widely used in educational testing data. These models are not perfect because they simplify the individual item responding process, ignore the differences among different response patterns, cannot handle multidimensionality that lay behind options within a single item, and cannot manage missing response…

Automated scoring of student responses to open-ended questions, including short-answer questions, has great potential to scale to a large number of responses. Recent approaches for automated scoring rely on supervised learning, i.e., training classifiers or fine-tuning language models on a small number of responses with human-provided score…

In this research, we explore how coworker ideation levels or, more specifically, the average ideation levels of coworkers within a workgroup affect a focal employee's ideation. We examine an underlying mechanism and a boundary condition of this influence process. Drawing on social cognitive theory, we argue that high coworker ideation levels are…

In Automated Essay Scoring (AES) systems, many previous works have studied group fairness using the demographic features of essay writers. However, individual fairness also plays an important role in fair evaluation and has not been yet explored. Initialized by Dwork et al., the fundamental concept of individual fairness is "similar people…

This study explores using transfer learning in machine learning for natural language processing (NLP) to create generic automated essay scoring (AES) models, providing instant online scoring for statewide writing assessments in K-12 education. The goal is to develop an instant online scorer that is generalizable to any prompt, addressing the…

In this study, we validated the "ReadFree tool", a computerised battery of 12 visual and auditory tasks developed to identify poor readers also in minority-language children (MLC). We tested the task-specific discriminant power on 142 Italian-monolingual participants (8-13 years old) divided into monolingual poor readers (N = 37) and…

When comparing social science phenomena through a time perspective, absolute and relative difference (RD) are the two typical presentation formats used to communicate interpretations to the audience, while time distance (TD) is the least frequently used of such formats. This article argues that the chosen presentation format is extremely important…

Performance in elementary cognitive tasks is moderately correlated with fluid intelligence and working memory capacity. These correlations are higher for more complex tasks, presumably due to increased demands on working memory capacity. In accordance with the binding hypothesis, which states that working memory capacity reflects the limit of a…

There is a wealth of evidence that people's reasoning is influenced by explanatory considerations. Little is known, however, about the exact form this influence takes, for instance about whether the influence is unsystematic or because of people's following some rule. Three experiments investigate the descriptive adequacy of a precise proposal to…

Learning at home not only provides written assignments that are changed in electronic form but must also reflect student learning outcomes at home. Likewise, researchers use literary reading to avoid students getting bored with learning Indonesian language literacy and character education. However, improving literacy skills is not just reading…

Automatic machine learning (AutoML) methods automate the time-consuming, feature-engineering process so that researchers produce accurate student models more quickly and easily. In this paper, we compare two AutoML feature engineering methods in the context of the National Assessment of Educational Progress (NAEP) data mining competition. The…

International large-scale assessments (ILSAs) transitioned from paper-based assessments to computer-based assessments (CBAs) facilitating the use of new item types and more effective data collection tools. This allows implementation of more complex test designs and to collect process and response time (RT) data. These new data types can be used to…

This note is concerned with examining the relationship between within-group and between-group variances in two-level nested designs. A latent variable modeling approach is outlined that permits point and interval estimation of their ratio and allows their comparison in a multilevel study. The procedure can also be used to test various hypotheses…