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…

This observational study used data from 270 second-grade students to investigate the association between students' strategy use for multidigit addition and subtraction and their mathematics achievement. Based on strategies they used during a mathematics interview, students were classified into the following strategy groups: (a) standard algorithm,…

While hierarchical machine learning approaches have been used to classify texts into different content areas, this approach has, to our knowledge, not been used in the automated assessment of text difficulty. This study compared the accuracy of four classification machine learning approaches (flat, one-vs-one, one-vs-all, and hierarchical) using…

In everyday communication, not only do speakers describe, but they also depict. When depicting, speakers can take on the role of other people and quote their speech or imitate their actions. In previous work, we developed a paradigm to elicit depictions in speakers. Here we apply this paradigm to signers to explore depiction in the manual…

This study examined how machine learning and natural language processing (NLP) techniques can be leveraged to assess the interpretive behavior that is required for successful literary text comprehension. We compared the accuracy of seven different machine learning classification algorithms in predicting human ratings of student essays about…

Dialogism provides the grounds for building a comprehensive model of discourse and it is focused on the multiplicity of perspectives (i.e., voices). Dialogism can be present in any type of text, while voices become themes or recurrent topics emerging from the discourse. In this study, we examine the extent that differences between…

Large-scale assessments are supported by a large item pool. An important task in test development is to assign items into scales that measure different characteristics of individuals, and a popular approach is cluster analysis of items. Classical methods in cluster analysis, such as the hierarchical clustering, K-means method, and latent-class…

Background: Children with attention-deficit/hyperactivity disorder (ADHD) experience greater sleep problems than their peers. Although adolescence is generally a developmental period characterized by insufficient sleep, few studies have used a multi-informant, multi-method design, to examine whether sleep differs in adolescents with and without…

We present a machine learning model that uses particular attributes of individual questions asked by teachers and students to predict two properties of classroom discourse that have previously been linked to improved student achievement. These properties, uptake and authenticity, have previously been studied by using trained observers to live-code…

This study compares Spanish morphosyntax error types and magnitude in monolingual Spanish and Spanish-English bilingual children with typical language development (TD) and language impairment (LI). Performance across groups was compared using cloze tasks that targeted articles, clitics, subjunctives, and derivational morphemes in 57 children.…

The article describes an application of the Organizational Climate Descriptive Questionnaire (OCDQ) in the author's dissertation. He explored the possible relationships among [Fred] Fiedler's assessment of psychological distance of the leader (the principal) and the organizational climate of schools as assessed by the then recently developed OCDQ…