Correct specifications of hierarchical attribute structures in analyses using diagnostic classification models (DCMs) are pivotal because misspecifications can lead to biased parameter estimations and inaccurate classification profiles. This research is aimed to demonstrate DCM analyses with various hierarchical attribute structures via Bayesian…

This article proposes a class of cognitive diagnosis models (CDMs) for polytomously scored items with different link functions. Many existing polytomous CDMs can be considered as special cases of the proposed class of polytomous CDMs. Simulation studies were carried out to investigate the feasibility of the proposed CDMs and the performance of…

Complex systems are made up of many entities, whose interactions emerge into distinct collective patterns. Computational modeling platforms can provide a powerful means to investigate emergent phenomena in complex systems. Some research has been carried out in recent years about promoting students' modeling practices, specifically using…

A prior study developed the Computational Thinking Scale (CTS) for assessing individuals' computational thinking dispositions in five dimensions: decomposition, abstraction, algorithmic thinking, evaluation, and generalization. This study proposed the Developmental Model of Computational Thinking through validating the structural relationships…

The Big Data for Education Spoke of the NSF Northeast Big Data Innovation Hub and ETS co-sponsored an educational data mining competition in which contestants were asked to predict efficient time use on the NAEP 8th grade mathematics computer-based assessment, based on the log file of a student's actions on a prior portion of the assessment. In…

This article explains the process behind estimating a National Education Cost Model (NECM) and generating from that model projections of per-pupil costs to achieve 2016 national average outcomes (reading and math grades 3 to 8) across all districts in the United States, from 2019-20 to 2020-21. This article is a follow-up to a preliminary report…

Informal best fit lines frequently appear in school curricula. Previous research collectively illustrates that the adjective informal does not translate to cognitive simplicity. Using existing literature, we create a hypothetical framework of cognitive processes associated with studying informal best fit lines. We refine the framework using data…

As science becomes increasingly computationally intensive, the need for computational thinking (CT) and computer science (CS) practices in K-12 science education is becoming paramount. Incorporation of CT/CS practices in K-12 education can be seen in national standards and a variety of allied initiatives. One way to build capacity around an…

Effect sizes in the Cohen's d family are often used in education to compare estimates across studies, measures, and sample sizes. For example, effect sizes are used to compare gains in achievement students make over time, either in pre- and post-treatment studies or in the absence of intervention, such as when estimating achievement gaps. However,…

Second-order item response theory models have been used for assessments consisting of several domains, such as content areas. We extend the second-order model to a third-order model for assessments that include subdomains nested in domains. Using a graphical model framework, it is shown how the model does not suffer from the curse of…

For the past decade, the accountability model associated with No Child Left Behind (NCLB) emphasized proficiency on end of year tests; with Every Student Succeeds Act (ESSA) the emphasis on proficiency within statewide testing programs, though now integrated with other measures of student learning, nevertheless remains a primary metric for…

In large-scale educational surveys, a latent regression model is used to compensate for the shortage of cognitive information. Conventionally, the covariates in the latent regression model are principal components extracted from background data. This operational method has several important disadvantages, such as the handling of missing data and…

Teacher value-added models (VAMs) must isolate teachers' contributions to student achievement to be valid. Well-known VAMs use different specifications, however, leaving policymakers with little clear guidance for constructing a valid model. We examine the sensitivity of teacher value-added estimates under different models based on whether they…

The School Composition and the Black-White Achievement Gap study was undertaken by the National Center for Education Statistics to present both descriptive and associative information on the relationships among the percentage of students in a school who were Black (referred to as "Black student density" or "density"), the…

Growth curve models with different types of distributions of random effects and of intraindividual measurement errors for robust analysis are compared. After demonstrating the influence of distribution specification on parameter estimation, 3 methods for diagnosing the distributions for both random effects and intraindividual measurement errors…