While there are many different types of education data, policymakers and education leaders often place heavy emphasis on data from large-scale quantitative measures, such as annual state assessments. But data from these sources alone do not provide a complete picture of learning and are often not well suited to informing improvements at the local…

This contribution deals with effect measures for covariates in ordinal data models to address the interpretation of the results on the extreme categories of the scales, evaluate possible response styles, and motivate collapsing of extreme categories. It provides a simpler interpretation of the influence of the covariates on the probability of the…

Measurement-based care (MBC) research and practice, including clinical workflows and systems to support MBC, are grounded in adult-serving mental health systems. MBC research evidence is building in child and adolescent services, but MBC practice is inherently more complex due to identified client age, the family system and the need to involve…

Multilevel factor mixture modeling (FMM) is a hybrid of multilevel confirmatory factor analysis (CFA) and multilevel latent class analysis (LCA). It allows researchers to examine population heterogeneity at the within level, between level, or both levels. This tutorial focuses on explicating the model specification of multilevel FMM that considers…

In today's educational landscape, state and local educational agencies (SEAs and LEAs) often experience challenges connecting large-scale accountability data with actual school improvement initiatives. These challenges tend to be rooted in incoherent design and use of data systems for continuous improvement. As we aim to support SEAs in…

With the availability of educational digital data acquisition systems, it has also become possible in physics education to generate 'big' data sets by (a) measuring multiple variables simultaneously, (b) increasing the sample rate, (c) extending the measurement duration, or (d) choosing a combination among these three options. In the context of…

Across all sciences, the quality of measurements is important. Survey measurements are only appropriate for use when researchers have validity evidence within their particular context. Yet, this step is frequently skipped or is not reported in educational research. This article briefly reviews the aspects of validity that researchers should…

In both general chemistry and analytical chemistry courses, students are introduced to the concept of predominant species in solution when discussing acid/base chemistry. Speciation diagrams are often used to illustrate the concept and predict the relative abundance of species in solution. Herein, we describe a laboratory experiment for an…

SEERNet digital learning platforms (DLPs) are developing new infrastructure to support research in authentic contexts where student learning is happening. In order to contextualize this work within the larger field, we trace historical precedents along four main categories: data repositories, data collection services, research design interfaces,…

In a 1993 book review, E. Pearlstein asks, "Why don't textbook authors begin their discussion of magnetism by talking about magnets? That's what students have experience with." A similar question can be asked, "Why don't professors have students measure the force between permanent magnets in introductory physics labs?" The…

In this new Policy Note, Rachel Hewitt, HEPI's Director of Policy and Advocacy, highlights the need to distinguish between mental health and well-being and calls for more comprehensive data to be made available on the well-being of all those work and study at universities. Key points: (1) The conflation of mental health and well-being is not…

This chapter identifies some of the challenges surrounding data collection and analysis regarding development students, including testing and identifying academic needs, placement determination, and measuring student outcomes.

In this ITEMS module, we provide a didactic overview of the specification, estimation, evaluation, and interpretation steps for diagnostic measurement/classification models (DCMs), which are a promising psychometric modeling approach. These models can provide detailed skill- or attribute-specific feedback to respondents along multiple latent…

Sample representativeness is an important piece to consider when evaluating the quality of a screening assessment. If you are trying to determine whether or not the screening tool accurately measures children's skills, you want to ensure that the sample that is used to validate the tool is representative of your population of interest.

This article provides an overview of the R package lsasim, designed to facilitate the generation of data that mimics a large scale assessment context. The package features functions for simulating achievement data according to a number of common IRT models with known parameters. A clear advantage of lsasim over other simulation software is that…