This study used longitudinal data from a sample of 467 preschoolers to examine (1) if children’s executive function (EF) skills at the beginning of pre-K predict growth in their mathematics achievement across the pre-K year, (2) whether growth in learning behaviors, specifically task orientation, mediate the associations between EF and mathematics achievement, and (3) if there are sex differences in these associations.

This study evaluates the effects of asking items throughout the passage (i.e., embedding items) to achieve a more precise measure of reading comprehension by removing barriers for students to demonstrate their understanding. Results showed a significant impact of embedding comprehension items within reading passages on the measurement of student achievement in comparison to answering items at the end of the passage.

This study investigated teacher adaptation to the changes in teaching conditions caused by the transition to distance learning in the COVID-19 pandemic.

This study compares estimation of symptom networks with Bayesian GLASSO- and Horseshoe priors to estimation using the frequentist GLASSO using extensive simulations.

The COVID-19 pandemic, coupled with political and social unrest, has deeply disrupted the lives and learning experiences of most students. It has created an urgent need to address long-standing opportunity gaps and has highlighted the importance of providing resources that support student achievement, social-emotional learning, and physical and mental well-being. This urgency for action to address the impacts is valid, but it has also created a noisy environment of potential options of what might be best for students. It’s critical, now more than ever, for decisions to be grounded in solid research.

This research introduces a novel approach, using the Bayes factor, wherein a researcher can directly test for homogeneous within-person variance in hierarchical models. Additionally, we introduce a membership model that allows for classifying which (and how many) individuals belong to the common variance model.

How can we support academic growth for students with disabilities (SWD) who may have experienced disproportionate academic impacts from COVID-19?