Context: Prolonged disconnection from school and work represents major setbacks during the transition to adulthood and is a distinct feature of the developmental trajectories of many disadvantaged youths, especially those from a marginalized racial background (Hong and Chung 2022; Shanahan 2000). Differential schooling experiences are hypothesized…

The current research used the Proficient Academic Reader (PAR) framework to explore whether reading strategies, task awareness, and motivation predicted college students' literacy skills over and above foundational skills (e.g., decoding, vocabulary). Specifically, the current research investigated the unique contribution of the PAR constructs to…

As part of the effort to develop an improved oral reading fluency (ORF) assessment system, Kara et al. (2020) estimated the ORF scores based on a latent variable psychometric model of accuracy and speed for ORF data via a fully Bayesian approach. This study further investigates likelihood-based estimators for the model-derived ORF scores,…

The purpose of this qualitative descriptive study was to explore how educational leaders in the Northeast region of the United States describe the influence of their childhood experiences and attachment styles on their current leadership behaviors. Bowlby's attachment theory provided the theoretical framework for the study which aimed to address…

As part of the effort to develop an improved oral reading fluency (ORF) assessment system, Kara et al. estimated the ORF scores based on a latent variable psychometric model of accuracy and speed for ORF data via a fully Bayesian approach. This study further investigates likelihood-based estimators for the model-derived ORF scores, including…

To enable all who participate in educational settings to leverage AI tools for powerful learning, this paper describes a framework and strategies for educational leaders to design and implement a clear approach to AI literacy for their specific audiences (e.g. learners, teachers, or others) that are safe and effective. The first part of the paper…

This report shares the learnings across 28 exploratory projects from teams across K-12 school districts, nonprofits, and nonprofit and for-profit edtech companies, leveraging AI to support numerous goals across K-12 educational settings. Through this report, we aim to highlight the early successes of AI, surface the key barriers that call for…

Increasingly, people are looking for education and training options that are more affordable, flexible, can quickly open doors to good jobs, and--ideally--pave the way for further educational attainment. Businesses also want to hire workers with the skills needed for jobs in growing industries. Non-degree credentials (NDCs) can often meet these…

Quasi-experimental methods are a cornerstone of applied social science, providing critical answers to causal questions that inform policy and practice. Although open science principles have influenced experimental research norms across the social sciences, these practices are rarely implemented in quasi-experimental research. In this paper, we…

Growing literature documents the promise of active learning instruction in engaging students in college classrooms. Accordingly, faculty professional development (PD) programs on active learning have become increasingly popular in postsecondary institutions; yet, quantitative evidence on the effectiveness of these programs is limited. Using…

Academic and practitioner interest in data science has increased considerably. Yet scholarly understanding of what motivates students to learn data science is still limited. Drawing on the theory of planned behavior, we propose a research model to examine the determinants of behavioral intentions to learn data science. In the proposed research…

Qualitative Comparative Analysis (QCA) is a relatively young method of causal inference that continues to diffuse across the social sciences. However, recent methodological research has found the conservative (QCA-CS) and the intermediate solution type (QCA-IS) of QCA to fail fundamental tests of correctness. Even under conditions otherwise ideal…

Multilevel structural equation modeling (MSEM) allows researchers to model latent factor structures at multiple levels simultaneously by decomposing within- and between-group variation. Yet the extent to which the sampling ratio (i.e., proportion of cases sampled from each group) influences the results of MSEM models remains unknown. This article…

We propose a cognitive-psychological model of linguistic intuitions about copredication statements. In copredication statements, like "The book is heavy and informative," the nominal denotes two ontologically distinct entities at the same time. This has been considered a problem for standard truth-conditional semantics. In this paper, we…

Future teachers face the challenge of whether and how to address their students' misconceptions--naïve concepts that often conflict with the correct scientific concepts taught at school. We developed a short-term digital training intervention on instructional knowledge about strategies for addressing students' misconceptions in physics. It…