Despite a growing focus on access to and use of emergent literacy assessment in early childhood, little is known about early childhood teachers' data practices and their associations with children's emergent literacy skills. A questionnaire was used to confirm and elaborate findings from prior qualitative work (Schachter & Piasta, 2022)…

For decades, states have been investing in statewide longitudinal data systems (SLDSs) that connect individual-level data over time from early childhood, K-12, postsecondary, and workforce. Because of these investments, most states have a powerful tool that could provide people with the information they need to make decisions at key transition…

In today's data-sharing paradigm, personal data has become a valuable resource that intensifies the risk of unauthorized access and data breach. Increased data mining techniques used to analyze big data have posed significant risks to data security and privacy. Consequently, data breaches are a significant threat to individual privacy. Privacy is…

To ensure validity in survey research, it is imperative that we properly educate doctoral students on best practices in data quality procedures. A 14-year analysis of 679 studies in the AIS "Basket of 8" journals noted undercommunication in the most pertinent procedures, consistent across journals and time. Given recent calls for…

At City Academies Neighborhood Middle School, there is a gap in student achievement. Over the course of two years, our lowest performing students did not grow at the rate of their peers. This problem has several consequences, including over classification of students with disabilities and a widening achievement gap. The purpose of my research was…

High-quality, stable child care and early education (CCEE) can have lasting, positive impacts on children. However, the challenges of recruiting, strengthening, and retaining the CCEE workforce are well documented. CCEE educators typically have low levels of formal education and compensation; limited opportunities for education, training, and…

Objective: Several studies have shown that Adult ADHD presents differently in younger and older adults. We sought to assess the difference in care between these two groups using previously identified quality measures (QMs). Methods: Using electronic health record data, we matched a younger group of ADHD patients to an older group. We then assessed…

Children require access to high-quality statistics education to develop the skills to participate in a technological and data-reliant workforce. This study consisted of a five-lesson integrated STEM unit designed to develop the statistical literacy of 62 6th-grade (11-12 years old) emerging bilingual (EB) learners. Learning was situated in the…

Educational curricula in data analysis are increasingly fundamental to statistics, data science, and a wide range of disciplines. The educational literature comparing coding syntaxes for instruction in data analysis recommends utilizing a simple syntax for introductory coursework. However, there is limited prior work to assess the pedagogical…

Transparency is once again a central issue of debate across types of qualitative research. Work on how to conduct qualitative data analysis, on the other hand, walks us through the step-by-step process on how to code and understand the data we've collected. Although there are a few exceptions, less focus is on transparency regarding…

School exclusion reduction in Scotland--and especially in the city of Glasgow--has received substantial media and policy attention in recent years. In London in particular, multiple governmental agencies have explicitly expressed a desire to replicate the exclusion reduction which recently occurred in Glasgow, often citing the connection between…

The use of large-scale assessments (LSAs) in education has grown in the past decade though analysis of LSAs using multilevel models (MLMs) using R has been limited. A reason for its limited use may be due to the complexity of incorporating both plausible values and weighted analyses in the multilevel analyses of LSA data. We provide additional…

This paper scrutinizes the increasing trend of using international large-scale assessment (ILSA) data for causal inferences in educational research, arguing that such inferences are often tenuous. We explore the complexities of causality within ILSAs, highlighting the methodological constraints that challenge the validity of causal claims derived…

Social network research often depends on the willingness of respondents to provide personal information about themselves and alters. Survey design strategies that increase willingness to share this information are necessary for social network research to be feasible, especially when name generators are used for sampling because rosters are…

The synthetic control method (SCM) is a popular approach for estimating the impact of a treatment on a single unit with panel data. Two challenges arise with higher frequency data (e.g., monthly versus yearly): (1) achieving excellent pre-treatment fit is typically more challenging; and (2) overfitting to noise is more likely. Aggregating data…