Racial and economic equity gaps persist in access to college, degree attainment, and employment outcomes despite attempts to close them over multiple decades, and systemic barriers make it more difficult for BIPOC [Black, Indigenous, People of Color] students and students from low-income backgrounds to not only complete their degree but receive…

Students using self-directed learning platforms, such as Duolingo, cannot be adequately assessed relying solely on responses to standard learning exercises due to a lack of control over learners' choices in how to utilize the platform: for example, how learners choose to sequence their studying and how much they choose to revisit old material. To…

Over the years, researchers have studied novice programming behaviors when doing assignments and projects to identify struggling students. Much of these efforts focused on using student programming and interaction features to predict student success at a course level. While these methods are effective at early detection of struggling students in…

This book examines the idea of educational accountability in higher education, which has become a new secular gospel. But do accountability policies actually make colleges better? What if educational accountability tools don't actually measure what they're supposed to? What if accountability data isn't valid, or worse, what if it's meaningless?…

Data collection of IEP goals is an ongoing problem in special education (Blackwell & Rossetti, 2014; Codding, Skorron, & Pace, 2005, Sandall, Schwartz, & LaCroix, Ruble, McGrew, Wong, & Missall, 2018; Walton, 1985). Research shows that there are inconsistencies between belief and practice. Many educators acknowledge the importance…

Monte Carlo methods are an accepted methodology in regards to generation critical values for a Maximum test. The same methods are also applicable to the evaluation of the robustness of the new created test. A table of critical values was created, and the robustness of the new maximum test was evaluated for five different distributions. Robustness…

The main purpose of this study was to compare delay discounting of hypothetical monetary outcomes by adolescents adjudicated of illegal behavior to that of college students in order to lay a foundation for future discounting work with adjudicated adolescents. It is important to note that we conducted this work during the COVID-19 pandemic, which…

Seminaries in the United States have for more than two centuries sought to equip ministerial leaders for service within the community of faith. And yet these institutions have traditionally been the focus of very little quantitative research. This lack of data is particularly noteworthy given the existential crises many seminaries currently face,…

The purpose of this quantitative causal-comparative study was to determine the extent of differences in student achievement scores on the ACT based on enrollment in preparation courses in large group settings, for students graduating from 2011 to 2020 at a private high school in the southwestern United States. Bandura's Social Cognitive Theory…

K-12 students are expected to acquire competence in data display as part of developing statistical literacy. To support research, assessment design, and instruction, we developed a hypothesized learning progression (LP) using existing empirical literature in the fields of mathematics and statistics education. The data display LP posits a…

Authentic, "messy data" contain variability that comes from many sources, such as natural variation in nature, chance occurrences during research, and human error. It is this messiness that both deters potential users of authentic data and gives data the power to create unique learning opportunities that reveal the nature of science…

This paper identifies a nascent trend in several countries regarding increased collection, public availability and use of destination data for graduates of secondary education, with policy ambitions to support pupil-level decision-making and drive provider-level accountability. This trend mirrors the previous development of such data for higher…

Obtaining relevant data and conveying limitations of the results are two integral components to a successful statistical analysis. It is difficult for students to internalize a deep understanding of these components using only curated, textbook-style examples. Through hands-on data collection, this activity provides a channel for students to…

As big data and artificial intelligence become integral to business decision-making, business management students require proficiency in data science and big data. However, the use of instructional technologies, such as augmented reality (AR) and mind mapping to teach these subjects is limited. This study introduces an innovative pedagogical model…

Digital learning platforms (DLPs) can transform educational research by serving as infrastructure that bridges the gap between practice and research. This white paper examines the progress of DLPs in SEERNet, a multi-year initiative funded by the Institute of Education Sciences (IES), which aims to advance research infrastructure. Through…