Teachers play a crucial role in supporting students' learning. It is crucial to also support teachers in their teaching. Traditional means to support teachers are highly effective but also repetitive, not personalized or not scalable, and infrequent. As classrooms become instrumented with educational technologies, opportunities emerge to provide…

In this article we present and discuss the importance and relevance of the inclusion of spatial data analysis as part of the undergraduate statistics curriculum. Given its usefulness and applicability across a range of disciplines, spatial data are a topic that should receive more emphasis within undergraduate statistics curricula. There exist…

Data science is collaborative and its students should learn teamwork and collaboration. Yet it can be a challenge to fit the teaching of such skills into the data science curriculum. Team-Based Learning (TBL) is a pedagogical strategy that can help educators teach data science better by flipping the classroom to employ small-group collaborative…

The Early Childhood Data Use Assessment Tool is designed to identify and improve data use skills among early childhood education (ECE) program staff so that they can better use data to inform, plan, monitor, and make decisions for instruction and program improvement. Data use is critical in quality ECE programs but can be intimidating for some ECE…

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…

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…

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…