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…

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…

National College Access Network (NCAN) has heard repeatedly and consistently over the years that one of the best aspects of network membership is the ability to collaborate with and learn from other members. In an effort to further the transfer of ideas, in the summer of 2016 NCAN hosted a series of four Idea Incubators across the country, which…

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…

Commissioned by the Coalition for Networked Information, this report examines the role of research universities in addressing complex societal challenges. It focuses on climate change, which is best characterized as a "wicked" problem. Such problems are difficult to define and lack clear solutions in part because they involve multiple…

The focus of this study was on identifying patterns of student behavior to support data-informed decision-making which would then improve the learning experience and learning outcomes of online English language courses. Learning analytics approach (or more specifically cluster analysis) was used to identify engagement patterns in online learning.…

This paper reports on teachers developing their own data literacy and then acting as data coaches for colleagues in their schools. The 13 teachers from 7 schools in the study analysed standardised data using a data conversation protocol to identify students with significant mathematical misconceptions. They then took data-informed action with…

This book explores the transformative role of artificial intelligence in educational assessment, catering to researchers, educators, administrators, policymakers, and technologists involved in shaping the future of education. It delves into the foundations of AI-assisted assessment, innovative question types and formats, data analysis techniques,…