The legal and ethical use of Big Data and Learning Analytics in academic libraries has been widely debated. Analyzing large data sets has tremendous potential for libraries to implement changes that help students and prove the library's value to the university. The librarian's role in safeguarding patron privacy in a university setting where…

The authors developed a teaching project for students to debate data and workplace privacy dilemmas, formulate plans of action for the use of certain data about workers and job applicants, and apply the law to reach and defend their solutions. The purpose of this versatile exercise is to sensitize both undergraduate and graduate business students…

This data file documentation accompanies new data files for the High School Longitudinal Study of 2009 (HSLS:09) Postsecondary Education Transcript Study and Student Financial Aid Records Collection (PETS-SR). HSLS:09 follows a nationally representative sample of students who were ninth-graders in fall 2009 from high school into postsecondary…

Predicting student success in a data science degree program is a challenging task due to the interdisciplinary nature of the field, the diverse backgrounds of the students, and an incomplete understanding of the precise skills that are most critical to success. In this study, the applicant's future academic performance in a Master of Data Science…

School closures in response to the COVID-19 pandemic have dramatically changed the conditions in which students learn and experience schooling. Disparities in students' access to learning and in their academic outcomes are likely to exacerbate longstanding challenges and inequities. Now more than ever, educators need information that will help…

Building a culture of data governance at a higher education institution involves collaboration across the entire institution. Before the creation of formalized roles to perform data management and data governance functions at colleges and universities, these functions were performed by traditional institutional research personnel. Documentation…

This paper characterizes the ways in which increased attention to response process data has implications for psychometrics. To do so, this work draws on two organizing frameworks that have heretofore not been associated: evidence-centered design, and the distinction between greater and lesser statistics. Overlaying these frameworks leads to a…

Thanks to COVID-19, schools were closed and tests were canceled. The result is that we may not see test-taking data typically seen before. For some analyses, sample sizes may not meet the minimum requirement. For others, the sample of test-takers may be different from previous years. In some situation, there may be no data at all. What do we do in…

In this essay review, we first historicize how the OECD (Organization for Economic Co-operation and Development) rose to be a global education policy actor and authority from a historical, comparative, and international perspective. Subsequently, we sketch out the global educational governing mechanisms developed by the OECD, which include but are…

Onwuegbuzie and Hitchcock (2015) provided an initial framework for conceptualizing and conducting advanced-level mixed analysis approaches. In the present article, we build on these efforts by altering the framework to focus on crossover analyses, which might help analysts see the various component steps that can go into crossover analyses and…

Changing criterion designs (CCD) are single-case experimental designs that entail a step-by-step approximation of the final level desired for a target behavior. Following a recent review on the desirable methodological features of CCDs, the current text focuses on an analytical challenge: the definition of an objective rule for assessing the…

Teaching students to reason with data is not a totally new enterprise. A small but insistent statistics education community has been studying the process for decades. This commentary provides an introduction to some major themes of that research, in order to provide common ground for conversations between learning sciences researchers and those…

Classroom observation data using tools such as the Classroom Observation Protocol for Undergraduate STEM (COPUS) are frequently collected in instructional settings for large-scale research studies and program assessment. While COPUS data may be provided to instructors, it is often provided with little or no guidance on how the data can be used to…

Program "profiles" are one-page summaries that highlight the components of each teacher retention strategy or program. Similar to a logic model, program profiles make it easy to understand what components define the program; the direct results of the program component(s); and what the program is collecting, documenting, or measuring to…

Supervised machine learning has become one of the most important methods for developing educational and intelligent tutoring software; it is the backbone of many educational data mining methods for estimating knowledge, emotion, and other aspects of learning. Hence, in order to ensure optimal utilization of computing resources and effective…