We are interested in how codified knowledge is produced around the globe (which inputs are used to produce scientific articles and patented inventions) and the efficiency of the process (how do the best performers produce more with the same inputs or produce the same with less inputs). Using a Data Envelopment Analysis (DEA) efficiency frontier…

Research on the use of modeling and mapping tools in curriculum management is thriving, often focusing on the perspectives of the faculty alone. However, scholarly works that also incorporate the students' curriculum concerns are rare. A recurring theme in students' curriculum concerns is the perceived overlap among courses, usually expressed at…

Qualitative data analysis has been criticised for a lack of credibility over recent years when vagueness has been afforded to the reporting of how findings are attained. In response, there has been a growing body of literature emphasising a need to detail methods of qualitative data analysis. This paper adds to this body of knowledge by presenting…

The contemporary Human activity utilizes huge volumes of digital data to solve efficiently multiple socio-economic, scientific and technical problems. Now the big data analysis is mainly oriented to the socioeconomic sphere with a goal to lift the profit. The science and technology to penetrate deeper in the nature of objects and systems under…

We provide a computational exercise suitable for early introduction in an undergraduate statistics or data science course that allows students to "play the whole game" of data science: performing both data collection and data analysis. While many teaching resources exist for data analysis, such resources are not as abundant for data…

The shortage of qualified administrators who can utilize data analytics means that institutions are not able to harness data analytics to its fullest potential in order to remain competitive in a higher education market that continued to reward institutions that embrace entrepreneurship. Examining how new student affairs professionals in US higher…

Leveraging big data for student data analytics is increasingly integrated throughout university operations from admissions to advising to teaching and learning. Though the possibilities are exciting to consider, they are not without risks to student autonomy, privacy, equity, and educational value. There has been little research showing how…

The purpose of the study is to analyze disaggregate rural public teacher retention data to determine significant differences in retention by race, gender, and educational attainment. Missouri public schools in Northwest Missouri, who are considered rural through the years 2019-2021 were included in this study. ANOVA test results were analyzed to…

Using data to inform decision-making in the educational environment has increased over the last decade due to accountability requirements at the federal, state, and local level (Bernhardt, 2013; Datnow & Hubbard, 2016; Garland, 2014; Mandinach & Gummer, 2016; McKay, 2018; Wayman, 2005). While research supported the inclusion of data in…

Background: As the body of scientific evidence about what works in education grows, so does the need to effectively communicate that evidence to policy-makers and practitioners. Websites and clearinghouses such as the "What Works Clearinghouse" (WWC), "Evidence for ESSA," "Blueprints for Healthy Youth Development,"…

We examine the impact of wind energy installation on school district finances and student achievement using data on the timing, location, and capacity of the universe of U.S. installations from 1995 through 2017. Wind energy installation substantially increased district revenues, causing large increases in capital outlays, but only modest…

Meta-analysis and structural equation modeling (SEM) are 2 of the most prominent statistical techniques employed in the behavioral, medical, and social sciences. They each have their own well-established research communities, terminologies, statistical models, software packages, and journals ("Research Synthesis Methods" and…

In order to demonstrate the value of higher education and evaluate the effectiveness of various policies and practices, researchers are increasingly expected to merge data from the Integrated Postsecondary Education Data System (IPEDS) with a range of other federal and private-sector data sources. In this article, I detail a number of the most…

In this ITEMS module, we provide a didactic overview of the specification, estimation, evaluation, and interpretation steps for diagnostic measurement/classification models (DCMs), which are a promising psychometric modeling approach. These models can provide detailed skill- or attribute-specific feedback to respondents along multiple latent…

When practitioners use modern measurement models to evaluate rating quality, they commonly examine rater fit statistics that summarize how well each rater's ratings fit the expectations of the measurement model. Essentially, this approach involves examining the unexpected ratings that each misfitting rater assigned (i.e., carrying out analyses of…