In June 2019, Minnesota State set a critical goal: By 2030, eliminate the educational equity gaps at each of the 30 colleges and 7 universities that comprise the system. To achieve the goal of Equity 2030, and empower actors at every level of Minnesota State, system and campus leaders need to fully embrace data democratization. Without access to…

While many campuses have access to and publish equity-focused data, it can be difficult to share that data with the campus community in a way that engages multiple offices. This article outlines the Equity Liaison Initiative at the University of Wisconsin--La Crosse, which engages individuals from most offices on campus with equity-focused data to…

The increasing volume of information and the intense pace of its circulation are changing the ways universities access, use, analyze, and provide data. Many have championed the use of large-scale databases to track student admissions and retention, faculty productivity, student wellness, and other phenomena that shape our understandings of higher…

Evidence-based decision-making requires access to good and reliable data. In recent years, there has been a tremendous increase of data available to institutions, from internal as well as external sources. With this increase in data and its analytics, new challenges and questions arise. One of the most pertinent of which is the ethics and best…

Over the past 20 years, many colleges and universities have made significant progress in building data warehouses and implementing business intelligence tools to provide better access to administrative data that were previously locked away in enterprise systems. However, the data architectures from the 1990s and 2000s are aging as new technologies…

Multilevel modeling (MLM) gives researchers the ability to make inferences about organizations where nesting factors will bias results and the assumption of independence is not tenable. This article provides an overview of the variety of data sources that lend themselves to conducting institutional research (IR). It not only serves as a repository…

Intercollegiate athletics is no longer an area of interest solely for coaches and athletic administrators; increasingly, this field has captured the curiosity of faculty, researchers, and the general public. Such attention has the potential to greatly affect the course the field of intercollegiate athletics takes in the years to come.…

Most institutional research (IR) practitioners lack access to direct measures of longitudinal student learning, let alone assessment instruments systematically embedded into the curriculum that yield representative cognitive gain data controlling for student motivation. Typically, measures of student learning growth rest on findings from survey…

Academic leaders and governing boards are increasingly aware of the importance and difficulty in managing physical plants as finite resources. In addition, the finances needed to renovate or build facilities have become severely constrained. The National Science Foundation (2000), in its survey of research facilities, suggests that research space…

Benefits and potential problems with formal college and university programs of Interinstitutional data sharing are examined from an institutional perspective and the perspective of the institutional researcher. Benefits include access to data, networking and consulting, efficiency, increased researcher visibility, and better understanding of…

The costs to colleges and universities of establishing a data-sharing exchange are examined, and it is argued that in most cases, the financial costs are minimal when compared to the potential opportunity cost of making decisions without access to good comparative information. (Author/MSE)

Before joining a data-sharing consortium, colleges and universities must address issues regarding goals and expectations, including why comparative data are needed, information types needed, needed comparisons, selection of institutions for comparison, data accessibility, time requirements, costs, and need for technical expertise. (MSE)