Whenever I poke around for some institutional statistics or some data tables or sets to help me scope and understand my library research and assessment efforts, I always wonder if I’m missing some hidden gem of campus-related context or information. Over the years, more and more institutional data has been collected and shared, making it easier for library assessment projects to connect to experiences and knowledge on campus.
What is institutional data?
Institutional data are qualitative or quantitative data intentionally collected by the university that help with decision making and organizational direction, as well as with reporting obligations and regulations. With visualization tools, these data can be collected, analyzed, and shared publicly, giving the university community a cohesive presentation of strategies and functions (for example key performance indicators or KPIs).
Why might you use institutional data?
Being aware of the various data collected and reported on can certainly help library staff generate research questions for library practice, but perhaps more importantly, being aware of campus data can facilitate a broader conversation with campus stakeholders about the role of the library and its impact on student success, research, and community engagement. Knowing more about institutional data can aid in conversations with library vendors, too. And finally, institutional data provides context for library-related data, especially during accreditation reviews.
Tapping into institutional data as a library assessment practitioner allows one to connect the impact of decisions in a library context with impacts in other campus environments.
What University of Michigan data sources might be of interest?
Like most institutions of higher education, U-M collects and maintains a repository of essential data elements which help campus members make decisions. Some of those data elements are reflected in the following sources.
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Michigan Almanac: “provides a consolidated source of data and commentary covering all aspects and major activities of the U-M Ann Arbor campus.” Categories of factual data such as admissions, measures of student success, diversity, research transfer. finances, space, etc. The Office of Budget and Planning also provides links to many Common Data Sets, reports that collect campus information for the purpose of improving the accuracy of published college and university guidebooks. The CDS includes standardized elements, presented in ten sections, including Student Life and Academic Offerings and Policies.
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Information Technology Services (ITS) surveys: For several years, U-M surveyed students and instructors about their adoption and use of technology. ITS now uses the EDUCAUSE ECAR survey.
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My Learning Analytics: Sponsored by ITS, My Learning Analytics is a dashboard that “provides students with information about their engagement with course materials and resources, assignments, and grades in a Canvas course.”
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Data areas in Data Warehouse: These data sets are based on subject areas, including Spaces, Payroll, Student Records, and Teaching/Learning.
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Office of Enrollment Data & Research data, in Learning Analytics Data Architecture (LARC): Contains information about “students who have attended the University of Michigan since the mid-1990s.” But the Office of the Registrar has visualizations of enrollment data, too.
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ADVANCE Program: Great interactive dashboards of demographic and descriptive data about U-M faculty. Also, Research & Evaluation data, based on studies related to “campus climate, institutional indicators of diversity, salary equity, and policies & practices.”
There are data stewards across campus, representing units or functional areas, that may also have data available for library research purposes. It’s great to reach out to these local and knowledgeable experts.
Of course there are other national sources of potential interest too such as the Integrated Postsecondary Education Data System (IPEDS), which collects data from 7,500 U.S. institutions, allowing comparisons across key elements or indicators.
I also pay attention to the library-hosted institution repository, Deep Blue and Deep Blue Data, for reports, presentations, and data sets unique to the university. And while much more challenging to identify, I try to remember to review faculty research profiles and departmental annual reports for summary data that might be useful in setting a research context for library assessment efforts.