Throughout the 1990s and early 2000s, schools all over the world were learning to adapt to the rise of the internet and the migration of many school processes from physical to electronic formats. This shift required changes to databases and information systems, to how school personnel did their jobs, to the level of tech literacy school personnel needed, to budgets, and to school leadership structures as directors of technology joined senior leadership teams.
Over the past five to 10 years, a similar shift has started taking root in the independent school community around the role of data itself as a strategic asset. In a world where platforms like Netflix and Spotify seem to be able to integrate data about users from a shockingly broad number of sources, school leaders have begun to wonder if the data they collect about their community could be used not only for traditional task completion (e.g., making admission decisions or producing report cards/transcripts) but also for developing deeper insights about how the school functions (e.g., “Does the information we collect in the admission process actually predict whether a student will thrive at our school?”). With relatively recent advances from some of our largest vendors that allowed schools to liberate their data from their databases for further analysis, the answer has proved to be a resounding “Yes!” And the nascent field of independent school institutional research (IR) has emerged.
An established staple in higher education but still an emerging field in K–12 independent schools, IR can be described as the use of quantitative and qualitative data to describe and analyze school processes and inform decision-making. What exactly the practice looks like in schools, how it can be done, who is in charge of doing the work, how IR fits into decision-making processes, and how schools equip their communities with the data literacy skills they need to access the work are all open questions at this point.
Over the past five years, a network of institutional researchers and data analysts in independent schools has coalesced and, supported by an Edward E. Ford Foundation Educational Leadership grant to the Maret School in Washington, D.C., in 2020, come together to collaborate in the Center for Institutional Research in Independent Schools (CIRIS). Through webinars, conference sessions, and listservs/Slack platforms, CIRIS has aimed to provide a home for the people executing IR work to come together to explore all these open questions, build skills, and provide information to school leaders about what IR is and what it can do to help schools better deliver their missions.
One of the community requests that became most evident in this process was the need to provide a centralized repository of best practices and recommendations for schools looking to start or develop an IR program. To meet this need, CIRIS dedicated the 2023 Summer Fellows Lab, assembling a cohort of IR luminaries from across the country to share knowledge and expertise. The end product of this project, Data-Informed Decision Making: A Guide to Institutional Research in Independent Schools, touches on the diverse set of knowledge and skills schools need to foster a thriving IR program, including data strategy, survey strategy, data analysis skills, data visualization techniques, and how to cultivate a healthy communitywide data culture. It also includes tips for heads of school, boards, regional and professional associations, and vendors.
Given that data is the lifeblood of any IR program, it’s no surprise that tech office staff and institutional researchers (who are sometimes a part of the tech office themselves) have a shared interest in aspects of data collection and storage. Because this relationship forms the foundation of any IR program, CIRIS dedicated an entire chapter of the guide to data strategy.
Data strategy encompasses some facets of data policies that have traditionally been part of the tech office’s purview, including data infrastructure and data governance. As the guide makes clear, however, the concept of data strategy is more expansive and includes an exploration of whether schools are collecting the right data, whether the community has the data literacy skills to absorb analytical results, and how school communities can successfully navigate the institutional change dynamics that IR work can sometimes generate. In this chapter, CIRIS offers guidance on performing data inventories, creating data maps, auditing data quality, comparing current data collection practices against a school’s strategic goals, identifying new data flows to enable insights around those goals, adopting data style guides, and discovering ways to maximize data interoperability between systems.
This kind of technical work is imperative in an era when schools are increasingly focused on “squishy” priorities such as student and faculty/staff wellness or DEI. In order to describe the current state of our schools or to measure progress in these areas, we need to decide which data we should be collecting, how to consistently record and store that data, and how to ensure this new data integrates with our other information systems.
Some foundational yet surprisingly nuanced and thorny questions for schools that want to analyze DEI outcomes would be: How do we record data about the race/ethnicity of our community? Is our data complete? Do the available categories and data formats allow community members to report their full identities? How do we map our internal categories with the categories required for external reporting? Are the categories available in our various database systems consistent, or do some people have contradictory identities depending on which system we consult? In cases where there are conflicts, how do we determine which system is our source of truth? Many schools are surprised to discover that the answers to these seemingly simple questions are not what they assume.
Creating a coherent policy to address these questions is an exercise in data strategy because it touches on not just tech office staff but also the work of a DEI coordinator, admissions staff, communications personnel, and institutional researchers. One of the recommendations in the guide is that schools should anticipate the emergence of these kinds of questions that affect multiple offices and should create a data strategy committee comprising office staff from across the school—especially the tech office—to address them.
Being data-informed and executing IR are about much more than simply generating dashboards or reports. Shifting from a traditional, task-oriented data footing to an insight-oriented approach calls for an evolution, not just in the production of analysis but also in data storage and governance, in communitywide data literacy, and in how school leaders manage change dynamics.
Like the 1990s and 2000s, we find ourselves in new territory around data analysis—with the next new frontier of AI barreling toward us al-ready—without a prescribed road map for how to make these changes. As schools attempt to make this transition and discover new ways to ensure they are delivering their missions as best they can, CIRIS hopes the guide will prove useful and serve as a beacon to bring more of the IR community together as we support each other onward.