A New Vision for Institutional Research

This post is authored by Civitas Learning’s Senior Director of Strategic Services, Dr. Rob Robinson. Read on to learn about the changes he is seeing in Institutional Research as he’s traveling the country meeting with Civitas Learning partner institutions.

group of professionals

The excerpt quoted below is from renowned institutional researcher and former executive director of the Association of Institutional Research, Randy L. Swing, Ph.D., (with Leah Ewing Ross) who has recently brought forward a manifesto of sorts that is generating important conversations across higher education. His work, “An Aspirational Vision for Institutional Research” addresses the changing role of the Institutional Research office as we see a growing demand for data as decision support.

“A new vision for institutional research is urgently needed if colleges and universities are to achieve their institutional missions, goals, and purposes. The authors advocate for a move away from the traditional service model of institutional research to an institutional research function via a federated network model or matrix network model. When capacity is gained by having many hands involved, new opportunities are possible. A broader range of decision makers are supported by the institutional research function, and a student-focused paradigm emerges without degrading required reporting and basic management support. To this end, the Association for Institutional Research, with funding from the Bill & Melinda Gates Foundation, created a “Statement of Aspirational Practice for Institutional Research”. This statement focuses on student success as a core element of an effective decision-support system of management. The “Statement of Aspirational Practice for Institutional Research” makes student success a core element of an effective decision-support system of management. The authors encourage readers to re-enact the pilot testing of the Statement of Aspirational Practice for Institutional Research in their own institutions, districts, or systems.”  – Swing, Randy L.; Ross, Leah Ewing   |  Change: The Magazine of Higher Learning, v48 n2 p6-13 2016

I want to talk more about this statement, but before we get into logistics, let’s talk linguistics. “Analytics” as a stand-alone term is at risk of losing all meaning in the buzz and hype being presented these days. Let’s take a moment and try to drive toward some clarity. Many experts in this arena have asserted a progression of types of data analytics. For instance, Baer and Norris talk about the various types of analytics, which are built on top of each other, with “predictive analytics” and “action analytics” being the top two levels.

Similarly, the Gartner Group has a well-known “value escalator” with four phases of analytical conditions. In this construct, as an institution moves from Descriptive Analytics, through Diagnostic and Predictive Analytics, the goal state is Prescriptive Analytics. This is a useful model for understanding the increasing difficulty as one moves up the value escalator. However, in practical terms, each of the stages represented here are predicated by the systems and tools that support the previous stage.  In other words, without the ability – at some level – to create reports from the data the institution already collects, there isn’t an easy path to progress up the escalator.

Let me go a bit deeper on this.  In referring to data-informed reports, I am specifically thinking here of the work of Institutional Researchers (accreditation, state and federal compliance reporting, operational data dashboards) – the “table stakes” of data use that all institutions of higher education must produce.  These reports summarize the status of the institution as of a fixed place in time – annually, or at the start of each term, usually. The reports contain specific, precise, numbers which answer specific – mandated – questions like: what is your Fall enrollment? What do those students look like (demographics)? Of the students who started six number of years ago, how many have graduated?  And on, and on…

These reports can answer specific, common, questions. But they aren’t sufficient to address the growing set of data-hungry institutional stakeholders that are focused on student success.  As Dr. Swing points out, the model in which the IR office is the single point for the supply and translation of data is no longer adequate in today’s college or university.

“The greatest potential for building effective institutional research is leveraging talent across the institution. The function of institutional research connotes the institution-wide use of data and analytics, and not just the products of an office of institutional research.” – Swing and Ewing

We are seeing a broad and rapid democratization of access to data and a subsequent change in the traditional role of the institutional researcher from “source of truth” to that of interpreter and consultant. Their role has not diminished, it has changed. The set of tools and approaches needs, therefore, to be sufficient to address the broader set of data needs. You can see stories throughout the Civitas Learning Space of this evolution in action including this Democratizing Data story with Lone Star College, this story with Montgomery County Community College and this on data and transparency from St. Petersburg College. The institutions making real gains in student success work are democratizing data and mobilizing their IR office in ways not previously imagined.

The point here is that not all analytics processes, tools, and uses are the same.  The need for a suite of approaches – some tuned to reporting and some tuned to student success – has become critical to institutional success.

As I travel the country meeting with institutional leaders doing innovative student success work, it’s great to see a spectrum of people and roles at the table – including the still critically important IR office, who now interacts and intersects in so many exciting ways across the campus.

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