From Accountability to Care: Analytics for Personalized Student Support

Civitas Learning Blog Catalytic Conversations

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We’ve witnessed a gradual but radical shift in higher education’s approach to data over the last 15 years — from a culture of accountability to a culture of care. In the most recent installment of Catalytic Conversations, Mark Milliron and Angela Baldasare (formerly of the University of Arizona) discuss the facets of the transition from reporting metrics to actionable insights and outcomes, as well as the recipe for successful implementation.
The Constraints of Accountability
In the late 1990s on campuses across the US, increasing accountability demands from the federal government and other key stakeholders led to the development of teams devoted to data reporting and, ultimately, a focus on the goal of improving student data metrics. In the system of accountability, colleges and universities had to collect data, maintain in-depth student records, and generate comprehensive reports to demonstrate improvement and meet accreditation and funding requirements. One major limitation of how this system has been designed by and for government stakeholders is that, while it provides meticulous metrics on student performance, the primary goal becomes improving the metrics — not necessarily student performance. When making decisions on improving metrics, it’s easy to lose focus on improving the student experience. While overlap exists between metrics and outcomes, the former doesn’t always impact the latter. In the podcast, Angela states that by manipulating or maximizing metrics like admissions criteria and credit hour loads, institutions can meet key accountability and performance targets. However, these numbers may not correlate with the actual success of students. The result is that some colleges and universities may have excellent ratings without having improved their students’ success. Another significant limitation of the system of accountability is the quality of the stories told by the data. In his conversation with Angela, Mark posits that accountability data — better known as “autopsy data” — looks backward at what has already occurred. It is neither diagnostic nor explanatory. What were the trends? What were enrollment numbers? What was the credit hour attainment? What many institutions do at the close of term is look at data from that term and try to pull out outcomes; however, the ability to draw historical trend lines does not lend itself to understanding problems, responding to them in real time, or proactively heading them off.
Reporting Well vs Supporting Well
In contrast, a culture of care focuses first on improving student success outcomes, not institutional metrics — although a by product of this model is that by focusing on students, metrics also improve. Where systems of accountability target metrics like enrollment numbers as a measure of success, a culture of care goes on step further by also tracking numbers related to retention, graduation, and post-college employment. Teams involved in this work utilize data not purely for its own sake, but primarily for providing personalized support to help students succeed throughout their academic career. That is to say, the students’ journey at the institution is just as important as their entry. Instead of looking to the past to define institutional success, this approach instead uses data insights to identify students who are off track to support them in real time. The precision and actionability of these insights are even challenging assumptions about at-risk or “high priority” student groups. But the approach also extends beyond that to institutional organization and process. To ensure the effectiveness of student success programs and initiatives, teams centered around student success leverage available data to measure whether those efforts worked. It asks important big-picture questions: How do we create a data infrastructure to help with real time support? How do we measure what’s working for specific students so we can refine our efforts? In turn, this iterative approach builds a cycle of continuous learning and improvement with a flexible framework for institutional learning.
Laying the Foundation of Support with Data
So, which approach is right for your institution? Mark and Angela agree that both measures of accountability and a culture of care are integral to institutional success — in the eyes of key stakeholders as well as in fulfilling their mission to help students succeed. Reporting on accountability metrics is indispensable to higher education’s existence. These metrics are important as mechanisms for regulation, accountability, and as sources of information that help students and families understand institutional performance as they compare colleges. Yet the added layer of diagnostic data and a student-focused infrastructure within a culture of care is necessary for real-time support. Without it teams are limited in the impact they can make on student success. The right practice involves building an operational strategy on top of the existing metrics reporting infrastructure, ensuring that students reap the benefits of actionable data insights. And as a direct result, institutions reap the benefits of reporting improved student and institutional outcomes.

Check out the Catalytic Conversations podcast to hear Angela Baldasare and Mark Milliron dive deeper into the culture of care model and the key ingredients for successful implementation.

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