In the context of higher education quality assurance, sound academic decision-making cannot rely on instinct or personal preferences—it must be based on evidence. That evidence often comes in the form of key metrics, specifically key assessment data. For institutions to drive continuous improvement confidently, faculty and administrators must both (1) understand what the data reveal about current practices, and (2) use that understanding to guide future strategic planning.
To accomplish this, institutions need high-quality metrics and the ability to view them from both macro and micro perspectives. Aggregated data offer a big-picture view of student performance, while disaggregated data reveal the finer details needed to understand patterns and areas for improvement.
Aggregated Data: The Big Picture
Aggregated data are summary-level data that give a broad overview of institutional performance. These include statistics such as overall pass rates on exams, enrollment trends, retention, and graduation rates. They are especially useful for public reporting—such as IPEDS submissions or presentations to external stakeholders like advisory boards and community groups.
This type of data helps institutions “tell their story” at a high level and demonstrate overall effectiveness. However, aggregated data alone often mask important variations within student populations. To make meaningful programmatic improvements, institutions must go deeper—by breaking these data sets into smaller, more specific subsets through disaggregation.
Disaggregated Data: The Details That Drive Program Improvement
Many accrediting bodies such as HLC, CAEP, AAQEP, TRACS, and others require institutions to report both aggregated and disaggregated data across at least three assessment cycles. Common disaggregation parameters include program, cohort, gender, and race/ethnicity. While this is feasible at large institutions with diverse enrollments, it poses a challenge for smaller colleges or institutions with relatively homogenous student bodies. In those cases, disaggregation by gender or race may not be statistically meaningful or helpful for decision-making.
Depending on the assessment and institutional context, alternative disaggregation strategies can provide valuable insights. For instance, disaggregating by cohort is common—typically based on academic years (e.g., September 1–August 31). In licensure-based programs like teacher education or nursing, disaggregating by specialty area or licensure pathway is also standard practice.
Beyond that, institutions can disaggregate data in the following ways:
- By entry status: First-time freshmen vs. transfer students
- By admission type: Fully admitted vs. conditionally admitted students
- By prior degree: Post-baccalaureate students vs. those without a degree
- By course modality: Face-to-face vs. online learners
- By instructor: If a course or field experience is taught by multiple faculty
- By academic preparedness: Based on incoming GPA or standardized test scores
- By assessment attempt: First attempt vs. multiple attempts on key assessments or licensure exams
- By support service utilization: Students who were referred to academic support services vs. those who were not (similar to analyzing at-risk vs. non-at-risk student groups)
These strategies allow program leaders and faculty to gain a more nuanced understanding of how different groups of students are performing—and why.
Conclusion
Aggregated data are essential for summarizing institutional performance and sharing high-level outcomes. But disaggregated data offer the granular insights needed to identify strengths, pinpoint challenges, and support targeted interventions. In today’s accountability-focused educational landscape, combining both views enables colleges and universities to make truly data-informed decisions that lead to meaningful, strategic improvements at both the program and institutional levels.
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About the Author: A former higher education administrator, Dr. Roberta Ross-Fisher provides consultative support to colleges and universities in quality assurance, accreditation, educator preparation, program development, and competency-based education. She can be reached at: Roberta@globaleducationalconsulting.com