Use this whitepaper to learn more about risk indicators to help you identify students in the Murky Middle.
More than half of students who drop out of college do so in their second year or later, even after ending their first year with GPAs between 2.0 and 3.0. These students represent a “Murky Middle” where graduation outcomes are difficult to project.
Late-stage dropouts account for more than half of student attrition
While the first year is the single biggest year for attrition, over half of all student departure occurs in subsequent years. However, little is known about students who leave college in their second year or later, or what can be done to better support them through to graduation.
This resource is part of the Reimagine Constituent Engagement for the 21st Century Roadmap. Access the Roadmap for stepwise guidance with additional tools and research.
Before we can begin to develop effective intervention strategies targeting these students, we need to first develop a better understanding of who might be at elevated risk of a late-stage dropout (defined as dropout in the second year or later).
What is the Murky Middle?
Most student success initiatives target freshman students, but 52% of attrition occurs after the first year. And of these late stage departures, over half are within the “Murky Middle.” Here’s how to track degree progress after first year completion.
Use data to identify the Murky MiddleGet the Infographic
Unsurprisingly, early academic performance is a reliable indicator of ultimate graduation outcome. What is surprising is that the vast majority of late-stage dropouts were in good academic standing with a GPA between 2.0 and 3.0 when they returned for a second year.
But just over half of the students in this range ultimately graduated; nearly one-third dropped out in the second year or later. Because of their inherent ambiguity in graduation outcome, we’ve come to refer to the entire population of mid-range GPA students as “The Murky Middle.”
Emerging research from SSC suggests that rigorous analyses of academic data can separate the hidden population of struggling students from the likely graduates, enabling targeted intervention efforts—and ultimately improved outcomes.