Getting an associate degree before transfer isn’t always helpful

February 5, 2026
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For many students, vertical transfer (transfer from an associate’s to a bachelor’s program) is less a bridge than a maze. Typically, about 80 percent of community college students say they intend to earn a bachelor’s degree, yet only about 30 percent ever transfer and roughly 16 percent complete a bachelor’s within six years.

Yet under these topline numbers, outcomes vary widely. And figuring out which combinations of student actions and background factors matter, and which pathways are most promising, can be a complicated mess. As a result, much of the advice students receive rests on rules of thumb that feel intuitive, or on research that is merely simple correlation, failing to account for the complex reality of interconnected variables.

Through research in progress on vertical transfer, we have been analyzing transfer outcomes in ways that move beyond intuition or simple correlation and toward reliable evidence about what different pathways actually mean for associate-degree students’ likelihood of earning a bachelor’s degree.

There is a better approach to isolating what matters.

Transfer students differ from each other in many significant ways, including their GPAs, credits they’ve earned, when they transfer, their majors and life circumstances. Institutions also vary in alignment of requirements across general education and majors, and in the extent to which they support transfer students. Many of these attributes of both students and colleges are correlated with one another, making it hard to untangle what really matters in transfer student success.

In our project, to better understand the probability of positive transfer outcomes given these complex combinations of variables, we use a LASSO (least absolute shrinkage and selection operator) regression approach. LASSO is a statistical method that builds a prediction model while automatically reducing the influence of less important variables, sometimes eliminating them entirely, to keep the model simple and accurate. We apply this technique to a detailed and comprehensive transfer-related dataset: administrative data on approximately 38,000 City University of New York (CUNY) students who entered a community college between 2011 and 2018 and transferred to a CUNY bachelor’s college within four years.

This novel approach allows us to consider hundreds of student, pathway and institutional characteristics, along with their interactions, simultaneously. Rather than deciding in advance which variables should matter, the model identifies which factors are most strongly associated with and predictive of completing a bachelor’s degree within six years of starting community college. We have presented our analyses at multiple academic and practitioner-oriented conferences, and publication is forthcoming.

What the Findings Tell us, and the Conventional Wisdom They Challenge

Getting an associate degree before transferring is sometimes associated with increased bachelor’s-degree receipt, but not always.

According to our analyses, all else being equal, earning an associate degree before transfer is associated with a small increase, about 2 to 3 percentage points, in the probability of completing a bachelor’s degree.

But that result masks important differences. Students who earn transfer-oriented Associate of Arts (AA) or Associate of Science (AS) degrees see this modest boost, about 2.4 percentage points. However, students who earn an Associate of Applied Science (AAS) degree are about 5 percentage points less likely to complete a bachelor’s degree after transfer than students with AA or AS degrees. This is likely due to the fact that AAS degrees are considered terminal, not transfer, degrees, and at CUNY the AAS general education and major requirements are not aligned well with those for bachelor’s degrees. Consistent with this interpretation, AAS students who transfer before they earn their degree, and before they complete all the courses required for the AAS, do not face a similar bachelor’s graduation penalty. The takeaway is that alignment matters far more than simply earning a credential.

It is also worth noting that the magnitude of the effect of earning an AA or AS on graduating with a bachelor’s degree, holding other things constant, is small relative to the effect size of other variables such as GPA, number of credits and timing of transfer.

More transfer credits are associated with better transfer outcomes, but with diminishing returns.

Accumulating more credits before transfer is another factor associated with an increase in the likelihood of graduating, however that benefit diminishes as students accumulate more and more credits.

Students who transfer with relatively large numbers of credits are more likely to graduate than students who transfer with a moderate number of credits, however a student’s graduation probability increases most sharply alongside early credit accumulation. Results further suggest that transferring with very large numbers of credits provides no benefit to a student’s odds of graduation and may even be harmful. This reinforces the principle that credit applicability, not only credit volume, is what supports completion.

Waiting longer to transfer predicts significantly lower chances of earning a bachelor’s degree.

Timing has one of the strongest associations with completion in the entire analysis. Each additional year before transfer is associated with a large drop in the probability of earning a bachelor’s degree within six years of starting an associate’s degree program, even after accounting for GPA, credits earned, major and institution.

The flip side is also true. Well-timed, structured pathways are associated with substantially better outcomes. Students who vertically transfer as part of CUNY’s Justice Academy joint-admission program are about 11 percentage points more likely to complete a bachelor’s degree than otherwise similar transfer students.

Changing majors at the time of transfer is associated with a reduced likelihood of earning a bachelor’s degree; but so is continuing in the same major at a poorly aligned destination college.

Conventional wisdom holds that changing majors at transfer is risky, and the evidence supports that view, especially in STEM. Students who switch from a non-STEM major at the community college into a STEM major at transfer are 14.9 percentage points less likely to receive a bachelor’s degree than similar students who choose a major outside STEM when they transfer.

But focusing only on major switching misses an equally important risk. Choosing a poorly aligned receiving institution, even within the same major, can be just as problematic as switching majors. For example, our analysis shows that, holding everything else constant, students pursuing a nursing associate degree and transferring into a nursing bachelor’s program face a wide range of outcomes depending on which CUNY campus they choose. The difference in probability of bachelor’s completion between the highest probability transfer destination and the lowest probability destination is more than 20 percentage points.

From Analysis to Action: the Promise of a Transfer Scorecard

One promising application of this work is a Transfer Scorecard, an interactive tool that translates complex analyses into clear, usable information. Such a scorecard could show how a student’s likelihood of graduating changes depending on when they transfer, which major they pursue, and which institution they attend. Used responsibly, it could help administrators identify pathways that deserve investment or reform, support advisers in offering more precise guidance and empower students to make more informed transfer decisions.

The goal is not to dictate choices. It is to make tradeoffs visible. When the stakes are this high, students deserve advice grounded in solid evidence.

Martin Kurzweil is managing director of Ithaka S+R. Alexandra W. Logue is professor emerita at the Center for Advanced Study in Education, Graduate Center, CUNY. Pooja Patel is a senior analyst at Ithaka S+R. And David Wutchiett is a data scientist and analyst at the Office of Applied Research, Evaluation and Data Analytics at CUNY.



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