Data-Based Decision Making for Retention: Seven Policies That May Be Working against Retention and Net Tuition Revenue Goals

By Kurz, Kathy; Scannell, James et al. | University Business, January 2008 | Go to article overview
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Data-Based Decision Making for Retention: Seven Policies That May Be Working against Retention and Net Tuition Revenue Goals


Kurz, Kathy, Scannell, James, Veeder, Samantha, University Business


MUCH HAS BEEN ANALYzed and written about the price sensitivity of new students, but an increasing number of institutions are beginning to think in a more data-driven way about how pricing and discounting decisions impact returning students as well.

Typically, the first way institutional leaders begin to gather data on retention is to survey students who have left or are planning to leave. "I couldn't afford it" is certainly a frequently given reason for withdrawing. But survey responses can be unreliable and even misleading. Many students who leave will not respond to a survey, and those who do respond may be reluctant to share their real reasons for leaving. Saying "I can't afford it" is easier than admitting "I can't do the work" or "I'm homesick." Consequently, for survey responses to be translated into strategic policy changes that will make a difference in retention, more needs to be understood.

One valuable source of information in studying retention is the National Student Clearinghouse. Participating institutions can use the Clearinghouse's Student-Tracker (www.studentclearinghouse.org/colleges service to understand where students who have withdrawn are now attending college. Do students who say they can't afford it actually choose to transfer to less expensive institutions, or are they choosing an equally expensive but more prestigious option? If the latter, the comment "I can't afford it" may actually mean "I don't think this college is worth it."

However, probably the most valuable source of information on the price sensitivity of returning students is the institution's own student system. Student system data can be used to answer such questions as:

* Is attrition disproportionately high for students with high levels of unmet need?

* Do full-pay students leave at greater rates than financial aid recipients?

* Do students with changes to their aid awards have higher attrition?

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Clearly, it is not necessary (or even valuable) to rely on student survey or interview responses alone to understand more about how grants and unmet need impact persistence.

When beginning to use institutional data to study retention, it's important to explore the impact of specific financial aid policies that might be working against retention and net tuition revenue goals. Some of the most common candidates for analysis are discussed below.

1. Freshman-year-only awards

Some institutions offer scholarships for students upon entry that are available only for the first year of enrollment. Even when information about the award makes this policy clear, it's important to assess whether the loss of the award in the second year negatively impacts the persistence of recipients. (Institutions should not simply assume that such programs affect retention and make the scholarships renewable. Without the data to support such a policy change, institutions could find themselves significantly increasing the financial aid budget with no change in retention rates.)

2. High GPA requirements for merit renewal

One of the most poignant statements we have ever heard in a student focus group was from a young woman who had won her institution's most prestigious merit scholarship because she had had a 4.0 GPA in high school. Unfortunately, to retain the scholarship, she needed to continue to achieve that same GPA at the college. As she told us, "Getting an A minus is my worst nightmare."

Although this is an extreme example, many institutions do make students "re-earn" scholarships that they were originally offered based on prior performance as an incentive to enroll. To understand whether these policies are impacting retention, compare the retention rates of merit recipients with high GPAs to those who achieved GPAs above satisfactory academic progress but below the level needed for scholarship renewal.

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Data-Based Decision Making for Retention: Seven Policies That May Be Working against Retention and Net Tuition Revenue Goals
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