IN EXIT INTERVIEWS WITH students planning to transfer, the issue of affordability almost always tops the list of stated reasons for leaving. Institutions whose leaders take such responses at face value, however, could end up spending additional financial aid on upperclassmen without seeing any improvement in retention.
Often saying "I can't afford it" is easier than saying "I'm homesick," or "I don't know what I want to do with my education," or "I'm not able to handle the work." Consequently, it is important to further assess the role of affordability in retention using data.
National and international studies, as well as research conducted at other institutions, can shed light on possible influences of aid on retention.
For example, a number of institutional studies have shown that working on campus (as long as the student puts in no more than 20 hours of work a week) can have a positive influence on retention--probably because the job provides another connection to the institution. In August, the Educational Policy Institute (www.educationalpolicy.org) published a summary of research studies in a variety of countries (including the United States) that showed grants are more effective than loans at improving retention, but only of lower-income students.
Finding out whether such findings are true at your own institution, however, requires the use of institutional data, which is readily available from student records.
A SAMPLE ANALYSIS
The first step in understanding the factors most important in retention at a school is to examine retention rates by subpopulation for cohorts of entering students.
As a sample analysis ("Examination of Retention Rates," p. 32) demonstrates, this approach can shed light on whether high-need students are retained less than low-need students. Other financial-aid-related measures that could be included: levels of "unmet need" (e.g., need less grant aid from all sources); parent income levels; levels of total grant aid; types of aid received (e.g., merit only, versus merit plus need, versus need only); and student and parent debt levels.
This analysis can also be helpful in understanding the impact of specific financial aid policies. For example, leaders often wonder if they are setting the GPA bar for renewing merit scholarships too high. Examining retention rates of merit recipients by first-year GPA can help in assessing the potential enrollment and financial implications of changing renewal policies.
Similarly, some institutions allow students not initially offered merit awards to "earn" a scholarship based on their GPAs at the institution. Often, however, students performing well academically already have higher retention rates, and increasing financial aid to those students based on their high performance does not further enhance retention. Again, using a data-driven approach to setting such policies can help enhance institutional net tuition revenues.
EXAMINING THE VARIABLES
The disadvantage of simply reviewing retention rates by subpopulation is that some variables can be strongly correlated to each other, thus giving a false read on the influence of any one factor.
For example, national average-per-pupil expenditures on K-12 education are a function of the local tax base, and thus need and academic preparation are often strongly correlated. Consequently, if retention on high-need students is low, it could be because those students are not performing as well academically. To understand financial aid's influence, holding all other factors constant, therefore, is often helpful to build statistical models that will accurately predict retention. Such models then enable administrators to measure the unique contribution of each variable to the final retention outcome.
Because academic performance in the first term of enrollment is often a highly significant variable in an overall retention model, it is also instructive to build a model only for those students who achieved at a satisfactory level in Term I. …