Graduate Student Retention and Graduation Rates
Dear Suzanne: Why should we pay attention to graduate student retention and graduation rates?
When considering how to answer this question, I looked at two overall questions: First, how do institutions handle graduate student retention and graduation rates? Second, what is the best method for conducting this type of analysis? There is very little research as to what other institutions are doing on this topic, however, research conducted at the University of Alabama in Huntsville and The Mississippi University for Women in 2018, found that the solution is not necessarily "one size fits all." In reviewing data for these two institutions, each office found that data disaggregated to the degree level may cause your population and/or your samples to be too small and therefore cause validation issues.
The institutions began the process by looking at degree programs, because graduate students often enter a degree program at varying admission cycles and enrolled hours of study. Due to institutional policy adherence, the researchers hypothesized that having the cohorts in programs would garner better outcomes; however, going back to previous research completed by Simpson (2014), the institutions changed the cohort to all first-time graduate students, regardless of the area of study or whether they were full or part-time. Doing this allowed for more students in the cohort and contributed better results in the pilot project.
We need to address why stakeholders should be concerned. For undergraduate students, many institutions use these measures for peer analyses. In most cases, state governing boards that accredit academic programs have their own defined standards. For example, there are several states where institutions measure academic program productivity and should meet a minimum number of graduates (Mississippi Board of Trustees, 2018).
Other reasons include system or institutional governance practices, accreditation standards, and national reporting requirements. Admissions and enrollment managers may use the data to assist with enrollment projections and preparing for future student attendance, for determining how many classes should be offered, and for determining how many faculty members are needed for an upcoming term. Knowing how many students are expected to attend and to be retained through completion helps programs manage their time, funding, overall growth and success (Boyce & Rickard, 2008).
Another aspect as to why graduate student retention and graduation rates are important is the impact of programmatic success on financial aid eligibility. Most financial aid offices follow a prescribed formula to allow students to continue to receive federal funding. A student aid award is based on the total number of hours required to complete each program for both undergraduate and graduate students. According to the federal Student Academic Progress policy, graduate level students in master’s degree programs are expected to complete their 30-hour degree by the time they reach 40 credit hours and cannot receive financial aid for hours over 120% of the defined credits for the degree (U.S. Dept. of Education, 2011). Financial aid requirements therefore impact the way students complete their programs of study.
Other reasons include enrollment projections, the institutions percentage of alumni donations from graduate students, and whether the student’s salary increased because they completed a graduate degree. Additionally, are there impacts on earning an advanced degree, spending, and taxes in the economy?
A federal model for measuring graduate student success does not exist. Based on research by Simpson (2014) institutions should consider measuring graduate students equally regardless of their major. As an example, when measuring two graduate programs between 2002 and 2007, Business Administration and Counseling, graduate students in Business were 150% more likely to graduate. Other significant indicators were identified in the study, such as Caucasian students were 175% more likely to graduate than minority students. Students who received federal assistance and those who received waivers were 47% and 87% more likely to graduate respectively. The model, although it had significant indicators, should include variables that address social integration, including extracurricular activities or other groupings like graduate cohort programs, and potentially not address the degree program alone (Simpson, 2014).
Identifying how the initial sample is captured will aid in the success of the model. Next, you will want to choose a 2-, 4-, or 6-year rate as compared to 4-, 6-, and 8-year from the undergraduate model (U.S. Dept of Education, 2012). Additionally, disaggregation by student level (Certificate, Masters, Specialist, or Doctoral), demographics, and institutional policies on the time allotted to complete the degree, and the number of hours used for transfer credit may be beneficial for your analysis. Finally, whether or not the institution admits provisionally, or if the institutions has a cohort model may aid in your institutions model.
Within this article, I have addressed several ideas as to why measuring graduate student progression and completion rates are important, and a beginner’s guide for how an institution can start to think of ways to measure graduate student success. As IR/IE administrators, we should ask ourselves how graduate students impact the institution as a whole. Doing this may lead to more robust analyses of how these students impact our institutions overall.
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