Five data-informed steps for optimizing college student retention
Vice President, Consulting Services
February 21, 2012
The University of Texas made news this week as it unveiled an ambitious plan to raise its four-year graduation rate by 20 points for its next class of entering freshmen.
It’s a strong move and in my opinion a correct one. My colleague Jim Hundrieser has written before about why raising standards for student completion would benefit both institutions and students. In their rationale for pushing this change, Texas cited lowering the overall cost of attending college for students (and lowering potential debt loads) as well as using institutional resources more efficiently. Graduating more students in four years requires less time and money for the institution, which in turn frees up more resources to keep graduating students in a more timely fashion.
It’s an ambitious plan and I hope that Texas succeeds. At the same time, having helped many campuses with the same ambition, it’s also quite a challenge. Where do you begin?
The answer is data. Simply put, data are the lifeblood to successful student recruitment and retention. You cannot possibly hope to maximize enrollment yields and student completion rates without strong data analysis and planning. The following five steps illustrate how to achieve a robust, data-informed approach to retention.
- Make data the foundation for decision making. It sounds simple, yet my colleagues and I continuously visit campuses that do not rely on data to guide their strategies. Often “conventional wisdom” or “that’s the way we’ve always done it” override any actual research or data. Those types of processes are very flawed for crafting enrollment strategies, especially given the rapid changes that are reshaping the higher education environment.
- Collect all the data that are relevant to student success. In discussing student retention, first-to-second-year persistence and overall completion/graduation rates are useful metrics. However, they do not provide a complete picture of persistence patterns and are lagging indicators, gathered only after it is too late to intervene with students. My colleague Lew Sanborne has outlined excellent additional retention metrics to track. There are also many other data elements to review that can help not only provide a more accurate assessment of retention at your campus, but intervene with students in a more timely fashion, such as:
- Student motivational data—How do students feel about attending college? What are their attitudes toward studying? What family and/or social factors could be interfering with their success? Motivational data can go a long way toward focusing your student retention initiatives.
- Credit hours attempted versus credit hours earned—This ratio is very revealing as it demonstrates if students are succeeding in their educational plans before reaching the critical juncture of withdrawing. It is a very useful measurement to assess students at the midpoint of their first year.
- Student satisfaction and priorities assessment—When students are not satisfied, they become less likely to persist. Improving their satisfaction improves the quality of their life and learning. Coupling that with priorities assessment helps you better understand which satisfaction issues are the most pressing and need immediate attention.
- Common characteristics in student retention—Do students who persist or withdraw share common characteristics? Are there indicators of student success or red flags for persistence that would help you quickly understand which students you should target?
- Institutional barriers to student success—Similar to student characteristics, are there certain factors across campus that may be hindering persistence and completion?
- Understand what the data are telling you. You have made a commitment to collecting data and have gathered the data you need to inform your decisions. Now what? This is turning point for using data to improve student retention. You have to be able to know what the data say about student persistence. Are there patterns to persistence? Do you know which students or cohorts to prioritize? Which resources are having the greatest impact on student success? This is admittedly one of the more difficult tasks in data-informed retention planning and one where experience really pays off. However, once you successfully analyze your data, your retention efforts really take off as well.
- Take action based on the data. Here we close the loop with step one. Now that you are informed by data, you can build retention initiatives on solid information. You’ll be able to focus your limited resources more strategically on the students who need the most help and/or are the most receptive to assistance.
- Use what you know about retention to guide recruitment. There is still a tendency to look at student recruitment and retention as two unrelated silos. But one of the biggest factors in student retention is the shape of the incoming class. It is vital for campuses, when recruiting, to extend their concept of the funnel past the initial enrollment stage and through the career of the student. By determining which students not only have the desired characteristics you want, but also the best chance to persist and succeed, your entire campus benefits. (For an example of the relationship of recruitment and retention, read our report Targeting Financial Aid for Improved Retention Outcomes about our work with public campuses in Louisiana.)
Of course, these strategies really just touch the tip of the retention iceberg. I encourage you to continue to keep researching and learning about the best strategies for improving student retention (I recently wrote about some of the pioneering studies in the field). Noel-Levitz also has produced a number of recent retention studies that provide benchmarks and strategies.
Finally, if you would like to explore this topic further, I invite you to attend a Webinar my colleagues and I are conducting on March 8, Focusing Your Enrollment Management to Increase Recruitment Yields and Completion Rates. In particular, we’ll discuss how you can use data to predict enrollment behavior and how looking at the complete funnel, from prospective student to graduating student, is a much more holistic and effective approach to student retention.
As always, please feel free to e-mail me or leave a comment if you have any questions.