Strategic Enrollment Management Quarterly

Advancing research in enrollment and student success

Editor's Note

Tom Green, Ph.D.


I recently spoke on a panel during a meeting of higher education and business leaders. One of my fellow panelists, a data scientist, said, “Data is the new oil.” His comment reflected the rapid rise of data as a major commodity in our economy. Our ability to harness it, analyze it, and make sense of it for some purpose has become big business in most sectors, higher education included. In this issue, the first of our eighth year of publication, we feature three articles focused on the use of data in SEM.

The use of data in student retention is the focus of an article by Bert Ellison, John M. Braxton, Melissa Lang, and Kelly Grant. Their angle on this topic is to ask whether the tools we use to examine retention at our institutions, student information systems and others, as well as surveys used to gather information not found in these databases, are tied to what we know are important factors in student persistence. Are we gathering the information we need to understand our students’ likelihood of continuation? This well-written article takes on one of Big Data’s key challenges. With so much data all around us, what is the important data to track, and how do we make meaning of all of it?

What could be a hotter topic in data science than artificial intelligence? David Hansen takes on the use of machine learning and artificial neural networks as a tool to improve predictive analytics in admissions. In a case study approach that invites replication, the article tracks how one university took up the challenge of applying AI to predict which prospects were most likely to enroll at the university. While past and common approaches to predictive analytics used (mainly) logistic regression against the dependent variable of matriculation, Hansen’s approach uses neural networks, which work to find linkages and commonalities among large variable sets. His approach appears to create more reliable results at a far lower cost than commercial services. Of course, it implies that the intellectual resources and skills are available in-house!

The third data article in this issue, penned by Morgan Blair and Alex Zanidean, looks at the impact that data analysis is having on the enrollment profession. They profess that the days of following your gut, making the best guess, and rolling the dice on enrollment strategies are now gone. With so much research and data available to us, it is no longer necessary nor defensible to “fly blind” on enrollment strategies. Data is, after all, the bedrock of SEM, and this article discusses the existing complexities associated with getting one’s hands on the information required to make data-informed decisions. The authors borrow a technique from manufacturing, control charts, as a methodology to assist enrollment managers in harnessing the data they need to make data-informed decisions without the constraints many experience in trying to gather it.

This issue isn’t just on data, however. Zach Taylor offers an analysis of the relationship between internet search and summer melt, or the phenomenon of students who undertake the college admissions process but don’t wind up attending any institution after high school. By looking at the ways in which websites are optimized to allow search engines to find topics on them (keyword searches), Taylor notes that those with greater levels of search optimization fared better than those who used paid advertising for keywords. In short, paying attention to the tags on your website is a more cost-effective and more productive means of increasing yield and, inversely, reducing summer melt.

Tyler Portis provides a very well-written and well-researched article on the disproportionate impacts of loans on our African American students. He points to several key data points, including higher rates of borrowing and higher default rates among this part of our population. These are inextricably linked to issues of income inequality and lack of familiar financial capital that are also prevalent for African Americans. Portis points out two important practices that can help these students: appropriate repayment counseling for enrolled students and outreach to former students who leave without degrees. While he also points to the practices of for-profit institutions in the article—and these are documented among some institutions in that sector—this is an issue that impacts all institutional types, regardless of their control. While higher education can be the solution to income inequality for many students, Portis’ important article highlights the ways in which we are contributing to income inequality for those African Americans who struggle with student debt.

Happy reading!