AACRAO caught up with University of Minnesota colleagues Tina Falkner, Director of Compliance and Continuity and AACRAO Vice President for Records and Registration, and Rachel McKessock, Coordinator of Student Degree Progress. They discussed their upcoming AACRAO Annual Meeting session, Mining Student Data in Search of “The Graduates.”
The mandate also set higher first-year retention rate goals.
AC: Can you elaborate on the student data you used - was it being collected already, or did you have to start adding new fields in your SIS?
Rachel McKessock: We had to both collect more data and use more of our existing data. Before this effort, we had student information stored and collected across a number of different places and forms of media. We had to build a system which pulled all of the relevant data from admissions records, the academic transcript, the degree audit system, and all of our new advising tools.
And with this flood of data, we were able to analyze the main components that affect progress toward degree. Of the components, we chose to focus on four main areas: academic policy, student behavior, curriculum, and student services (aka, academic advising).
AC: Did you encounter any difficulties when dealing with other departments or systems to get at this data?
Rachel McKessock : It was hard to get everything together. The information and records were all so decentralized. I should also add that it was challenging to figure out what was needed and what wasn’t. That said, there was no department that was unwilling to share the data or work together to get results; but there was some reluctance in how to use the data and what it might expose.
In doing this work, we were exposing some of the problems that are endemic to the decentralized model. People weren’t using all the tools available to them, and we also found inconsistent or incorrect application of policy and practice.
TF: For example, our academic course repeat policy states that students may only repeat a course once, but in practice students were allowed to take the course many times. It goes without saying, those students took much longer to graduate.
AC: You mention some of the red flags you encountered when looking at the data – what were the main areas you ended up zeroing in on?
RM: As we mentioned earlier, there are lots of factors that have an impact on student degree progress. We knew that we couldn’t tackle them all but chose to focus on the ones we believed had the biggest influence on retention and graduation were policy, student behavior, curriculum, and student services.
TF: For example, , we were able to identify curriculum bottle necks and requirements that perhaps impeded progress towards earning degrees. Additionally, we had an advising culture that waited for students to come to them rather than what we are currently using – what I call appropriately intrusive advising.
RM: – It really is a web of things that affect graduation and retention, it isn’t just one area.
AC: Have you seen success since you have started collecting and using this data to change practice and policy at Minnesota?
RM: We have actually exceeded our mandated goal of a 60% graduation rate, and we have seen increased retention rates.
RM: One of the hurdles we had to overcome was this sense from some members of the institution, that in order to improve graduation and retention rates, we needed to decrease our academic expectations of students. That simply isn’t true, we need to examine and re-think how we deliver our curriculum. I think we should also mention that we did work with the Associate Deans rather extensively once we identified issues. We want students to graduate but we don’t want to ‘dumb down’ the curriculum either.
AC: You were able to implement this system and make a meaningful impact with the data, but do you think the same system could be developed at a small private school, for example?
RM: We hope to convey that regardless of what sort of institution you are at, it is possible to make this project a reality even without full-time staff. I would say it is likely more manageable at smaller institutions simply because you won’t be dealing with as large a data set as we do at the University of Minnesota. Simply focusing on one area that has an impact on graduation and retention rates can have positive results. TF: Our model is not the only way to do it, but you need to get into your data to make your retention and graduation rates grow reliably.
RM: All our decisions are things that we truly believe are in the best interest of the student and the university. Whatever approach is adopted, make sure to block out all the other noise and focus on those interests.