Your Student Success Plan Needs A Smart System

November 7th 2017

It’s hard to go to any college campus or higher education conference and not hear about student retention. If your institution is starting to develop new plans to address retention issues—or looking to refine existing efforts—figuring out where to focus may be a challenge. There is great breadth in definitions of success, best practices, funding sources, and a host of other issues related to student success. If you feel dizzy just trying figuring out where to start, not to mention evaluate whether or not you are on the right track—welcome, you are not alone.

Next week, I’ll be co-presenting a University Business webinar on approaches to holistic student success, and on the idea that student success means more than simply focusing on academics. Many student success and retention efforts have a heavy academic focus—and rightfully so. But, academics are merely a single component of any comprehensive plan. A holistic plan must also consider non-academic topics and issues.

In order to have a truly comprehensive plan for student success, your campus must be able to pull all of the pieces—academic and non-academic—into the conversation. And, as I think through this topic, the importance of having smart systems in place on campus to help manage these efforts is one of the first key components that comes to mind.

With so many data points scattered across campus, countless faculty and staff engaged as key stakeholders, and multiple programmatic efforts, having a smart system to manage your student success efforts is critical.

In order to have a truly comprehensive plan for student success, your campus must be able to pull all of the pieces—academic and non-academic—into the conversation. A smart system can help.

A Smart System for Smarter Retention Plans

So, what do I mean by smart systems? A smart system used on a campus to assist in student success and retention efforts should fundamentally do four things:

1. Integrate data from a variety of sources into a single location.

There is no doubt that colleges and universities have a wealth of information about their students. However, the challenge is finding a way to get that information all in one place.

  • Institutional records contain admissions data, enrollment patterns, academic performance, and financial aid information.
  • Other systems may have course-level engagement data.
  • Individual offices may house notes and records on visits and interactions.
  • Surveys may gather information on goals, commitment, non-cognitive variables, intentions, and satisfaction.

Even if this data is shared across campus, it is likely in more than one system. Having a system that can pull in data from a variety of sources and place it into a single view is imperative—it saves you time, and your time is a precious resource.

2. Analyze the information coming in.

Not only should your smart system or tool consolidate information into once place, it should also analyze and evaluate that information to help your faculty and staff make sense of it. If there is too much information in one place, or if it not organized in a thoughtful manner, you’re likely going to be confused and overwhelmed. What do you need to focus your attention on? What are a student’s strengths and weaknesses? What information has been most recently added? And, how do you get the results you need quickly? Your smart system of choice should analyze information as it comes in, place things into a single view, and help to spot patterns and make sense of the information in a timely manner.

3. Predict which students may struggle.

There are many models which drive how campuses—and those within a campus—make decisions about how to identify and support at-risk students. If you work with student retention, I’m sure you’ve noticed. Some may create triggers or flags from certain data points. Others many profile those who leave and try to find similar students. However, models that identify individual students at-risk of leaving based on predictive analytics make the most sense, and best utilize your relevant campus data to inform student success efforts. Predictive models let campuses to use multiple data points to make risk predictions about individual students, thus allowing for prioritization and focus of campus efforts. Given the need for manageable workloads and other challenges, individual risk predictions provide focus and help you to prioritize your efforts.

4. Share those predictions in a timely manner with people who can make a difference.

At the end of the day, the most accurate risk predictions are useless if they are not in the hands of staff who work with students each and every day. One of the biggest challenges with predictive models is that they can quickly become incredibly complex and difficult to use on a practical level. The results or output of any predictive components should be displayed in a simple, easy-to-use way. The primary goal of most student success initiatives is to empower campus faculty and staff to identify at-risk students, connect them to the resources they need the most, and enable them to persist and complete their college degree. A smart system will deliver critical insights on individual at-risk students quickly to front-line staff and allow them to act. So, any system must allow our campus users to do just that.

Interested in hearing more about comprehensive approaches to student success? Register for our upcoming webinar, presented with University Business, exploring the holistic student experience.