According to the National Student Clearinghouse Research Center, total college student enrollment in the United States has declined 11% since 2011.
Much of this can be attributed to the strong economy: when it’s rolling, more people skip or postpone secondary education. Another barrier to secondary education is the rapidly rising cost of college. Public universities have been hit especially hard with reductions in funding from state governments, and this results in tuition increases that outpace grants and scholarships given to students. The increasing differential must be borne by families and many can’t afford to make the investment.
In a trend that seems counterintuitive, college applications are at all-time highs. High school seniors are being marketed to often and early from lots of schools, and the branding campaigns have led to students applying to more colleges in hopes of being accepted to the best institution they can. But as application numbers go up, acceptance rates decline, which colleges use to artificially create prestige and justify higher tuition costs.
Higher education has not been on the leading edge of analytics, but the art of advanced analytics is being used more often in this highly competitive environment to help colleges and universities meet their core goals of helping students graduate on time, minimizing student debt, and streamlining their own operations.
Like any other industry, impactful decision making starts with data sources and accessibility to the data. In higher education, some of the key data sources that are now being blended for improved school performance are:
- Student Information Systems: Contains class and grade information.
- Learning Management Systems: These applications let universities track student performance outside of the classroom, helping understand participation in online class chats with students and professors, patterns around assignment submission compared to the due date, and clickstream data that shows which department online resources and class wikis were visited and how often.
- Social Media: Comments on instructors, courses, and other students can be processed in real-time.
- Wi-Fi Data: Helps colleges understand locations and durations of stay in places such as libraries, classrooms, and student unions.
Once data from these sources and others are organized and integrated, institutions of higher education are able to impact university and student performance by solving the following key challenges:
- Discover toxic course combinations.
- Understand which programs graduate more students and the reason for those success rates.
- Proactively direct students to tutors and other support resources to help them succeed.
- Demonstrate which academic success programs actually work, and within which student segments.
- Improve diversity.
- More quickly distribute funds to colleges based on enrollment or degree production.
These are just a few ways colleges and universities are leveraging their data to ensure student success and position themselves competitively to applicants and prospective students.
The LRS Big Data and Analytics team has over 20 years of experience in analytics, information management, and data warehousing. If your university is struggling with any of the challenges above and are interested in understanding how we can help you find value in your data, please fill out the form below to request a meeting.
About the author
Steve Cavolick is a Senior Solution Architect with LRS IT Solutions. With over 20 years of experience in enterprise business analytics and information management, Steve is 100% focused on helping customers find value in their data to drive better business outcomes. Using technologies from best-of-breed vendors, he has created solutions for the retail, telco, manufacturing, distribution, financial services, gaming, and insurance industries.