Join me as I chat with Ashley Kern and Erin Thompson of Sightline. We dive deep into how Colleges and Universities should be utilizing their data to pivot during and after the pandemic. Who is thriving? Who is struggling?
Analytics
Whether you are driving your car, listening to music on your iPhone, or flying across the country, materials surround you. The world needs engineers and scientists who understand materials: to make them stronger, lighter, safer, greener, and more cost-effective.
SightLine teamed up with the Association of Governing Boards (AGB) to offer a webinar on balancing enrollment
This article is part two of a two-part series to help your institution bounce back from the disruption of COVID-19.
The COVID-19 virus has completely changed life in America after just a few short weeks. Every day schedules, our shopping and eating habits, and even our interactions with friends and family have been disrupted.
As the VP of Enrollment or Director of Financial Aid, you may gain a better idea of the size and caliber of your incoming student class as the enrollment season progresses.
A hands-on approach to predictive analytics provides both the data and support for solutions.
Identifying individual students who are at-risk of dropping out is often a subjective exercise in higher education.
Predictive Analytics in a World of Choices
As higher education continues to leverage student data and make predictions as to whether students will enroll, be retained, and graduate, the inevitable question that comes up is … why do students behave the way they do?
SightLine has discovered through focused research that, on average, twice as many students leave their degrees during summer break than during winter break. Is this exodus a result of the temporal difference between the two vacations?
It’s well known that colleges struggle to retain a portion of students until graduation. Researchers and college professionals postulate a variety of reasons why students leave a four-year degree program.
