A hands-on approach to predictive analytics provides both the data and support for solutions.
Following up with our previous post, Six Steps to At-Risk Student Intervention: A University Case Study, found improved student retention post university int
Performance based scholarships aim to reduce reliance on loans and provide incentives for academic success. This is particularly true for students identified as at-risk of dropping out. There are a variety of risk factors specific to each student and institution.
Identifying individual students who are at-risk of dropping out is often a subjective exercise in higher education.
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?
They invent, design, code, create, and collaborate.
Finances play a significant role in student success, which we define as degree completion and skills mastery. Students need to feel secure in their ability to pay tuition in order to focus on the meat and potatoes of college life: academics and extracurriculars.
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?
Many universities have significant budgets available for student employment. At SightLine, we view these resources as a great opportunity to engage with the students at your University and promote student success.
This past week, the SightLine team presented at the Student Affairs Administrators in Higher Education (NASPA) joint conferences; Closing the Achievement Gap: Student Success in Higher Education Conference and the
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.