Analytics for EductionIntelliSift addresses the challenge of attracting and retaining students
Entering a College or University is a vulnerable period for students. The non-continuation rate for academic institutions is a challenge, however the first semester becomes busy with on boarding of students. Academic staff may have less time to identify and assist students in need of support. Each student exiting is a loss, for both the student and the institution. There is a loss of potential funding as well as tuition revenue.
IntelliSift’s Student Retention Module uses Machine Learning to predict students at risk, at the beginning and throughout the academic year. This allows staff to focus on students requiring help and advice, ensuring a successful outcome to their academic journey.
- Define retention issues, goals and objectives
- Analysis of historic student data
- Report on outcome and potential ROI, suitability of data for Machine Learning
- All Starter Deliverables
- Student Retention Dashboard showing number of students at risk, the loss in revenue, breakdown by department school and course. Drill down to list of students requiring support