The South African Higher Education is facing a lot of challenges with maximizing the revenue to students taking longer to graduate and high drop out rates. Many institutions today, decision leaders are often left to make financial decisions in the dark without proper systems in place.Higher education finance is often viewed as a “black box,” with revenue generation, spending, and the monitoring of student outcomes often taking place separately from each other. This paper proposes an intelligent system using machine learning technologies to predict completion in minimum time and retention of students. We then calculate the subsidies based on the system and advise planning officers and decision makers.
Higher Education User GroupMesa, AZ 85212 United States
support@heug.org
M-F 8 AM to 5 PM MST
Join HEUG
Community Council
Interest Areas
Resources
Alliance Conference
Global Meetings
Online Webinars
Code of Conduct
Privacy Policy
Terms of Service
HEUG Code of Conduct
Copyright 2026 Higher Education User Group, Inc.
Copyright © 2026 Higher Education User Group, Inc.