Potential Student At-Risk AI Tool

Potential Student At-Risk AI Tool from Higher Colleges of Technology

The Potential Student At-Risk tool is a comprehensive predictive solution developed to support early identification of students who are potentially at-risk of underperforming, scoring low CGPA, or dropping out. The primary objective is to enable faculty and students to take corrective actions and improve academic performance early on.  

The tool uses advanced Machine Learning and AI models, leveraging historical and live data including academic and non-academic features. When a student is identified as "potentially at-risk," it signifies an increased likelihood they will fall into the "at-risk" category by the semester's end based on the data inputs, allowing for effective interventions. 

By proactively preventing students from entering the at-risk pool, the solution goal is to enhance student success and retention rates, helping them graduate successfully on time. As part of a comprehensive system, the solution is not only capable of identifying potential at-risk students, but it also aims to show the potential cause behind the classification. This early warning system allows for timely and targeted interventions tailored to individual student needs to maximise academic impact. As such, the solution is designed as a support tool for human judgment, integrating feedback loops and stakeholder engagement, rather than replacing educators' oversight. 

The application has successfully passed the proof-of-concept stage and is currently deployed, since Fall 2024. The solution is designed for high scalability, capable of covering all HCT campus locations and supporting over 25,000 students.