University of Kalba Launches AI-Powered Early Warning System to Support Student Success

Kalba, Sharjah, UAE – October 2026

The University of Kalba (UKB) has taken a major step in its AI transformation journey with the launch of the Student Success Early Warning System, an intelligent platform that predicts which students may be at academic risk before their GPA falls below the 2.0 threshold.

The system uses machine learning models trained on UKB’s historical student data, learning the patterns that typically came before academic difficulty. It analyses each student’s GPA trajectory, credit progress, and course performance, together with attendance and absence records, which are key factors in placing students on academic probation. Based on this, it estimates each student’s level of risk and highlights the main reasons behind it.

Students are placed in one of four color-coded levels. Green indicates students who are on track and progressing well with no warning signs. Yellow is an early warning, signaling early concerns such as declining grades, rising absences, or missed coursework. Orange identifies students who are likely to be at risk and are predicted to fall below a 2.0 GPA or into probation if current trends continue. Red marks students whose GPA is already below 2.0 or who are on probation, and who require intensive support and a recovery plan.

By identifying warning signs early, the university can reach students while there is still time to change the outcome through advising, tutoring, and support services, helping them avoid probation and stay on the path to graduation.

The system is currently being piloted as an AI-powered assistant for academic advising in the College of Computing and Intelligent Systems and the College of Sport Science. It supports, rather than replaces, human judgment by providing academic advisors with clear, data-driven insights that enable them to identify and support students who need assistance the most. The results of this pilot phase will inform its future expansion across the University.

Developed entirely in-house by UKB faculty members, the system showcases the exceptional expertise, innovative capabilities, and technical proficiency of the University's academic community. This achievement demonstrates UKB's capacity to develop practical, homegrown AI solutions, translating faculty expertise into meaningful innovations that enhance student success.