PREDICT-C: Predictive Analytics for Early Support of At-Risk GEM Computing Students

This project will develop and pilot a predictive analytics model to identify Computing students from Global Ethnic Majority (GEM) backgrounds who are at risk of academic underperformance. Using three years of institutional data, the project will build a transparent early warning system to flag students based on engagement, attendance, and performance trends. Co-created with students and advisors, the tool will inform timely, targeted interventions that enhance continuation, progression, and attainment. By combining data science and inclusive pedagogic practice, this initiative supports the university’s Access and Participation Plan and reduces awarding disparities in a sustainable, scalable way.