Harnessing Artificial Intelligence to Predict Timely Degree Progression through Self-Efficacy Profiling

This study investigates the predictive relationship between academic self-efficacy and timely degree progression among Arab university students in the UAE.Using binary logistic regression on data from 1,420 students, results show modest predictive value and highlight cultural variables influencing academic timelines.The findings underscore the need for AI-enhanced, context-sensitive student support systems.This research contributes to educational policy and practice by aligning predictive analytics with equity-focused retention strategies.