MUMBAI, India, June 22 -- Intellectual Property India has published a patent application (202621048519 A) filed by Sage University on April 16, 2026, for A System And Method For Multi-Layer Engagement-Driven Predictive Student Dropout Risk Analysis And Intervention.
Inventors include Dr Prashant Jain; Dr. Sumit Jain; Dr. Satyendra Sharma; Dr Hemang Shrivastava; and Deepak Bairagi.
The application for the patent was published on June 12, 2026, under issue no. 24/2026.
Abstract: ABSTRACT A System and Method for Multi-Layer Engagement-Driven Predictive Student Dropout Risk Analysis and Intervention A system and method for predicting student dropout risk using a multi-layer, context-adaptive, engagement-driven predictive intelligence framework is disclosed. The system acquires multi- source student engagement data from educational platforms, including activity patterns, participation behavior, assignment submissions, and interaction trends. The data is preprocessed and analyzed using multi-layer temporal analysis to identify evolving behavioral patterns across micro and macro timelines. A behavioral drift detection mechanism compares real-time engagement with personalized baseline profiles to detect early signs of disengagement. Machine learning models with context-aware data fusion generate dynamic and continuously updated dropout risk predictions. The system further provides explainable analytics by identifying key contributing factors influencing risk levels. An integrated decision-support framework generates prioritized, context-aware intervention strategies and real-time alerts. Additionally, a feedback-driven adaptive learning mechanism refines predictive models over time. The invention enables early, accurate, and proactive identification of at-risk students, improving retention outcomes and decision-making efficiency. Fig.3
Disclaimer: Curated by HT Syndication.
