MUMBAI, India, Aug. 24 -- Intellectual Property India has published a patent application (202641098324 A) filed by Anurag University on August 14, 2026, for System And Method For Early Identification Of Academically At-Risk Engineering Students Using Multi Source Academic Performance Analytics And Machine Learning.
Inventors include Dr. N Suresh Rao; Mrs. Jampa Sakunthala Devi; Dr. A. Radha Krishna; Mrs. L. Yamuna; Mrs. Kakanaboina Sarvani; Mrs. Meneni Mounika; and Dr. B. Srinivasulu.
The application for the patent was published on August 21, 2026, under issue no. 34/2026.
Abstract: The present invention relates to a computer-implemented system and method for the early identification of academically at risk engineering students using multi-source academic performance analytics and machine learning-based predictive analytics. The system collects academic data including attendance, internal assessment marks, assignment scores, laboratory performance, semester examination results, previous academic records, and other educational parameters from institutional databases. The collected data are preprocessed and analyzed using one or more machine learning models to identify academic risk factors and generate a composite academic risk score. Based on the generated score, students are classified into predefined risk categories, including low, moderate, and high risk. A web-based faculty decision- support dashboard presents the predicted risk level, contributing factors, performance trends, and recommended intervention measures to facilitate timely academic counseling and monitoring. The predictive model is periodically updated using newly available academic data to improve prediction accuracy. The invention enables educational institutions to implement proactive academic support, enhance student retention, improve academic performance, and facilitate data-driven decision- making.
Disclaimer: Curated by HT Syndication.
