MUMBAI, India, June 26 -- Intellectual Property India has published a patent application (202621051824 A) filed by Symbiosis International Deemed University on April 23, 2026, for Machine Learning Based System And Method For Predicting Student Dropout In Educational Institutions.
Inventors include Vedant Shrirao; Parth Satokar; Dr. Monali Gulhane; and Dr. Nitin Rakesh.
The application for the patent was published on June 19, 2026, under issue no. 25/2026.
Abstract: ABSTRACT MACHINE LEARNING BASED SYSTEM AND METHOD FOR PREDICTING STUDENT DROPOUT IN EDUCATIONAL INSTITUTIONS The present invention relates to a machine learning based system (100) and method for predicting student dropout in educational institutions. The system comprises a data acquisition module (110) for collecting student demographic, academic, and socio-economic data, a data preprocessing unit (120) for cleaning and normalizing the collected data, a feature extraction module (130) for identifying relevant predictive variables using correlation analysis, a machine learning prediction engine (140) implementing multiple classification algorithms including Random Forest, Neural Networks, Logistic Regression, and Decision Tree classifiers, and a risk assessment interface (150) for generating dropout probability scores and early warning alerts. The system processes student records containing variables including marital status, application mode, course enrollment, attendance patterns, previous qualifications, parental education levels, scholarship status, gender, and age at enrollment to generate accurate dropout predictions enabling timely interventions by educational administrators. [
Disclaimer: Curated by HT Syndication.
