MUMBAI, India, July 13 -- Intellectual Property India has published a patent application (202641084265 A) filed by Dr. P. Vasuki; Dr. Stephen Raj S; Smita Nitin Deshpande; Dr. Rashmi Patil; N Viswanadhareddy; and Dr. R. Senthamil Selvan on July 09, 2026, for Machine Learning Based Personalized Learning Recommendation System For Digital Education Platforms.
Inventors include Dr. P. Vasuki; Dr. Stephen Raj S; Smita Nitin Deshpande; Dr. Rashmi Patil; N Viswanadhareddy; and Dr. R. Senthamil Selvan.
The application for the patent was published on July 10, 2026, under issue no. 28/2026.
Abstract: The present invention relates to a machine learning based personalized learning recommendation system for digital education platforms that intelligently generates adaptive learning recommendations by analyzing multidimensional learner data and educational content characteristics. The system comprises a learner data acquisition module, a data preprocessing module, a feature engineering module, a learner profile generation engine, a machine learning prediction engine, a recommendation ranking engine, a learning path optimization module, a feedback collection module, and a continuous model training engine. The system collects learner interactions, assessment results, behavioral patterns, engagement metrics, and content utilization information to construct individualized learner profiles and predict competency levels, knowledge gaps, and learning outcomes using one or more trained machine learning models. Personalized educational resources and adaptive learning pathways are dynamically generated and continuously refined through learner feedback and incremental model updates, thereby improving recommendation accuracy, learner engagement, knowledge retention, educational performance, and scalability across diverse digital education platforms.
Disclaimer: Curated by HT Syndication.
