MUMBAI, India, Sept. 22 -- Intellectual Property India has published a patent application (202621092002 A) filed by Shilpa Suresh Newale; and Mr. Nagnath Basanna Aherwadi on July 29, 2026, for Ai-Based Personalized Learning System Using Adaptive Weighted Probabilistic Optimization For Mathematics Education.
Inventors include Shilpa Suresh Newale; and Mr. Nagnath Basanna Aherwadi.
The application for the patent was published on September 18, 2026, under issue no. 38/2026.
Abstract: This invention presents an intelligent, AI-driven personalized learning system which aimed at improving the way mathematics is taught and learned. Instead of using a one-size-fits-all approach, the system continuously observes how each student performs while solving problems and understanding concepts. Based on this, it builds a dynamic understanding of the student’s knowledge level using probabilistic models. The system does not just track correct or incorrect answers—it also considers how learning changes over time. By incorporating a time-decay factor, it accounts for the natural tendency of students to forget concepts if they are not revised regularly. This allows the system to identify when a student needs reinforcement of previously learned topics. In addition, the system uses a multi-objective optimization strategy to carefully select the most appropriate learning content for each student. It balances multiple factors such as difficulty level, learning progress, retention, and engagement to recommend questions or topics that are neither too easy nor too difficult. As a result, the learning experience becomes more efficient, personalized, and engaging. Students receive the right content at the right time, which helps them build a stronger understanding of mathematics, stay motivated, and ultimately achieve better academic performance.
Disclaimer: Curated by HT Syndication.
