MUMBAI, India, Oct. 5 -- Intellectual Property India has published a patent application (202641114735 A) filed by Dr. V. Anitha; Dr. Raja Sekhar Koduru; Dr. Pokanati Veera Venkata Rama Rao; Dr. V. Subramanyam; Mr. Sudhakar Chilaka; Mr. Jonnalagadda Prasad; Dr. Sudha Paipuru; and Dr. Ramesh Bhavisetti on September 24, 2026, for An Artificial Intelligence-Based System And Method For Cognitive-Emotional State Aware Personalized Education And Learning Intervention.
Inventors include Dr. V. Anitha; Dr. Raja Sekhar Koduru; Dr. Pokanati Veera Venkata Rama Rao; Dr. V. Subramanyam; Mr. Sudhakar Chilaka; Mr. Jonnalagadda Prasad; Dr. Sudha Paipuru; and Dr. Ramesh Bhavisetti.
The application for the patent was published on October 02, 2026, under issue no. 40/2026.
Abstract: ABSTRACT: Title: An Artificial Intelligence-Based System and Method for Cognitive-Emotional State Aware Personalized Education and Learning Intervention The present invention provides an artificial intelligence-based system and method for dynamically personalizing education according to a learner's cognitive and emotional state. The system acquires multimodal learner data comprising assessment performance, response behavior, interaction patterns, textual or speech inputs, visual or physiological indicators, learning history, and contextual information. The acquired data is preprocessed, synchronized, and transformed into features for estimating cognitive parameters and emotional parameters. A multimodal fusion engine combines the estimated states with learner performance and historical information to generate a dynamic learner-state representation. An intervention decision engine selects or generates personalized educational content, learning activities, assessment difficulty, explanations, hints, pacing, or reinforcement according to the learner-state representation. Post-intervention learner responses are monitored and evaluated to determine intervention effectiveness. The resulting feedback updates learner-state and personalization parameters, thereby providing a closed-loop adaptive learning system.
Disclaimer: Curated by HT Syndication.
