MUMBAI, India, May 29 -- Intellectual Property India has published a patent application (202641043718 A) filed by Hlndusthan College Of Engineeering And Technology, Coimbatore, Tamil Nadu, on April 6, for 'al based personalized learning path and adaptive assessment system with department wise learning analytics.'
Inventor(s) include S. Nivetha; S. Shankar; N. J. R. Muniraj; D. Loganathan; T. K. P. Rajagopa; M. Mohanasundaram; B. Reena; S. Aravind; S. Dhanush; V. Harisi-Ikuma, N. S.; and Jyothis.
The application for the patent was published on May 29, under issue no. 22/2026.
According to the abstract released by the Intellectual Property India: "This invention presents a low-power, scalable, and intelligent AI-Based Personalized Learning Path and Adaptive Assessment System designed as a full-stack web platform for smart education environments. The system operates in real-time, leveraging a hybrid intelligence framework that combines Machine Learning, Deep Learning, and Data Analytics to deliver personalized learning experiences and dynamic assessment capabilities. The system utilizes a multi-layer adaptive cngmc compnsmg: Student Profiling + Personalized Learning Path Generation+ Adaptive Assessment Module+ Predictive Analytics for early dropout detection. It is implemented using a modern web architecture with a Pythonbased backend, interactive frontend interface, and integrated database system for efficient data handling and analytics. The complete development-to-deployment pipeline includes: * Data collection and preprocessing of student academic and behavioral data. * Feature extraction and model training using machine learning algorithms. * Integration of adaptive learning and assessment modules. * Deployment of a real-time analytics dashboard tor educators and administrators. The proposed system achieves improved learning efficiency, enhanced student engagement, and accurate performance prediction. Experimental results demonstrate significant improvement over traditional learning systems, with better adaptability and personalized content delivery. The final outcomes include: * Real-time adaptive learning and assessment system * Improved student engagement and performance tracking * Early prediction of at-risk students for timely intervention * Integrated system with multiple intelligent modules The invention is applicable to higher education institutions, online learning platforms, smart classrooms, and large-scale digital education systems requiring personalized and datadriven learning solutions."
Disclaimer: Curated by HT Syndication.
