MUMBAI, India, Jan. 2 -- Intellectual Property India has published a patent application (202541122479 A) filed by Malla Reddy (MR) Deemed to be University; Malla Reddy College Of Engineering And Technology; Malla Reddy Vishwavidyapeeth; Malla Reddy University; and Malla Reddy Engineering College For Women, Malkajgiri, Telangana, on Dec. 5, 2025, for 'cognitive ai tutor for adaptive stem learning experiences.'
Inventor(s) include Dr. Syed Umar; Mr. N. Vishal; Laiphangbam Melinda; Mr. Chekuri Mahesh; Dr. M. Ravi Kanth; and Dr. Geetha Reddy Yenna.
The application for the patent was published on Jan. 2, under issue no. 01/2026.
According to the abstract released by the Intellectual Property India: "The development that can provide science, technology, engineering and mathematics (STEM) learning with adaptive and individualized learning experience is known as cognitive artificial intelligence tutor. The system takes in the cognitive modeling, behavioral analytics and neural-based adaptive reasoning to examine the work of the learner, detect the gap of concepts and update the sort of teaching in real-time. It is a simulator of the human tutor by integrating pattern recognition of neural networks with cognitive rules based interpretation to bring learners through the simplest to the most complex concepts. The architecture involves a learner profiling engine which operates to keep on tracking the engagement, understanding and correct response. The results of these observations are inputted into adaptive inference module that seals appropriate learning pathways, levels of feedback and contents of the instruction transformed to the cognitive state of the learner. The signal of reinforcement turns the model to be dynamically adjusted therefore maintained long term and it is easily understood. Multimodal interaction layer can facilitate text and voice communication and offer better access and interaction. The framework supports various styles of learning and levels of complication and allows the personalization of the learning in the context of academic standards. The evaluations indicate increased motivation of learners, enhanced acquisition of concepts and increased sustained performance improvement in comparison to non-dynamic e-learning systems. The system can be used as a scalable basis for intelligent tutoring system at educational institutions, online systems, and in individual learning environments."
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