MUMBAI, India, Aug. 10 -- Intellectual Property India has published a patent application (202641080513 A) filed by Hindusthan College Of Engineering & Technology on June 30, 2026, for Study Buddy: A Chatbot Specialized To Give Study Plan Recommendations.
Inventors include Dr. J. Jaya; Dr. R. Vidhya; Dr. D. Satheesh Kumar; V. Devi; P. Arul Selvam; K. Anu Priya; Abinithi A; Parvathy C S; and Akshit R.
The application for the patent was published on July 31, 2026, under issue no. 31/2026.
Abstract: The project StudyBuddy is an Al-based study recommendation system designed to enhance students’ learning efficiency and academic performance. Tn today’s competitive environment, students often face difficulty in planning effective study strategies due to lack of personalized guidance. StudyBuddy addresses this problem by using machine learning techniques to analyze student performance and provide customized study recommendations. The system focuses on transforming traditional learning methods into a data-driven approach. Instead of relying on generalized study plans, StudyBuddy allows students to input their previous exam scores and pass/fail status. Based on this information, the system predicts the optimal number of study hours required for improvement. This helps students understand how much effort is needed and enables better time management. The proposed system incorporates a trained Random Forest machine learning model that processes the input data and generates accurate predictions. These predictions are further converted into actionable suggestions through a recommendation module. The system categorizes students into performance levels such as low, moderate, and high, and provides appropriate guidance like focusing on weak areas, increasing study time, practicing regularly, and maintaining consistency. To enhance user interaction, the system includes an intuitive and interactive dashboard with a chat-based interface. This chatbot-style assistant makes the system easy to use and allows students to receive recommendations in a conversational manner. The interface is designed to be simple, responsive, and user-friendly, ensuring accessibility for all users. Unlike traditional systems that provide only study materials or recorded content, StudyBuddy emphasizes personalized learning and intelligent guidance. It helps students move away from trial-and-error methods and adopt structured study plans based on data analysis. The system also encourages active learning by promoting regular practice, revision, and performance tracking. Overall, StudyBuddy contributes to the development of smart education systems by integrating artificial intelligence into learning. It improves productivity, reduces confusion in study planning, and supports students in achieving better academic outcomes. With further enhancements, such as adding more performance factors and expanding features, the system has the potential to become a comprehensive digital learning a^§istant for students.
Disclaimer: Curated by HT Syndication.
