MUMBAI, India, May 29 -- Intellectual Property India has published a patent application (202621043039 A) filed by Ms. Rashmi Ingle; Dr. Sakshi Kumar; Dr. Swati Mirlekar; Dr. Surabhi Saxena; Mrs. Talamu Rajyalakshmi; Dr. Konari Rajasekhar; Mr. Mohammad Shariq Mahboob; and Rangu Rakesh, Nagpur, Maharashtra, on April 3, for 'ai-driven automated evaluation system for coding assessments in indian engineering education.'
Inventor(s) include Ms. Rashmi Ingle; Dr. Sakshi Kumar; Dr. Swati Mirlekar; Dr. Surabhi Saxena; Mrs. Talamu Rajyalakshmi; Dr. Konari Rajasekhar; Mr. Mohammad Shariq Mahboob; and Rangu Rakesh.
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: "The present invention relates to an AI-driven automated evaluation system designed to enhance the assessment of coding skills in engineering education, particularly within the Indian academic context. The system addresses the limitations of traditional manual evaluation methods, which are often time-consuming, inconsistent, and unable to provide detailed feedback for large numbers of students. By leveraging artificial intelligence and machine learning techniques, the invention enables efficient, accurate, and scalable evaluation of programming assignments. The system evaluates code submissions using a multi-layered approach that includes syntax validation, test case execution, and advanced analysis of code structure, efficiency, and adherence to programming standards. Unlike conventional assessment tools that focus primarily on output correctness, the proposed system performs deeper evaluation of logical reasoning and problem-solving strategies. It also incorporates natural language processing to interpret problem statements and assess code documentation, ensuring a more comprehensive evaluation process. A key feature of the invention is its ability to generate personalized and actionable feedback for students. This feedback highlights errors, inefficiencies, and potential improvements, supporting continuous learning and skill development. The system further includes an adaptive assessment mechanism that adjusts the difficulty level of coding tasks based on individual performance, enabling a more tailored and engaging learning experience. Designed to align with Indian engineering curricula, the system supports multiple programming languages and integrates seamlessly with existing academic frameworks. It also provides detailed analytics and performance reports for educators, facilitating data-driven teaching strategies and improved student outcomes. Additionally, built-in plagiarism detection ensures academic integrity by identifying similarities in code submissions. Overall, the invention offers a comprehensive, scalable, and intelligent solution for coding assessment, improving the quality, fairness, and effectiveness of programming education while preparing students for industry requirements."
Disclaimer: Curated by HT Syndication.
