Question Generation Using Artificial Intelligence and Knowledge Augmented Generation

Abstract - This project introduces an innovative, AI-driven platform tailored to streamline and enhance the process of question paper generation for educators at various academic levels. Utilizing cutting-edge technologies such as Natural Language Processing (NLP), Knowledge-Augmented Generation (KAG), and Large Language Models (LLMs), the system is capable of understanding and extracting key concepts from a variety of educational resources. These include user-uploaded materials such as textbooks, existing question banks, lecture notes, and previous year exam papers. Educators are provided with a user-friendly interface where they can define specific parameters, including subject area, topic coverage, question complexity (difficulty level), and the desired number of questions. Based on these inputs, the platform intelligently generates a diverse and balanced set of questions, ensuring coverage across cognitive levels—such as knowledge recall, application, and analysis. Additionally, each question is accompanied by a corresponding answer key, which helps educators expedite the evaluation process. Keywords - Automated Question Paper Generation, NLP-Based Assessment Design Tool, AI-Powered Educational Assessment System.