EduQGen: AI - Based Question paper Generation System

In the evolving landscape of education, the traditional process of manually creating question papers is often time-consuming, prone to bias, and lacks adaptability. This project, titled EduQGen: AI-Based Question Paper Generation System, proposes an intelligent solution to automate and optimize question paper creation using artificial intelligence and natural language processing (NLP). The system enables dynamic generation of question papers based on user-defined parameters such as subject, difficulty level, question type, and Bloom’s Taxonomy levels. EduQGen extracts questions from a curated database and applies machine learning algorithms to classify, rank, and assemble them into balanced papers. The system ensures uniqueness, coverage of syllabus, and adherence to examination guidelines. Additionally, the interface allows educators to review, regenerate, or edit questions as per academic needs. The implementation uses Python, NLP libraries, and a modular database structure to store categorized questions. Testing and evaluations indicate that EduQGen significantly reduces manual effort, maintains paper quality, and adapts to various academic frameworks.