AI Based Automated MCQ Generator
This project aims to develop an AI-based Automated MCQ Generator that can dynamically generate multiple-choice questions from user-provided input such as text topics or uploaded study materials. The development of an AI-powered Automated MCQ Generator capable of dynamically creating multiple-choice questions based on user inputs, including uploaded study materials (PDF, DOCX, TXT files) or manually entered topics. Unlike traditional systems that depend on a pre-existing question database, our solution leverages the Gemini API to generate fresh, contextually relevant questions in real time. The system is built with a lightweight and interactive frontend (HTML, CSS, JavaScript) and a Flask-based backend that handles file processing, topic input, and API integration. All MCQs are generated on demand, eliminating the need for static storage. In-memory session management ensures efficient handling of quiz sessions, without reliance on external databases.By automating the MCQ creation process, the project significantly reduces the manual effort required by educators and offers a scalable solution for personalized and adaptive assessments. This tool is especially suited for online education platforms, teachers, and learners seeking quick, intelligent quiz generation tailored to specific learning materials or topics.
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-06-02
- DOI
- https://doi.org/10.5281/zenodo.15575105
- Primary Topic
- Gene expression and cancer classification
- Type
- article
- Field-Weighted Citation Impact
- 0.00