To develop a solution that enables universities and educational coaching institutes to generate a question bank from any uploaded content, such as textbooks, class notes, or research papers, using generative AI models.
Creating question papers manually has been a longstanding challenge for educators, examination boards, and coaching institutes. The traditional approach is often riddled with inefficiencies, inconsistencies, and limitations, which impact the learning and assessment experience. Some of the key issues include
Introduce new attributes for questions, assessing not just difficulty but also cognitive and emotional complexity to ensure holistic student evaluation.
Enable coding assignments and practical problem-solving questions for STEM subjects to encourage applied learning rather than rote memorization.
Upload previous years’ question papers to analyze patterns, question distributions, and topic coverage, allowing educators to refine question sets over time.
Enable users to specify particular topics for targeted question creation, ensuring better alignment with specific subjects, modules, or learning objectives.
This AI-powered question bank generation system is a groundbreaking innovation in the field of education. By leveraging advanced AI models, the system provides an efficient and scalable solution for educational institutions to create structured, high-quality question sets. The automation not only ensures accuracy, flexibility, and adherence to pedagogical standards but also drastically reduces manual effort, saving hours of work and minimizing human errors while improving exam consistency. The ability to scale, adapt, and evolve with future enhancements makes this system a critical tool for modern educational needs. By eliminating traditional inefficiencies and providing a robust, AI-driven approach to assessment creation, this system will redefine how educators generate and manage exam content, contributing to a more effective and streamlined educational ecosystem.