Quiz.ai
This is a smart Quiz Generator that generates a dynamic quiz from any uploaded text/PDF document using NLP. This can be used for self-analysis, question paper generation, and evaluation, thus reducing human effort.
Features
- implements automatic question generation (AQG) techniques
Automatic question generation (AQG) is concerned with the construction of algorithms for producing questions from knowledge sources, which can be either structured (e.g. knowledge bases (KBs) or unstructured (e.g. text))
- helps in resource saving(time, money and human effort)
- enables the enrichment of the teaching process, adapt learning to student knowledge and needs, as well as drill and practice exercises
- presents an automatic mechanism to assemble exams or to adaptively select questions from a question bank.
Theme
The theme of our project idea is Security and Productivity. We are reducing the manual efforts and thus increasing the productivity of the teachers. This will help in removing the Distraction of Questions making and reducing the labor to go through the text to generate questions thereby helping the teachers to focus on other necessary things.
Quiz.ai also fits into the current online education scenario where most of the classes take place over online platforms like Google Meet and Zoom. We help students with quick MCQs that help them to revise and memorize the concepts better.
WorkFlow
Flowchart
Simplified UserFlow
Technology Stack:
- Frontend: HTML, CSS, Vanilla JS
- Backend: Flask
- IDE: VS Code
- Design: Illustrator, Figma, Zeplin, Framer
- Version Control: Git and GitHub
- Database: Firebase
How to Get Started?
Setup
- Fork and Clone the repo using
$ git clone https://github.com/geekquad/quiz.ai.git
$ cd quiz.ai
- Setup Virtual environment
$ python3 -m venv env
- Activate the virtual environment
$ source env/bin/activate
- Install dependencies using
$ pip install -r requirements.txt
- Run Flask server using
$ python app.py
Browser Support
- Firefox: version 4 and up
- Chrome: any version
- Safari: version 5.2 and up
- Internet Explorer/Edge: version 8 and up
- Opera: version 9 and up
Note: Support for modern mobile browsers is experimental. The website is not responsive in mobile devices until now.
Cite This Article
"An Encrypted Automatic Multiple-Choice Question Generator for Self-Assessment Using Natural Language Processing",
International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved),
ISSN:2349-5162, Vol.9, Issue 5, page no. ppj337-j343, May-2022,
Available at : http://www.jetir.org/papers/JETIR2205A45.pdf
Team:
| S.No. | Name | Role | GitHub Username |
|---|---|---|---|
| 1. | Arpita Verma | Full Stack Developer | @ArpitaV13 |
| 2. | Aditya Kumar Gupta | ML | @geekquad |
| 3. | Devansh Chaudhary | UI/UX | @rex12543 |
Contributors ✨
Thanks goes to these wonderful people (emoji key):
 Aditya Kumar Gupta 💻 🖋 |
 Arpita Verma 💻 🖋 |
 Devansh Chaudhary 💻 🖋 |
This project follows the all-contributors specification. Contributions of any kind welcome!
