Quiz Master AI: An Interactive Machine Learning-Based Quiz Generator
Quiz Master AI is an innovative machine learning-based application designed to create an interactive and engaging platform for quiz-based learning. The primary goal of the project is to develop a system that generates multiple-choice questions (MCQs) from user-provided content and allows users to participate in quizzes, enhancing their learning experience. Participants can level up based on their performance, fostering a competitive and collaborative environment for knowledge acquisition. In Quiz Master AI, users can form groups with a designated group author who provides a paragraph or passage as input. This input is processed by a machine learning model trained to extract key information, identify important concepts, and generate contextually accurate and diverse multiple-choice questions. The goal is to test the comprehension and retention of the paragraph's content, making the learning process more interactive and effective. Once the questions are generated, the group members take the quiz, answering the MCQs based on their understanding of the input passage. After the quiz is completed, participants are scored, and each individual's performance determines their progression through different levels. This "level-up" system is designed to motivate users by rewarding them for their learning achievements and providing a sense of accomplishment as they improve. Quiz Master AI leverages natural language processing (NLP) techniques to ensure the questions are relevant, unambiguous, and educational. The model can handle a wide range of content topics, making it suitable for various educational purposes, from school subjects to professional training. Additionally, the platform's gamified approach encourages healthy competition and collaboration among users, making learning both fun and productive.
Institutions
- Sant Gadge Baba Amravati University (IN)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2024-11-23
- DOI
- https://doi.org/10.5281/zenodo.14208813
- Primary Topic
- Intelligent Tutoring Systems and Adaptive Learning
- Type
- article
- Field-Weighted Citation Impact
- 0.00