QURIO: A Real-Time Multiplayer Quiz Battle Platform for Competitive Exam Preparation

In this paper, the design, development, and implementation of an adaptive multiplayer quiz software for the better preparation of students in competitive exams are discussed. Unlike the traditional static quiz websites, the software will dynamically change the difficulty level of the questions depending on the performance, learning patterns, and initial diagnosis test results of the user. After registration, the software will require the user to respond to a series of profiling questions, the answers to which will help the software provide the user with questions tailored specifically to their level of knowledge. There will also be a progressive learning component, where the user will be able to achieve awards for continuous learning by completing a series of escalated difficulty questions. Additionally, the software can be used in multiplayer mode, either two players or four players, with a smart matching algorithm that will help the software automatically pair players of equal skills, ensuring healthy competition. To make learning easier, an integrated chat bot has been included using Google API, giving immediate solutions for incorrect answers and additionally enabling the user to ask subsequent questions. Also, it has been made possible for the user to create more than one profile if they want to prepare for more than one competitive exam. The results confirm that by combining adaptive learning, matchmaking, and AI support in one system, there can be improved performance and motivation for learning.