Design and implementation of an application for the automated generation of quiz questions using the OpenAI API

This bachelor's thesis addresses the problem of time-consuming manual creation of quiz questions through the design and implementation of the NexusQuiz AI web application, which automatically generates high-quality and relevant questions from text sources using the OpenAI API. We built the app using the MMSP methodology. This involved looking at other tools, designing the application's structure, building the application using Vue.js and Supabase, and carefully crafting prompts for the OpenAI API using prompt engineering. We then checked how good the questions were using both data-driven tests and expert opinions, which confirmed their high semantic relevance, good comprehensibility, and the factual correctness of most questions, with an expert also viewing them pedagogically suitable. The outcome of NexusQuiz AI is a working, easy-to-use platform that's proven to generate meaningful and clear quiz questions of different types and difficulties, perfect for learning. So, NexusQuiz AI is a helpful tool for teachers and content makers. It makes preparing tests easier, shows what modern AI can do for education, and has clear paths for future improvements.