2026-05-05T01:43:17.159Z http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai

ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai:1:11661 2025-10-27T16:06:34Z 1

AI-Powered Quiz Generation for Learning Management Systems: A Full-Stack Implementation for Canvas LMS 2025 http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai/record/1/11661 https://ceur-ws.org/Vol-4076/short3.pdf F. Imad Ali T. Emad Ali W. Aljamal P. Dakić A. Dhulfiqar Zoltan In modern education, the manual creation of exam questions remains a time-consuming task that limits instructional productivity. This study aims to automate the generation of quizzes and exams by integrating advanced natural language processing techniques with Learning Management Systems, specifically Canvas. The scope of the project encompasses the development of a scalable, full-stack web application that streamlines assessment design for educators. Methodologically, the system leverages OpenAI’s GPT API in conjunction with PyPDF2 for course material parsing, diverging from LangChain to ensure efficient and accurate content extraction. The application features a Python-based Flask back-end for question generation and a JavaScript/HyperText Markup Language/Cascading Style Sheets front-end for user interaction and Learning Management Systems integration. The outcomes show that our developed tool efficiently produces pedagogically sound and contextually relevant questions, greatly minimizing the manual labor required of teachers. Next, the easy-to-use interface enables teachers to effortlessly manage resources, examine generated questions, and alter quiz parameters in a modern and contemporary manner. By automating the generation of assessments, providing wide applicability across educational contexts, and being adaptable to future learning management system (LMS) platforms, the suggested method improves educational efficiency. conferenceObject https://ceur-ws.org/Vol-4076/short3.pdf https://ceur-ws.org/Vol-4076/short3.pdf