INTELLIGENT ASSESSMENT SYSTEM: AUTOMATIC QUIZ GENERATION FROM LECTURE NOTES USING NLP TECHNIQUES

The Intelligent Assessment System: Automatic Quiz Generation from Lecture Notes Using NLP Techniques is a mobile-based application designed to automate the creation of multiple-choice quizzes from students’ lecture notes. This study addressed the challenges associated with manual quiz preparation by providing an efficient, accurate, and adaptive tool that enhances teaching and learning outcomes while also making education more engaging. Specifically, the objectives included preprocessing lecture notes, extracting key concepts, and automatically generating relevant assessment questions. The methodology followed a design and implementation framework, with the system developed using Flutter for the frontend and a Flask-powered backend. An NLP engine, incorporating libraries such as NLTK, spaCy, and Transformers, was integrated to perform text preprocessing, keyword extraction, and question generation. The system architecture also leveraged AI models to ensure semantic relevance and contextual accuracy of the generated quizzes. Testing and evaluation demonstrated that the application effectively generated accurate and meaningful quizzes, tracked user performance, and provided a user- friendly interface that enhanced student interactivity and self-assessment. The system reduced instructor workload and promoted active learning by dynamically deriving quizzes directly from lecture materials. Based on these findings, the study affirms that the Intelligent Assessment System demonstrates the potential of AI in strengthening educational tools by automating quiz generation, improving learner engagement, and supporting digitally driven education. Recommendations for future enhancement include the integration of multimedia content, adaptive difficulty levels, and compatibility with learning management systems to ensure broader applicability across diverse academic environments.