Lecture Summarizer and Quiz Generator: A Comprehensive Survey

Abstract

The rapid growth of online education has created a demand for intelligent tools that enhance learning efficiency, engagement, and personalization. This survey paper consolidates research on two key AI-driven educational technologies: lecture summarization and quiz generation. We analyze methodologies, tools, and evaluation metrics from multiple recent studies, including EDUZONE, IFSE, Jotter, and Video-Based Transcript Summarizer. Lecture summarization techniques are explored through extractive and abstractive approaches, video indexing, note generation, and hybrid models. Quiz generation is examined through ontology-based personalized systems, intelligent feedback mechanisms, and integration with learning management systems. The paper highlights the convergence of Natural Language Processing (NLP), computer vision, speech recognition, and semantic modeling in creating adaptive and scalable educational assistants. We discuss performance metrics, practical implementations, limitations, and future research directions, providing a holistic view of current advancements and opportunities in AI-enhanced education.