Learnersourcing System

Learnersourcing systems leverage student-generated educational content to enhance learning, aiming to create scalable and personalized learning experiences. Current research focuses on improving the quality and utility of this content through AI-powered methods, such as using large language models (LLMs) to enhance question explanations and neural networks to predict student performance and automatically assess question quality. These advancements address challenges like inconsistent content quality and inefficient content creation, ultimately promising to improve the effectiveness and efficiency of educational platforms.