Learner Knowledge

Learner knowledge assessment aims to accurately determine what students know and don't know, informing personalized learning and improved educational materials. Current research focuses on automating the creation of effective assessments, including automatically generating distractors for multiple-choice questions and assembling question sets that comprehensively evaluate student understanding using algorithms like genetic algorithms and pre-trained language models. These advancements leverage large datasets of student performance to refine assessment design and improve the accuracy of knowledge estimations, ultimately leading to more efficient and effective learning experiences.