Educational Question Generation

Educational question generation (EQG) focuses on automatically creating pedagogically sound questions from educational materials, aiming to improve efficiency and scalability in education. Current research heavily utilizes large language models (LLMs), often fine-tuned on scientific or educational datasets, to generate questions at various cognitive levels as defined by Bloom's taxonomy, with a focus on improving controllability and question quality through techniques like advanced prompting and keyword provision. This field is significant because it promises to automate a time-consuming task for educators, potentially personalizing learning experiences and enabling large-scale assessment in online education.