Exploring Automated Distractor Generation for Math Multiple-choice Questions via Large Language Models

arXiv:2404.02124v1 Announce Type: new
Abstract: Multiple-choice questions (MCQs) are ubiquitous in almost all levels of education since they are easy to administer, grade, and are a reliable format in assessments and practices. One of the most important aspects of MCQs is the distractors, i.e., incorrect options that are designed to target common errors or misconceptions among real students. To date, the task of crafting high-quality distractors largely remains a labor and time-intensive process for teachers and learning content designers, which …

abstract arxiv automated cs.cl easy education format language language models large language large language models math multiple practices questions type via