27 citations · 31 across the 14 of their papers we have counts for
5 papers · 1 filter
DiVERT: Distractor Generation with Variational Errors Represented as Text for Math Multiple-choice Questions
Nigel Fernandez, Alexander Scarlatos, Wanyong Feng +2
High-quality distractors are crucial to both the assessment and pedagogical value of multiple-choice questions (MCQs), where manually crafting ones that anticipate knowledge defici…
Improving Automated Distractor Generation for Math Multiple-choice Questions with Overgenerate-and-rank
Alexander Scarlatos, Wanyong Feng, Digory Smith +2
Multiple-choice questions (MCQs) are commonly used across all levels of math education since they can be deployed and graded at a large scale. A critical component of MCQs is the d…
Math Multiple Choice Question Generation via Human-Large Language Model Collaboration
Jaewook Lee, Digory Smith, Simon Woodhead +1
Multiple choice questions (MCQs) are a popular method for evaluating students' knowledge due to their efficiency in administration and grading. Crafting high-quality math MCQs is a…
Exploring Automated Distractor Generation for Math Multiple-choice Questions via Large Language Models
Wanyong Feng, Jaewook Lee, Hunter McNichols +5
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.…
Improving the Validity of Automatically Generated Feedback via Reinforcement Learning
Alexander Scarlatos, Digory Smith, Simon Woodhead +1
Automatically generating feedback via large language models (LLMs) in intelligent tutoring systems and online learning platforms has the potential to improve the learning outcomes…