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20242026
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cs.CL2026

Misconception Diagnosis From Student-Tutor Dialogue: Generate, Retrieve, Rerank

Joshua Mitton, Prarthana Bhattacharyya, Digory Smith +3

Timely and accurate identification of student misconceptions is key to improving learning outcomes and pre-empting the compounding of student errors. However, this task is highly d…

cs.CL2025

PIIvot: A Lightweight NLP Anonymization Framework for Question-Anchored Tutoring Dialogues

Matthew Zent, Digory Smith, Simon Woodhead

Personally identifiable information (PII) anonymization is a high-stakes task that poses a barrier to many open-science data sharing initiatives. While PII identification has made…

cs.CL2024

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…

cs.CL2024

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…

cs.CL2024

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.…