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Found 5 papers, 2 papers with code
Math Multiple Choice Question Generation via Human-Large Language Model Collaboration
We conduct a pilot study involving math educators to investigate how the tool can help them simplify the process of crafting high-quality math MCQs.
Exploring Automated Distractor Generation for Math Multiple-choice Questions via Large Language Models
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
Second, we propose a framework for feedback generation that optimizes both correctness and alignment using reinforcement learning (RL).
Automated Distractor and Feedback Generation for Math Multiple-choice Questions via In-context Learning
Multiple-choice questions (MCQs) are ubiquitous in almost all levels of education since they are easy to administer, grade, and are a reliable form of assessment.
NeurIPS Competition Instructions and Guide: Causal Insights for Learning Paths in Education
In this competition, participants will address two fundamental causal challenges in machine learning in the context of education using time-series data.
