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20142024
most citedMathematical Language Processing: Automatic Grading and Feedback for Open Response Mathematical Questions

15 citations · 38 across the 15 of their papers we have counts for

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Showing cs.CLShow all

8 papers · 1 filter

cs.CL20242 cited

Improving Socratic Question Generation using Data Augmentation and Preference Optimization

Nischal Ashok Kumar, Andrew Lan

The Socratic method is a way of guiding students toward solving a problem independently without directly revealing the solution to the problem. Although this method has been shown…

cs.CL20241 cited

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.…

cs.CL20243 cited

Using Large Language Models for Student-Code Guided Test Case Generation in Computer Science Education

Nischal Ashok Kumar, Andrew Lan

In computer science education, test cases are an integral part of programming assignments since they can be used as assessment items to test students' programming knowledge and pro…

cs.CL2023

Modeling and Analyzing Scorer Preferences in Short-Answer Math Questions

Mengxue Zhang, Neil Heffernan, Andrew Lan

Automated scoring of student responses to open-ended questions, including short-answer questions, has great potential to scale to a large number of responses. Recent approaches for…

cs.CL2023

Interpretable Math Word Problem Solution Generation Via Step-by-step Planning

Mengxue Zhang, Zichao Wang, Zhichao Yang +2

Solutions to math word problems (MWPs) with step-by-step explanations are valuable, especially in education, to help students better comprehend problem-solving strategies. Most exi…

cs.CL2023

SmartPhone: Exploring Keyword Mnemonic with Auto-generated Verbal and Visual Cues

Jaewook Lee, Andrew Lan

In second language vocabulary learning, existing works have primarily focused on either the learning interface or scheduling personalized retrieval practices to maximize memory ret…