6 citations · 11 across the 9 of their papers we have counts for
10 papers
Principal Trait Analysis: Towards Deriving "Skills" in Human-AI Collaboration
Hunter McNichols, Kai Du, Andrew Lan
Large Language Model-powered agents are increasingly used in the workplace via human-artificial intelligence (AI) collaboration. In this new era of work, it is important to underst…
Gumbel Machine: Counterfactual Student Writing Generation via Gumbel Noise Steering
Hunter McNichols, Alexander Scarlatos, Mihai Dascalu +2
An effective method of teaching across disciplines is to provide examples of high-quality work. However, an example may be significantly different from a student's current work, ma…
A Multi-Agent Approach to Validate and Refine LLM-Generated Personalized Math Problems
Fareya Ikram, Nischal Ashok Kumar, Junyang Lu +4
Students benefit from math problems contextualized to their interests. Large language models (LLMs) offer promise for efficient personalization at scale. However, LLM-generated per…
The StudyChat Dataset: Analyzing Student Dialogues With ChatGPT in an Artificial Intelligence Course
Hunter McNichols, Fareya Ikram, Andrew Lan
The widespread availability of large language models (LLMs), such as ChatGPT, has significantly impacted education, raising both opportunities and challenges. Students can frequent…
Exploring Automated Keyword Mnemonics Generation with Large Language Models via Overgenerate-and-Rank
Jaewook Lee, Hunter McNichols, Andrew Lan
In this paper, we study an under-explored area of language and vocabulary learning: keyword mnemonics, a technique for memorizing vocabulary through memorable associations with a t…
Can Large Language Models Replicate ITS Feedback on Open-Ended Math Questions?
Hunter McNichols, Jaewook Lee, Stephen Fancsali +2
Intelligent Tutoring Systems (ITSs) often contain an automated feedback component, which provides a predefined feedback message to students when they detect a predefined error. To…
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.…
Automated Distractor and Feedback Generation for Math Multiple-choice Questions via In-context Learning
Hunter McNichols, Wanyong Feng, Jaewook Lee +4
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. An important aspe…
Algebra Error Classification with Large Language Models
Hunter McNichols, Mengxue Zhang, Andrew Lan
Automated feedback as students answer open-ended math questions has significant potential in improving learning outcomes at large scale. A key part of automated feedback systems is…
A Conceptual Model for End-to-End Causal Discovery in Knowledge Tracing
Nischal Ashok Kumar, Wanyong Feng, Jaewook Lee +3
In this paper, we take a preliminary step towards solving the problem of causal discovery in knowledge tracing, i.e., finding the underlying causal relationship among different ski…