59 citations · 167 across the 33 of their papers we have counts for
8 papers · 1 filter
Leveraging Large Language Models for Identifying Knowledge Components
Canwen Wang, Jionghao Lin, Kenneth R. Koedinger
Knowledge Components (KCs) are foundational to adaptive learning systems, but their manual identification by domain experts is a significant bottleneck. While Large Language Models…
Leveraging LLMs to Assess Tutor Moves in Real-Life Dialogues: A Feasibility Study
Danielle R. Thomas, Conrad Borchers, Jionghao Lin +6
Tutoring improves student achievement, but identifying and studying what tutoring actions are most associated with student learning at scale based on audio transcriptions is an ope…
Augmenting Human-Annotated Training Data with Large Language Model Generation and Distillation in Open-Response Assessment
Conrad Borchers, Danielle R. Thomas, Jionghao Lin +2
Large Language Models (LLMs) like GPT-4o can help automate text classification tasks at low cost and scale. However, there are major concerns about the validity and reliability of…
A Systematic Review on Prompt Engineering in Large Language Models for K-12 STEM Education
Eason Chen, Danyang Wang, Luyi Xu +3
Large language models (LLMs) have the potential to enhance K-12 STEM education by improving both teaching and learning processes. While previous studies have shown promising result…
How Can I Get It Right? Using GPT to Rephrase Incorrect Trainee Responses
Jionghao Lin, Zifei Han, Danielle R. Thomas +4
One-on-one tutoring is widely acknowledged as an effective instructional method, conditioned on qualified tutors. However, the high demand for qualified tutors remains a challenge,…
How Can I Improve? Using GPT to Highlight the Desired and Undesired Parts of Open-ended Responses
Jionghao Lin, Eason Chen, Zeifei Han +5
Automated explanatory feedback systems play a crucial role in facilitating learning for a large cohort of learners by offering feedback that incorporates explanations, significantl…
Comparative Analysis of GPT-4 and Human Graders in Evaluating Praise Given to Students in Synthetic Dialogues
Dollaya Hirunyasiri, Danielle R. Thomas, Jionghao Lin +2
Research suggests that providing specific and timely feedback to human tutors enhances their performance. However, it presents challenges due to the time-consuming nature of assess…
Using Large Language Models to Provide Explanatory Feedback to Human Tutors
Jionghao Lin, Danielle R. Thomas, Feifei Han +4
Research demonstrates learners engaging in the process of producing explanations to support their reasoning, can have a positive impact on learning. However, providing learners rea…