:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Thomas, Danielle R., Borchers, Conrad, Bhushan, Shambhavi, Gatz, Erin, Gupta, Shivang, Koedinger, Kenneth R.
Format:	Preprint
Published:	2025
Subjects:	Computation and Language Computers and Society
Online Access:	https://arxiv.org/abs/2506.17006
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Leveraging LLMs to Assess Tutor Moves in Real-Life Dialogues: A Feasibility Study
by: Thomas, Danielle R., et al.
Published: (2025)

Detecting LLM-Generated Short Answers and Effects on Learner Performance
by: Bhushan, Shambhavi, et al.
Published: (2025)

Do Tutors Learn from Equity Training and Can Generative AI Assess It?
by: Thomas, Danielle R., et al.
Published: (2024)

Augmenting Human-Annotated Training Data with Large Language Model Generation and Distillation in Open-Response Assessment
by: Borchers, Conrad, et al.
Published: (2025)

Improving Assessment of Tutoring Practices using Retrieval-Augmented Generation
by: Han, Zifei FeiFei, et al.
Published: (2024)

Does Multiple Choice Have a Future in the Age of Generative AI? A Posttest-only RCT
by: Thomas, Danielle R., et al.
Published: (2024)

Comparing Few-Shot Prompting of GPT-4 LLMs with BERT Classifiers for Open-Response Assessment in Tutor Equity Training
by: Kakarla, Sanjit, et al.
Published: (2025)

Beyond Agreement: Rethinking Ground Truth in Educational AI Annotation
by: Thomas, Danielle R., et al.
Published: (2025)

Brief but Impactful: How Human Tutoring Interactions Shape Engagement in Online Learning
by: Borchers, Conrad, et al.
Published: (2026)

Using Large Language Models to Assess Tutors' Performance in Reacting to Students Making Math Errors
by: Kakarla, Sanjit, et al.
Published: (2024)

Modernizing Ground Truth: Four Shifts Toward Improving Reliability and Validity in AI in Education
by: Thomas, Danielle R., et al.
Published: (2026)

Understanding Teacher Revisions of Large Language Model-Generated Feedback
by: Borchers, Conrad, et al.
Published: (2026)

Representation Learning to Study Temporal Dynamics in Tutorial Scaffolding
by: Borchers, Conrad, et al.
Published: (2026)

How Can I Get It Right? Using GPT to Rephrase Incorrect Trainee Responses
by: Lin, Jionghao, et al.
Published: (2024)

Disentangling Learning from Judgment: Representation Learning for Open Response Analytics
by: Borchers, Conrad, et al.
Published: (2025)

Large Language Models as Students Who Think Aloud: Overly Coherent, Verbose, and Confident
by: Borchers, Conrad, et al.
Published: (2026)

Improving Hybrid Human-AI Tutoring by Differentiating Human Tutor Roles Based on Student Needs
by: Gurung, Ashish, et al.
Published: (2026)

Starting Seatwork Earlier as a Valid Measure of Student Engagement
by: Gurung, Ashish, et al.
Published: (2025)

Benchmarking Educational LLMs with Analytics: A Case Study on Gender Bias in Feedback
by: Du, Yishan, et al.
Published: (2025)

From Heuristics to Analytics: Forecasting Effort and Progress in Online Learning
by: Qiu, Eric S., et al.
Published: (2026)

VTutor for High-Impact Tutoring at Scale: Managing Engagement and Real-Time Multi-Screen Monitoring with P2P Connections
by: Chen, Eason, et al.
Published: (2025)

Coasting Through Class: Learning Opportunity Loss from Practice Avoidance During Individual Seatwork
by: Gurung, Ashish, et al.
Published: (2026)

Measuring the Impact of Student Gaming Behaviors on Learner Modeling
by: Liu, Qinyi, et al.
Published: (2025)

An Integrated Platform for Studying Learning with Intelligent Tutoring Systems: CTAT+TutorShop
by: Aleven, Vincent, et al.
Published: (2025)

Predicting Learning Performance with Large Language Models: A Study in Adult Literacy
by: Zhang, Liang, et al.
Published: (2024)

The Digital Divide in Generative AI: Evidence from Large Language Model Use in College Admissions Essays
by: Lee, Jinsook, et al.
Published: (2026)

Toward Trait-Aware Learning Analytics
by: Borchers, Conrad, et al.
Published: (2026)

3DG: A Framework for Using Generative AI for Handling Sparse Learner Performance Data From Intelligent Tutoring Systems
by: Zhang, Liang, et al.
Published: (2024)

Who Decides in AI-Mediated Learning? The Agency Allocation Framework
by: Borchers, Conrad, et al.
Published: (2026)

GPTutor: Great Personalized Tutor with Large Language Models for Personalized Learning Content Generation
by: Chen, Eason, et al.
Published: (2024)

Toward LLM-Supported Automated Assessment of Critical Thinking Subskills
by: Peczuh, Marisa C., et al.
Published: (2025)

Can Large Language Models Match Tutoring System Adaptivity? A Benchmarking Study
by: Borchers, Conrad, et al.
Published: (2025)

Compounding Disadvantage: Auditing Intersectional Bias in LLM-Generated Explanations Across Indian and American STEM Education
by: Gupta, Amogh, et al.
Published: (2026)

Combining Large Language Models with Tutoring System Intelligence: A Case Study in Caregiver Homework Support
by: Venugopalan, Devika, et al.
Published: (2024)

Reviewing the Reviewer: Elevating Peer Review Quality through LLM-Guided Feedback
by: Purkayastha, Sukannya, et al.
Published: (2026)

Leveraging Large Language Models for Identifying Knowledge Components
by: Wang, Canwen, et al.
Published: (2025)

When Neutral Summaries are not that Neutral: Quantifying Political Neutrality in LLM-Generated News Summaries
by: Vijay, Supriti, et al.
Published: (2024)

An Annotated Reading of 'The Singer of Tales' in the LLM Era
by: Varshney, Kush R.
Published: (2025)

LLUMI: Improving LLM Writing Assistance for Mental Health Support with Online Community Feedback
by: Kim, Jiwon, et al.
Published: (2026)

HRIPBench: Benchmarking LLMs in Harm Reduction Information Provision to Support People Who Use Drugs
by: Wang, Kaixuan, et al.
Published: (2025)