Cover Image

Brief but Impactful: How Human Tutoring Interactions Shape Engagement in Online Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Borchers, Conrad, Gurung, Ashish, Liu, Qinyi, Thomas, Danielle R., Khalil, Mohammad, Koedinger, Kenneth R.
Format:	Preprint
Published:	2026
Subjects:	Computers and Society
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

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

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

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

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

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

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

LLM-Generated Feedback Supports Learning If Learners Choose to Use It
by: Thomas, Danielle R., et al.
Published: (2025)

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

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

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

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

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)

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

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

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

Automatic Large Language Models Creation of Interactive Learning Lessons
by: Lin, Jionghao, et al.
Published: (2025)

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)

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

Million Tutoring Moves (MTM): An Open Multimodal Dataset for the Science of Tutoring
by: Kizilcec, René, 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)

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

Evaluating a Data-Driven Redesign Process for Intelligent Tutoring Systems
by: Lyu, Qianru, et al.
Published: (2026)

Who Decides in AI-Mediated Learning? The Agency Allocation Framework
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)

Sticky Help, Bounded Effects: Session-by-Session Analytics of Teacher Interventions in K-12 Classrooms
by: Jin, Qiao, et al.
Published: (2026)

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

How Learner Control and Explainable Learning Analytics on Skill Mastery Shape Student Desires to Finish and Avoid Loss in Tutored Practice
by: Borchers, Conrad, et al.
Published: (2024)

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

How Can I Improve? Using GPT to Highlight the Desired and Undesired Parts of Open-ended Responses
by: Lin, Jionghao, et al.
Published: (2024)

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

Fifteen Years of Learning Analytics Research: Topics, Trends, and Challenges
by: Švábenský, Valdemar, et al.
Published: (2026)

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

GPT-4 as a Homework Tutor can Improve Student Engagement and Learning Outcomes
by: Vanzo, Alessandro, et al.
Published: (2024)

Optimizing Mastery Learning by Fast-Forwarding Over-Practice Steps
by: Xia, Meng, et al.
Published: (2025)

The Impact of Virtual Laboratories on Active Learning and Engagement in Cybersecurity Distance Education
by: Kebande, Victor R.
Published: (2024)

Push and Pull in Community College Cross-Enrollment: Remoteness, Articulation, and Student Mobility
by: Borchers, Conrad, et al.
Published: (2026)

How to Assess AI Literacy: Misalignment Between Self-Reported and Objective-Based Measures
by: Zhang, Shan, et al.
Published: (2026)

AI2T: Building Trustable AI Tutors by Interactively Teaching a Self-Aware Learning Agent
by: Weitekamp, Daniel, et al.
Published: (2024)

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