59 citations · 167 across the 33 of their papers we have counts for
15 papers · 1 filter
LLM-based Multimodal Feedback Produces Equivalent Learning and Better Student Perceptions than Educator Feedback
Chloe Qianhui Zhao, Jie Cao, Jionghao Lin +1
Providing timely, targeted, and multimodal feedback helps students quickly correct errors, build deep understanding and stay motivated, yet making it at scale remains a challenge.…
Generative AI alone may not be enough: Evaluating AI Support for Learning Mathematical Proof
Eason Chen, Sophia Judicke, Kayla Beigh +16
We evaluate the effectiveness of LLM-Tutor, a large language model (LLM)-powered tutoring system that combines an AI-based proof-review tutor for real-time feedback on proof-writin…
AI Knows Best? The Paradox of Expertise, AI-Reliance, and Performance in Educational Tutoring Decision-Making Tasks
Eason Chen, Jeffrey Li, Scarlett Huang +4
We present an empirical study of how both experienced tutors and non-tutors judge the correctness of tutor praise responses under different Artificial Intelligence (AI)-assisted in…
VTutor for High-Impact Tutoring at Scale: Managing Engagement and Real-Time Multi-Screen Monitoring with P2P Connections
Eason Chen, Xinyi Tang, Aprille Xi +5
Hybrid tutoring, where a human tutor supports multiple students in learning with educational technology, is an increasingly common application to deliver high-impact tutoring at sc…
From First Draft to Final Insight: A Multi-Agent Approach for Feedback Generation
Jie Cao, Chloe Qianhui Zhao, Xian Chen +4
Producing large volumes of high-quality, timely feedback poses significant challenges to instructors. To address this issue, automation technologies-particularly Large Language Mod…
SlideItRight: Using AI to Find Relevant Slides and Provide Feedback for Open-Ended Questions
Chloe Qianhui Zhao, Jie Cao, Eason Chen +2
Feedback is important in supporting student learning. While various automated feedback systems have been implemented to make the feedback scalable, many existing solutions only foc…
Toward Automated Qualitative Analysis: Leveraging Large Language Models for Tutoring Dialogue Evaluation
Megan Gu, Chloe Qianhui Zhao, Claire Liu +4
Our study introduces an automated system leveraging large language models (LLMs) to assess the effectiveness of five key tutoring strategies: 1. giving effective praise, 2. reactin…
VTutor: An Open-Source SDK for Generative AI-Powered Animated Pedagogical Agents with Multi-Media Output
Eason Chen, Chenyu Lin, Xinyi Tang +4
The rapid evolution of large language models (LLMs) has transformed human-computer interaction (HCI), but the interaction with LLMs is currently mainly focused on text-based intera…
Improving Automated Feedback Systems for Tutor Training in Low-Resource Scenarios through Data Augmentation
Chentianye Xu, Jionghao Lin, Tongshuang Wu +2
Tutoring is an effective instructional method for enhancing student learning, yet its success relies on the skill and experience of the tutors. This reliance presents challenges fo…
Combining Large Language Models with Tutoring System Intelligence: A Case Study in Caregiver Homework Support
Devika Venugopalan, Ziwen Yan, Conrad Borchers +2
Caregivers (i.e., parents and members of a child's caring community) are underappreciated stakeholders in learning analytics. Although caregiver involvement can enhance student aca…
Do Tutors Learn from Equity Training and Can Generative AI Assess It?
Danielle R. Thomas, Conrad Borchers, Sanjit Kakarla +5
Equity is a core concern of learning analytics. However, applications that teach and assess equity skills, particularly at scale are lacking, often due to barriers in evaluating la…
Does Multiple Choice Have a Future in the Age of Generative AI? A Posttest-only RCT
Danielle R. Thomas, Conrad Borchers, Sanjit Kakarla +5
The role of multiple-choice questions (MCQs) as effective learning tools has been debated in past research. While MCQs are widely used due to their ease in grading, open response q…
GPTutor: Great Personalized Tutor with Large Language Models for Personalized Learning Content Generation
Eason Chen, Jia-En Lee, Jionghao Lin +1
We developed GPTutor, a pioneering web application designed to revolutionize personalized learning by leveraging the capabilities of Generative AI at scale. GPTutor adapts educatio…
Using Large Language Models to Assess Tutors' Performance in Reacting to Students Making Math Errors
Sanjit Kakarla, Danielle Thomas, Jionghao Lin +2
Research suggests that tutors should adopt a strategic approach when addressing math errors made by low-efficacy students. Rather than drawing direct attention to the error, tutors…
Improving Student Learning with Hybrid Human-AI Tutoring: A Three-Study Quasi-Experimental Investigation
Danielle R. Thomas, Jionghao Lin, Erin Gatz +8
Artificial intelligence (AI) applications to support human tutoring have potential to significantly improve learning outcomes, but engagement issues persist, especially among stude…