most citedGenerative AI in Education: From Foundational Insights to the Socratic Playground for Learning

4 citations · 12 across the 8 of their papers we have counts for

collaborators

8 papers

cs.HC2025

Exploring Communication Strategies for Collaborative LLM Agents in Mathematical Problem-Solving

Liang Zhang, Xiaoming Zhai, Jionghao Lin +6

Large Language Model (LLM) agents are increasingly utilized in AI-aided education to support tutoring and learning. Effective communication strategies among LLM agents improve coll…

cs.LG2025

Generative Data Imputation for Sparse Learner Performance Data Using Generative Adversarial Imputation Networks

Liang Zhang, Jionghao Lin, John Sabatini +6

Learner performance data collected by Intelligent Tutoring Systems (ITSs), such as responses to questions, is essential for modeling and predicting learners' knowledge states. Howe…

cs.AI2025★ 4 cited

Generative AI in Education: From Foundational Insights to the Socratic Playground for Learning

Xiangen Hu, Sheng Xu, Richard Tong +1

This paper explores the synergy between human cognition and Large Language Models (LLMs), highlighting how generative AI can drive personalized learning at scale. We discuss parall…

cs.LG2024

Data Augmentation for Sparse Multidimensional Learning Performance Data Using Generative AI

Liang Zhang, Jionghao Lin, John Sabatini +6

Learning performance data describe correct and incorrect answers or problem-solving attempts in adaptive learning, such as in intelligent tutoring systems (ITSs). Learning performa…

cs.LG2024

Generative Adversarial Networks for Imputing Sparse Learning Performance

Liang Zhang, Mohammed Yeasin, Jionghao Lin +2

Learning performance data, such as correct or incorrect responses to questions in Intelligent Tutoring Systems (ITSs) is crucial for tracking and assessing the learners' progress a…

cs.AI2024★ 4 cited

SPL: A Socratic Playground for Learning Powered by Large Language Model

Liang Zhang, Jionghao Lin, Ziyi Kuang +2

Dialogue-based Intelligent Tutoring Systems (ITSs) have significantly advanced adaptive and personalized learning by automating sophisticated human tutoring strategies within inter…

cs.CY2024★ 2 cited

Predicting Learning Performance with Large Language Models: A Study in Adult Literacy

Liang Zhang, Jionghao Lin, Conrad Borchers +4

Intelligent Tutoring Systems (ITSs) have significantly enhanced adult literacy training, a key factor for societal participation, employment opportunities, and lifelong learning. O…

cs.CY2024★ 2 cited

3DG: A Framework for Using Generative AI for Handling Sparse Learner Performance Data From Intelligent Tutoring Systems

Liang Zhang, Jionghao Lin, Conrad Borchers +2

Learning performance data (e.g., quiz scores and attempts) is significant for understanding learner engagement and knowledge mastery level. However, the learning performance data c…