6 papers
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…
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…
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…
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…
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…
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…