10 citations · 22 across the 17 of their papers we have counts for
18 papers
PEARL: A Task-Aware Framework for Evaluating Differentially Private Synthetic Educational Data
Xianghui Meng, Yujing Zhang, Jionghao Lin
Personalized learning systems rely on real learner data, including performance, behavior, and demographic information, but these data are highly privacy-sensitive. Differentially p…
TeachUp: Facilitating Early-Stage Teachers to Learn Instructional Strategies from Classroom Videos with Reflective Support
Haoxiang Fan, Ding Lei, Zaihong Zheng +4
Recorded videos of offline open classes provide good examples for early-stage teachers to learn instructional strategies, e.g., how to organize cooperative learning. However, learn…
Practice Less, Explain More: LLM-Supported Self-Explanation Improves Explanation Quality on Transfer Problems in Calculus
Eason Chen, Xinyi Tang, Yvonne Zhao +10
We conducted a between-subjects experiment (N=92) comparing three conditions in a calculus learning environment: no self-explanation (control), menu-based self-explanation, and ope…
Assessing the Impact and Underlying Pathways of Sequenced AI feedback on Student Learning
Jie Cao, Chloe Qianhui Zhao, Christian Schunn +3
Feedback is essential for learning, but its effectiveness relies heavily on how well it engages students in the educational process. Generative AI offers novel opportunities to eff…
Building Regulation Capacity in Human-AI Collaborative Learning: A Human-Centred GenAI System
Yujing Zhang, Jionghao Lin
Collaborative learning works when groups regulate together by setting shared goals, coordinating participation, monitoring progress, and responding to breakdowns through co-regulat…
Human-AI Collaboration Reconfigures Group Regulation from Socially Shared to Hybrid Co-Regulation
Yujing Zhang, Xianghui Meng, Shihui Feng +1
Generative AI (GenAI) is increasingly used in collaborative learning, yet its effects on how groups regulate collaboration remain unclear. Effective collaboration depends not only…
MisEdu-RAG: A Misconception-Aware Dual-Hypergraph RAG for Novice Math Teachers
Zhihan Guo, Yuting Lu, Jionghao Lin
Novice math teachers often encounter students' mistakes that are difficult to diagnose and remediate. Misconceptions are especially challenging because teachers must explain what w…
Chat-Based Support Alone May Not Be Enough: Comparing Conversational and Embedded LLM Feedback for Mathematical Proof Learning
Eason Chen, Sophia Judicke, Kayla Beigh +18
We evaluate GPTutor, an LLM-powered tutoring system for an undergraduate discrete mathematics course. It integrates two LLM-supported tools: a structured proof-review tool that pro…
Simulating Novice Students Using Machine Unlearning and Relearning in Large Language Models
Jiajia Song, Zhihan Guo, Jionghao Lin
Student simulation can support learning-by-teaching pedagogy where human students (as tutors) teach AI-simulated novice students (as tutees). Recent research often relies on prompt…
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…
Automated Bias Assessment in AI-Generated Educational Content Using CEAT Framework
Jingyang Peng, Wenyuan Shen, Jiarui Rao +1
Recent advances in Generative Artificial Intelligence (GenAI) have transformed educational content creation, particularly in developing tutor training materials. However, biases em…
VTutor: An Animated Pedagogical Agent SDK that Provide Real Time Multi-Model Feedback
Eason Chen, Chenyu Lin, Yu-Kai Huang +4
Pedagogical Agents (PAs) show significant potential for boosting student engagement and learning outcomes by providing adaptive, on-demand support in educational contexts. However,…
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…
RAMO: Retrieval-Augmented Generation for Enhancing MOOCs Recommendations
Jiarui Rao, Jionghao Lin
Massive Open Online Courses (MOOCs) have significantly enhanced educational accessibility by offering a wide variety of courses and breaking down traditional barriers related to ge…
Elucidating STEM Concepts through Generative AI: A Multi-modal Exploration of Analogical Reasoning
Chen Cao, Zijian Ding, Gyeong-Geon Lee +3
This study explores the integration of generative artificial intelligence (AI), specifically large language models, with multi-modal analogical reasoning as an innovative approach…
AI Chatbots as Multi-Role Pedagogical Agents: Transforming Engagement in CS Education
Cassie Chen Cao, Zijian Ding, Jionghao Lin +1
This study investigates the use of Artificial Intelligence (AI)-powered, multi-role chatbots as a means to enhance learning experiences and foster engagement in computer science ed…
Robust Educational Dialogue Act Classifiers with Low-Resource and Imbalanced Datasets
Jionghao Lin, Wei Tan, Ngoc Dang Nguyen +6
Dialogue acts (DAs) can represent conversational actions of tutors or students that take place during tutoring dialogues. Automating the identification of DAs in tutoring dialogues…
Does Informativeness Matter? Active Learning for Educational Dialogue Act Classification
Wei Tan, Jionghao Lin, David Lang +4
Dialogue Acts (DAs) can be used to explain what expert tutors do and what students know during the tutoring process. Most empirical studies adopt the random sampling method to obta…