24 citations · 100 across the 44 of their papers we have counts for
7 papers · 1 filter
Personalized Learning Path Planning with Goal-Driven Learner State Modeling
Joy Jia Yin Lim, Ye He, Jifan Yu +7
Personalized Learning Path Planning (PLPP) aims to design adaptive learning paths that align with individual goals. While large language models (LLMs) show potential in personalizi…
Learning in Context: Personalizing Educational Content with Large Language Models to Enhance Student Learning
Joy Jia Yin Lim, Daniel Zhang-Li, Jifan Yu +7
Standardized, one-size-fits-all educational content often fails to connect with students' individual backgrounds and interests, leading to disengagement and a perceived lack of rel…
Handling Students Dropouts in an LLM-driven Interactive Online Course Using Language Models
Yuanchun Wang, Yiyang Fu, Jifan Yu +7
Interactive online learning environments, represented by Massive AI-empowered Courses (MAIC), leverage LLM-driven multi-agent systems to transform passive MOOCs into dynamic, text-…
LecEval: An Automated Metric for Multimodal Knowledge Acquisition in Multimedia Learning
Joy Lim Jia Yin, Daniel Zhang-Li, Jifan Yu +8
Evaluating the quality of slide-based multimedia instruction is challenging. Existing methods like manual assessment, reference-based metrics, and large language model evaluators f…
Student-AI Interaction in an LLM-Empowered Learning Environment: A Cluster Analysis of Engagement Profiles
Zhanxin Hao, Jianxiao Jiang, Jifan Yu +2
Integrating Large Language Models (LLMs) into educational practice enables personalized learning by accommodating diverse learner behaviors. This study explored diverse learner pro…
LongWriter-V: Enabling Ultra-Long and High-Fidelity Generation in Vision-Language Models
Shangqing Tu, Yucheng Wang, Daniel Zhang-Li +8
Existing Large Vision-Language Models (LVLMs) can process inputs with context lengths up to 128k visual and text tokens, yet they struggle to generate coherent outputs beyond 1,000…
Which Type of Students can LLMs Act? Investigating Authentic Simulation with Graph-based Human-AI Collaborative System
Haoxuan Li, Jifan Yu, Xin Cong +6
While rapid advances in large language models (LLMs) are reshaping data-driven intelligent education, accurately simulating students remains an important but challenging bottleneck…