28 citations · 45 across the 12 of their papers we have counts for
12 papers
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…
Mapping Student-AI Interaction Dynamics in Multi-Agent Learning Environments: Supporting Personalised Learning and Reducing Performance Gaps
Zhanxin Hao, Jie Cao, Ruimiao Li +3
Multi-agent AI systems, which simulate diverse instructional roles such as teachers and peers, offer new possibilities for personalized and interactive learning. Yet, student-AI in…
AI instructional agent improves student's perceived learner control and learning outcome: empirical evidence from a randomized controlled trial
Fei Qin, Zhanxin Hao, Jifan Yu +2
This study examines the impact of an AI instructional agent on students' perceived learner control and academic performance in a medium demanding course with lecturing as the main…
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…
An LMM for Efficient Video Understanding via Reinforced Compression of Video Cubes
Ji Qi, Yuan Yao, Yushi Bai +4
Large Multimodal Models (LMMs) uniformly perceive video frames, creating computational inefficiency for videos with inherently varying temporal information density. This paper pres…