2 citations · 2 across the 8 of their papers we have counts for
5 papers · 1 filter
A Theory-Guided LLM Pedagogical Agent Supporting Open-Ended STEM+C Learning
Clayton Cohn, Surya Rayala, Siyuan Guo +13
Open-ended learning environments (OELEs) can support STEM+C (science, technology, engineering, mathematics, and computing) inquiry through activities such as computational modeling…
EXG: Self-Evolving Agents with Experience Graphs
Yuxin Jin, Siyuan Zhang, Hanchen Wang +3
Large language model (LLM)-based agents have demonstrated strong capabilities in complex reasoning and problem solving through multi-step interactions, yet most deployed agents rem…
AI-Assisted Competency Assessment from Egocentric Video in Simulation-Based Nursing Education
Hanchen David Wang, Yilin Liu, Madison J. Lee +4
Assessing learner competency in clinical simulation requires expert observation that is time-intensive, difficult to scale, and subject to inter-rater variability. Vision-language…
Towards Verified and Targeted Explanations through Formal Methods
Hanchen David Wang, Diego Manzanas Lopez, Preston K. Robinette +3
As deep neural networks are deployed in safety-critical domains such as autonomous driving and medical diagnosis, stakeholders need explanations that are interpretable but also tru…
Evidence-Decision-Feedback: Theory-Driven Adaptive Scaffolding for LLM Agents
Clayton Cohn, Siyuan Guo, Surya Rayala +11
LLMs offer tremendous opportunities for pedagogical agents to help students construct knowledge and develop problem-solving skills, yet many of these agents operate on a "one-size-…