7 papers
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-…
DetPO: In-Context Learning with Multi-Modal LLMs for Few-Shot Object Detection
Gautam Rajendrakumar Gare, Neehar Peri, Matvei Popov +3
Multi-Modal LLMs (MLLMs) demonstrate strong visual grounding capabilities on popular object detection benchmarks like OdinW-13 and RefCOCO. However, state-of-the-art models still s…
A Theory-Guided LLM Pedagogical Agent for STEM+C Scaffolding Without Over-Reliance
Clayton Cohn, Surya Rayala, Siyuan Guo +13
LLM pedagogical agents are proliferating, yet recent findings have raised questions about their adherence to established theories of learning and, by extension, their educational v…
Personalizing Student-Agent Interactions Using Log-Contextualized Retrieval-Augmented Generation (RAG)
Clayton Cohn, Surya Rayala, Caitlin Snyder +10
Collaborative dialogue offers rich insights into students' learning and critical thinking, which is essential for personalizing pedagogical agent interactions in STEM+C settings. W…
A Theory of Adaptive Scaffolding for LLM-Based Pedagogical Agents
Clayton Cohn, Surya Rayala, Namrata Srivastava +6
Large language models (LLMs) present new opportunities for creating pedagogical agents that engage in meaningful dialogue to support student learning. However, current LLM systems…
LearnLens: An AI-Enhanced Dashboard to Support Teachers in Open-Ended Classrooms
Namrata Srivastava, Shruti Jain, Clayton Cohn +3
Exploratory learning environments (ELEs), such as simulation-based platforms and open-ended science curricula, promote hands-on exploration and problem-solving but make it difficul…