7 citations · 9 across the 5 of their papers we have counts for
6 papers
Agreement Is Not Validity: Cross-Model LLM Consensus in Diagnosing Student Failure Modes in K-12 Math Tutoring Dialogue
Clayton Cohn, Joyce Fonteles, Kirk Vanacore +5
In K-12 mathematics tutoring, student-tutor dialogue provides rich evidence of learners' problem-solving processes and sources of difficulty. Learning analytics research increasing…
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…
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…
Multimodal Methods for Analyzing Learning and Training Environments: A Systematic Literature Review
Clayton Cohn, Eduardo Davalos, Caleb Vatral +7
Recent technological advancements in multimodal machine learning--including the rise of large language models (LLMs)--have improved our ability to collect, process, and analyze div…
3D Gaze Tracking for Studying Collaborative Interactions in Mixed-Reality Environments
Eduardo Davalos, Yike Zhang, Ashwin T. S. +3
This study presents a novel framework for 3D gaze tracking tailored for mixed-reality settings, aimed at enhancing joint attention and collaborative efforts in team-based scenarios…
A First Step in Using Machine Learning Methods to Enhance Interaction Analysis for Embodied Learning Environments
Joyce Fonteles, Eduardo Davalos, Ashwin T. S. +9
Investigating children's embodied learning in mixed-reality environments, where they collaboratively simulate scientific processes, requires analyzing complex multimodal data to in…