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Exploring Synergies: Teacher-AI Collaboration in K-12 STEM
Thu, April 24, 1:45 to 3:15pm MDT (1:45 to 3:15pm MDT), The Colorado Convention Center, Floor: Meeting Room Level, Room 608Session Type: Paper Session
Abstract
This session delves into the evolving collaboration between teachers and AI in K-12 STEM education, exploring how AI tools can enhance instructional practices, personalize learning, and improve student outcomes. This program highlights the potential and challenges of integrating AI into classrooms. Attendees will gain insights into how AI can support teachers in fostering more inclusive, engaging, and adaptive learning environments, while also addressing the professional development required to effectively harness these technologies for educational innovation.
Sub Unit
Chair
Papers
Enhancing K-12 Mathematics Instruction Through Human-AI Collaboration: A Comprehensive Study on Curriculum and AI Utilization - Alex Liu, University of Washington; Min Sun, University of Washington; Shawon Sarkar, University of Washington; Lorraine Marie Males, University of Nebraska - Lincoln; Zewei Tian, University of Washington
Exploring Teacher-AI Collaboration and Its Implications on Science Instruction - Soobin Jeon, University of Michigan; Yunyan Li, University of Michigan; Xingjian Gu, University of Michigan; Xinyi Lu, University of Michigan; Xiaoyu Liu, University of Maryland; Joshua Littenberg-Tobias, GBH; Shawn Stevens, WGBH; Xu Wang, University of Michigan; Ying Xu, Harvard University
Generating Automated Feedback and Hints for Algebra Problems Based on Directed Networks - Yajie Song, McGill University; Maria Cutumisu, McGill University