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Session Type: Poster Session
This session brings together empirical studies and design-based explorations of how educators and learners engage directly with generative AI in classroom settings. These works highlight AI as a pedagogical collaborator and focus on how teachers and students adapt to AI’s affordances.
30. Transforming EFL Learning: The Promise and Challenges of Generative AI Integration in Higher Education (Poster 30) - Siyuan Chen, College of William & Mary
31. Triadic Collaborative Intelligence in High School Algebra: A Case Study of Student–Teacher–AI Interaction (Poster 31) - Zilong Pan, Lehigh University; Zilu Jiang, Johns Hopkins University; Shen Ba, The Education University of Hong Kong; Chenglu Li, University of Utah
32. AI as Reflective Partner: Analyzing Pre-Service Teachers' Growth in ELL Instruction (Poster 32) - Donna Wake, University of Central Arkansas; Nykela Jackson, University of Central Arkansas; Lisa Mack, University of Central Arkansas
33. Co-Designing Lessons with AI: Elementary Teachers’ Use of Generative AI for Student-Centered Learning (Poster 33) - Seoyeon Choi, Korea University; Seulgi Jeong, Korea University; Yeongje Kim, Korea University; Insook Han, Korea University
34. Generative AI as Pedagogical Partner: Adoption, Challenges, and Transformation in U.S. Language Classrooms (Poster 34) - Jue Wang, University of North Carolina - Charlotte; Kristin Davin, University of North Carolina - Charlotte
35. Investigating Student Engagement and Ethical Reflection through Generative AI in Graduate Instructional Design (Poster 35) - Scott H. Moss, National University; Dwayne Wood, National University
36. Moving Beyond Efficiency: How Teacher Educators Reconsidered Their Beliefs and Practices with Generative AI (Poster 36) - Luqing Zang, Slippery Rock University of Pennsylvania; Jingwen He, University of North Texas; Yesim Nur Akar Hozman, Michigan State University