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Scaffolding Learning with AI
Fri, April 10, 7:45 to 9:15am PDT (7:45 to 9:15am PDT), JW Marriott Los Angeles L.A. LIVE, Floor: Ground Floor, Gold 2Session Type: Roundtable Session
Abstract
This session examines how generative AI can (and cannot) serve as instructional scaffolding across diverse learning contexts—from social studies supports for ELLs to long-term effects on critical thinking, theoretical lenses for tool evaluation, and promoting self-regulated learning in graduate research. Together, the papers link practical evaluations, experimental evidence, and a multi-paradigmatic framework to surface design principles, equity concerns, and mechanisms by which AI scaffolds foster metacognition and learning outcomes.
Sub Unit
Chair
Papers
Looking for help: A test to see if AI can help create social studies scaffolds that provide key assistance for ELLs - Tierney B Hinman, Auburn University; Jesus Tirado, Auburn University; Jamie Harrison, Auburn University; Matthew F. Summerlin, Auburn University; Megan Andrews, Auburn University; Sarah I. Bailey, Opelika City Schools; Anna Poole, Auburn University
Use of AI-based Scaffolding in Writing: Longitudinal Impact on Critical Thinking - Qi Sun, University at Albany - SUNY; Alanda Joseph, University at Albany - SUNY; Cong Wu, University at Albany - SUNY; Gabriel Schlomer, University at Albany - SUNY; Tianlin Wang, University at Albany - SUNY
A Multi-Paradigmatic Perspective Towards the Adoption of Artificial Intelligence in Education - Haidee A. Jackson, University of Texas - Permian Basin; Suman Rath, Montclair State University
AI Scaffolding for Self-Regulated Learning in Graduate Research: A Mixed-Methods Study - Jiahui Qi, East China Normal University; Jun Xu, East China Normal University; Yutian Gao, East China Normal University