GenAI in STEM Teacher Education: Investigating the Tensions and Emerging Possibilities of Adoption and Use

• In Event: Virtual Poster Session
  In Virtual iPresentation Only: Division K - Section 07: Teacher Educator Initial and Ongoing Development Virtual Poster Session

Abstract

This collaborative self-study investigates the integration of Generative Artificial Intelligence (GenAI) into STEM teacher education, focusing on tensions during adoption and use. Analyzing data through the AI Competency Framework, the authors, STEM teacher educators, reveal variations in GenAI use across courses, disciplines, and instructors. The study identifies factors that influenced their GenAI adoption in teacher preparation, including curriculum expectations, ethical concerns, and departmental norms. The findings highlight the complex relationship between STEM teacher educators' knowledge, beliefs, and perceived responsibilities, and the tensions that emerge when integrating GenAI into teacher preparation programs. Insights inform strategies and possibilities to support STEM teacher educators in navigating these tensions and harnessing GenAI to enhance inclusive teaching and learning, ensuring equitable access for all students.

Authors

• Yvonne Franco, University of Tampa

• Ruthmae Sears, University of South Florida

• Stephanie A. Arthur, University of South Florida

• Sandra Vernon-Jackson, University of South Florida