Teaching What We Don’t Yet Know: A Collaborative Self-Study of Teacher Educators Navigating Generative AI

• In Event: AERA Roundtable Session Sunday 11:45 am - Gold 1
  In Roundtable Session: Retooling on the Job: Technology, AI and Digital Tools for Teacher Educators

Abstract

This collaborative self-study examines how teacher educators engage in collective inquiry to model generative AI integration as a layered literacy practice, one that is ethical, critical, situated, and culturally responsive. Grounded in critical AI literacy (Bali, 2023; Roe et al., 2024), our bi-monthly meetings became spaces to explore how AI shapes our pedagogies, identities, and ethical commitments. We designed and reflected on small-scale classroom innovations while also grappling with broader tensions around authorship, labor, and justice. Our findings emphasize the importance of transparency, curiosity, and care, not just in practice, but in how we learn alongside one another. We offer a model of teacher education that embraces uncertainty and collective sensemaking as essential to navigating AI’s evolving role in literacy instruction.

Authors

• Katie Trautman, University of Texas at Austin

• Emily McDonald, University of Texas at Austin

• Laura Iris Sanchez, University of Texas at Austin

• Amanda Smith, University of Texas at Austin