From tool to encounter: Generative AI as a catalyst for ethical and epistemic transformation in STEM teacher learning
Year: 2026
Type: conference-paper
Abstract: This paper examines how generative artificial intelligence (GenAI) reconfigures teacher learning within STEM education through a posthumanist and diffractive lens.Drawing on an empirical study involving preservice and inservice teachers engaged in AI-integrated science and mathematics classrooms, the paper reconceptualizes GenAI not as an instructional tool but as a pedagogical encounter and an active participant shaping teachers' epistemological and ethical becomings.Using data from microteaching sessions, collaborative lesson design, and reflective narratives, the study maps how teachers negotiate distributed learning and ethical response-ability as they design and critique AI-mediated learning activities.Findings reveal three entangled processes: emergent agency in classroom dialogues, distributed learning between teachers and AI tools, and ethical reconfigurations of teacher becoming.The paper proposes an onto-epistemological framework for GenAI integration that emphasizes relationality, reflexivity, and culturally responsive practice, contributing to learning sciences scholarship on technology-mediated teacher education.
Source: Proceedings.
Institutions: The Ohio State University, Boğaziçi University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: bronze
OpenAlex ID: W7214021231