A collective self-study of teacher educators on preparing early and elementary educators for reflective AI-integrated pedagogy

The introduction of generative artificial intelligence (GenAI) into teacher education has raised urgent questions about pedagogy, ethics, and teacher roles. This collective self-study of three teacher educators in an early childhood and elementary education program examined how they integrated GenAI into their coursework for pre- and in-service teachers. Guided by the UNESCO AI Competency Framework for Teachers (AI CFT), we investigated our practices, focusing on the human-centered, ethical, and pedagogical dimensions involved in supporting teachers to engage critically and agentively with AI tools. Findings revealed that intentional integration of GenAI can open new pedagogical spaces that move beyond prohibition toward critical and ehtical AI use. At the same time, our courses revealed persistent challenges: AI-generated content frequently contained cultural biases or inaccuracies, and many teachers initially accepted such content uncritically, underscoring the need for scaffolding and the development of critical digital literacy. Finally, we found that working with GenAI prompted teachers to (re)negotiate questions of authorship, originality, and professional identity, with responses ranging from resistance to cautious adaptation to growing curiosity. These insights suggest that teacher education must foreground critical AI literacy, ethical reasoning, and teacher agency to prepare educators for thoughtful, human-centered AI integration.

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Publication Details

Journal
Teachers and Teaching
Published
2026-11-04
DOI
https://doi.org/10.1080/13540602.2026.2755877
Primary Topic
Artificial Intelligence in Education
Type
article
Field-Weighted Citation Impact
0.00
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article

A collective self-study of teacher educators on preparing early and elementary educators for reflective AI-integrated pedagogy

Hyeonho Yu, Younkyung Hong, Sehyun Yun
Teachers and Teaching
Artificial Intelligence in Education
article

A collective self-study of teacher educators on preparing early and elementary educators for reflective AI-integrated pedagogy

Hyeonho Yu, Younkyung Hong, Sehyun Yun
article en

Abstract

The introduction of generative artificial intelligence (GenAI) into teacher education has raised urgent questions about pedagogy, ethics, and teacher roles. This collective self-study of three teacher educators in an early childhood and elementary education program examined how they integrated GenAI into their coursework for pre- and in-service teachers. Guided by the UNESCO AI Competency Framework for Teachers (AI CFT), we investigated our practices, focusing on the human-centered, ethical, and pedagogical dimensions involved in supporting teachers to engage critically and agentively with AI tools. Findings revealed that intentional integration of GenAI can open new pedagogical spaces that move beyond prohibition toward critical and ehtical AI use. At the same time, our courses revealed persistent challenges: AI-generated content frequently contained cultural biases or inaccuracies, and many teachers initially accepted such content uncritically, underscoring the need for scaffolding and the development of critical digital literacy. Finally, we found that working with GenAI prompted teachers to (re)negotiate questions of authorship, originality, and professional identity, with responses ranging from resistance to cautious adaptation to growing curiosity. These insights suggest that teacher education must foreground critical AI literacy, ethical reasoning, and teacher agency to prepare educators for thoughtful, human-centered AI integration.

Teachers and Teaching
Ball State University (US), The University of Texas Rio Grande Valley (US)
Openalex Percentile: Top 10%
Artificial Intelligence in Education
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A collective self-study of teacher educators on preparing early and elementary educators for reflective AI-integrated pedagogy — Hyeonho Yu, Younkyung Hong, et al. · Teachers and Teaching (2026) | TGRS Research Map | TGRS