Pioneering Teacher Educators Navigating AI Integration in Pre-Service Teacher Preparation: Strategies and Challenges

The rapid integration of artificial intelligence (AI) into educational settings presents a profound challenge for teacher education. This study examines how pioneering teacher educators in Israeli colleges of education perceive their role in training student teachers for AI-integrated teaching. Using a qualitative, interpretive phenomenological approach, semi-structured interviews were conducted with 13 participants—seven pedagogical advisors and six lecturers—from seven teacher training institutions representing diverse educational streams. Data were analyzed using a hybrid approach combining human thematic analysis and AI-assisted dialogic analysis. Findings revealed that participants perceived themselves as agents of change responsible for modeling critical AI use, while raising epistemic concerns regarding cognitive atrophy and the erosion of expertise. A crisis of trust triggered by students’ uncritical submission of AI-generated outputs prompted a shift toward process-based and in-class assessment. Pre-service teachers used AI for differentiated lesson planning, visual aids, and simulations, with experiences ranging from heightened self-efficacy to frustration. Persistent challenges included rapid technological change, the absence of institutional policy, ethical and privacy concerns, cultural factors, and economic barriers. Drawing on post-digital theory and AI literacy frameworks, this study argues that effective preparation for the AI era requires a fundamental reimagining of teacher education—one that redefines literacy, pedagogy, and human agency.

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Publication Details

Journal
AI in Education
Published
2026-08-18
DOI
https://doi.org/10.3390/aieduc2030029
Primary Topic
Teaching and Learning Programming
Type
article
Field-Weighted Citation Impact
0.00
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article

Pioneering Teacher Educators Navigating AI Integration in Pre-Service Teacher Preparation: Strategies and Challenges

Olzan Goldstein, Wafa Zidan, Nareman Marae-Haj
AI in Education
Teaching and Learning Programming
article

Pioneering Teacher Educators Navigating AI Integration in Pre-Service Teacher Preparation: Strategies and Challenges

Olzan Goldstein, Wafa Zidan, Nareman Marae-Haj
article en

Abstract

The rapid integration of artificial intelligence (AI) into educational settings presents a profound challenge for teacher education. This study examines how pioneering teacher educators in Israeli colleges of education perceive their role in training student teachers for AI-integrated teaching. Using a qualitative, interpretive phenomenological approach, semi-structured interviews were conducted with 13 participants—seven pedagogical advisors and six lecturers—from seven teacher training institutions representing diverse educational streams. Data were analyzed using a hybrid approach combining human thematic analysis and AI-assisted dialogic analysis. Findings revealed that participants perceived themselves as agents of change responsible for modeling critical AI use, while raising epistemic concerns regarding cognitive atrophy and the erosion of expertise. A crisis of trust triggered by students’ uncritical submission of AI-generated outputs prompted a shift toward process-based and in-class assessment. Pre-service teachers used AI for differentiated lesson planning, visual aids, and simulations, with experiences ranging from heightened self-efficacy to frustration. Persistent challenges included rapid technological change, the absence of institutional policy, ethical and privacy concerns, cultural factors, and economic barriers. Drawing on post-digital theory and AI literacy frameworks, this study argues that effective preparation for the AI era requires a fundamental reimagining of teacher education—one that redefines literacy, pedagogy, and human agency.

AI in EducationVol. 2(3)
Kaye Academic College of Education (IL), The Arab Academic College for Education in Israel (IL)
Quality Education
Openalex Percentile: Top 5%
Teaching and Learning Programming
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