Teacher educators’ adoption of artificial intelligence: A qualitative UTAUT study

The growing presence of artificial intelligence (AI) in education has created a need to understand how teacher educators engage with it. While technology acceptance research has focused on teachers and applied the Unified Theory of Acceptance and Use of Technology (UTAUT) through quantitative models, teacher educators’ AI use remains underexplored. This study employs UTAUT as a framework to examine factors shaping teacher educators’ acceptance and use of AI in teacher education in Türkiye. Semi-structured interviews were conducted with 30 teacher educators and analysed using deductive and inductive coding. The findings suggest that the constructs of performance expectancy (PE), effort expectancy (EE), social influence (SI), and facilitating conditions (FC) remained relevant, though several acquired context-specific meanings and extensions in teacher education. Trust qualified PE, and AI literacy reframed EE, while student expectations and a sense of professional responsibility extended SI. Ethical assurance, in turn, operated as a precondition for behavioural intention.

Authors

Institutions

Publication Details

Journal
European Journal of Teacher Education
Published
2026-07-22
DOI
https://doi.org/10.1080/02619768.2026.2701094
Primary Topic
Technostress in Professional Settings
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Teacher educators’ adoption of artificial intelligence: A qualitative UTAUT study

Çiğdem Han-Tosunoğlu, Dilan Bayram, Gökçe Kurt
European Journal of Teacher Education
Technostress in Professional Settings
article

Teacher educators’ adoption of artificial intelligence: A qualitative UTAUT study

Çiğdem Han-Tosunoğlu, Dilan Bayram, Gökçe Kurt
article en

Abstract

The growing presence of artificial intelligence (AI) in education has created a need to understand how teacher educators engage with it. While technology acceptance research has focused on teachers and applied the Unified Theory of Acceptance and Use of Technology (UTAUT) through quantitative models, teacher educators’ AI use remains underexplored. This study employs UTAUT as a framework to examine factors shaping teacher educators’ acceptance and use of AI in teacher education in Türkiye. Semi-structured interviews were conducted with 30 teacher educators and analysed using deductive and inductive coding. The findings suggest that the constructs of performance expectancy (PE), effort expectancy (EE), social influence (SI), and facilitating conditions (FC) remained relevant, though several acquired context-specific meanings and extensions in teacher education. Trust qualified PE, and AI literacy reframed EE, while student expectations and a sense of professional responsibility extended SI. Ethical assurance, in turn, operated as a precondition for behavioural intention.

European Journal of Teacher Education
Marmara University (TR)
Quality Education
Openalex Percentile: Top 5%
Technostress in Professional Settings
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.