Exploring Chinese University Educators’ Acceptance and Intention to Use AI Tools: An Application of the UTAUT2 Model

Artificial Intelligence (AI) tools are having a significant impact on the field of education, particularly when used by educators. This study aims to explore the acceptance of AI tools among university-level educators. Researchers adapted the UTAUT2 (Unified Theory of Acceptance and Use of Technology) model to the Chinese educational context and surveyed 402 university educators. The findings revealed several predictors related to educators’ behavioral intention to use AI tools in teaching including performance expectancy, effort expectancy (which emerged as the strongest predictor), and hedonic motivation. Additionally, the study showed that the predictors of actual AI tool usage are facilitating conditions, habit (identified as the strongest predictor), and behavioral intention. Notably, the study found that gender, age, and experience did not have a moderating effect. This study contributes to the existing body of evidence on AI tool acceptance among university educators and holds implications for their training and professional development.

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Publication Details

Journal
SAGE Open
Published
2024-10-01
DOI
https://doi.org/10.1177/21582440241290013
Citations
27
Primary Topic
Technology Adoption and User Behaviour
Type
article
Field-Weighted Citation Impact
28.37
Controls
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article

Exploring Chinese University Educators’ Acceptance and Intention to Use AI Tools: An Application of the UTAUT2 Model

Pengfei Chen, Ge Zhang, Si Xu
27 citations
SAGE Open
Technology Adoption and User Behaviour
28.37
article

Exploring Chinese University Educators’ Acceptance and Intention to Use AI Tools: An Application of the UTAUT2 Model

Pengfei Chen, Ge Zhang, Si Xu
article en
27 citations

Abstract

Artificial Intelligence (AI) tools are having a significant impact on the field of education, particularly when used by educators. This study aims to explore the acceptance of AI tools among university-level educators. Researchers adapted the UTAUT2 (Unified Theory of Acceptance and Use of Technology) model to the Chinese educational context and surveyed 402 university educators. The findings revealed several predictors related to educators’ behavioral intention to use AI tools in teaching including performance expectancy, effort expectancy (which emerged as the strongest predictor), and hedonic motivation. Additionally, the study showed that the predictors of actual AI tool usage are facilitating conditions, habit (identified as the strongest predictor), and behavioral intention. Notably, the study found that gender, age, and experience did not have a moderating effect. This study contributes to the existing body of evidence on AI tool acceptance among university educators and holds implications for their training and professional development.

SAGE OpenVol. 14(4)
Dhurakij Pundit University (TH), Jiangsu Academy of Safety Science & Technology (CN)
Openalex Percentile: Top 1%
Technology Adoption and User Behaviour
28.37
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