A profile analysis of pre-service teachers’ AI acceptance: Combining behavioral, technological, and human factors

Zhang C, Hu M, Wu W, Chen Y, Kamran F, Wang X (2025)

Publication Type: Journal article

Publication year: 2025

Journal

Teaching and Teacher Education Elsevier

Book Volume: 163

Article Number: 105086

DOI: 10.1016/j.tate.2025.105086

Abstract

This study aims to identify distinct profiles of AI acceptance among pre-service teachers. Latent profile analysis and ANOVAs were conducted to determine whether homogeneous latent profiles exist within a sample of 453 pre-service teachers in China. Our findings revealed four different profiles: High Acceptors (19.21 %), Cautious Supporters (54.30 %), Skeptics (16.56 %), and Pragmatic Adopters (9.93 %). Additionally, the findings indicate that all groups express concern about AI-related technological factors. More specifically, the results point out the importance of AI compatibility and factors related to digital literacy in shaping AI acceptance among pre-service teachers across different groups.

Authors with CRIS profile

Yanfen Chen Lehrstuhl für Schulpädagogik mit dem Schwerpunkt empirische Unterrichtsforschung

Involved external institutions

Ningbo University / 宁波大学 CN China (CN) Zhejiang International Studies University (ZISU) / 浙江外国语学院 CN China (CN) University Of Baltistan (UOBS) / جامعہ بلتستان سکردو / ༑། ཡུ་ནི་ཝྲ་སིཊི་ ཨཕ་ སྦལ་ཏིས་ཏན །༑། PK Pakistan (PK)

How to cite

APA:

Zhang, C., Hu, M., Wu, W., Chen, Y., Kamran, F., & Wang, X. (2025). A profile analysis of pre-service teachers’ AI acceptance: Combining behavioral, technological, and human factors. Teaching and Teacher Education, 163. https://doi.org/10.1016/j.tate.2025.105086

MLA:

Zhang, Chengming, et al. "A profile analysis of pre-service teachers’ AI acceptance: Combining behavioral, technological, and human factors." Teaching and Teacher Education 163 (2025).

BibTeX: Download