Comparing the Factor Structure of the TPACK Model to Assess AI Teaching Readiness in Pre-Service Teachers

Shanshan Cheng; Jirui Dong; Shujing Wu; Min Tang; Hui Sui

doi:10.2991/978-94-6463-750-2_26

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Comparing the Factor Structure of the TPACK Model to Assess AI Teaching Readiness in Pre-Service Teachers

Authors

Shanshan Cheng¹, Jirui Dong¹, Shujing Wu²^{, *}, Min Tang³, Hui Sui¹

¹Jinan Preschool Education College, Jinan, 250100, P. R. China

²Guangzhou Institute of Science and Technology, Guangzhou, 510540, P. R. China

³Hunan International Economics University, Changsha, 410205, P. R. China

^*Corresponding author. Email: 1955827979@qq.com

Corresponding Author

Shujing Wu

Available Online 15 June 2025.

DOI: 10.2991/978-94-6463-750-2_26 How to use a DOI?
Keywords: TPACK; Pre-service Teacher; AI Teaching Readiness
Abstract: This study examines the TPACK model’s factor structure to assess pre-service teachers’ readiness in J City, China, for integrating AI into their teaching practices. A survey involving 322 participants was conducted to investigate the relationships between TPACK components and their impact on competencies related to AI-enhanced teaching. The PLS-SEM analysis indicates that TK, PK, and CK significantly influence AI teaching readiness through their interactions with PCK, TPK, and TCK. Notably, TK exerts the most substantial impact on TPCK, highlighting the critical role of technological proficiency in AI-based education. Furthermore, PCK and TCK act as mediators for the effects of CK, while TPK and TCK mediate the influence of TK. This underscores the importance of integrated pedagogical and technological training. The findings suggest a need for AI-powered adaptive learning systems and immersive professional learning communities, emphasizing AI-related pedagogical strategies to enhance pre-service teachers’ digital teaching capabilities. The study also explores implications for AI-oriented teacher training and curriculum development.
Copyright: © 2025 The Author(s)
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title: Proceedings of the 2025 4th International Conference on Educational Innovation and Multimedia Technology (EIMT 2025)
Series: Atlantis Highlights in Social Sciences, Education and Humanities
Publication Date: 15 June 2025
ISBN: 978-94-6463-750-2
ISSN: 2667-128X
DOI: 10.2991/978-94-6463-750-2_26 How to use a DOI?
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

ris enw bib

TY  - CONF
AU  - Shanshan Cheng
AU  - Jirui Dong
AU  - Shujing Wu
AU  - Min Tang
AU  - Hui Sui
PY  - 2025
DA  - 2025/06/15
TI  - Comparing the Factor Structure of the TPACK Model to Assess AI Teaching Readiness in Pre-Service Teachers
BT  - Proceedings of the 2025 4th International Conference on Educational Innovation and Multimedia Technology (EIMT 2025)
PB  - Atlantis Press
SP  - 278
EP  - 284
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-94-6463-750-2_26
DO  - 10.2991/978-94-6463-750-2_26
ID  - Cheng2025
ER  -

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