Pre-service Teachers’ Attitudes and Behavioral Intention Towards Generative Artificial Intelligence: A Structural Equation Modeling Investigation Based on TAM

Authors

  • Baoxin Guo School of Information Technology in Education, South China Normal University, Guangzhou
  • Yue Feng School of Information Technology in Education, South China Normal University, Guangzhou
  • Yifan Wang School of Information Technology in Education, South China Normal University, Guangzhou
  • Sijie Zhang School of Information Technology in Education, South China Normal University, Guangzhou
  • Xiaohong Liu Institute of Artificial Intelligence in Education, South China Normal University, Guangzhou
  • Yingbin Zhang Institute of Artificial Intelligence in Education, South China Normal University, Guangzhou

Keywords:

Pre-service teachers, generative artificial intelligence, technology acceptance model

Abstract

This study uses the Technology Acceptance Model (TAM) to explore factors influencing pre-service teachers’ intention to adopt generative artificial intelligence (GenAI). A total of 715 pre-service teachers participated in a questionnaire survey. Structural equation modeling was used to analyze the relationships among perceived ease of use (PEU), perceived usefulness (PU), attitude (ATT), and behavioral intention (BI). The results show that PEU positively affects PU, PU positively affects ATT, and ATT positively affects BI. Additionally, three significant mediating effects are identified. The findings provide valuable insights into the complex relationship between pre-service teachers’ attitudes toward GenAI and their intention to adopt it.

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Published

2025-06-06

Issue

Vol. 2025 (2025): GCCCE 2025 English Conference Proceedings

Section

文章