The main goals of this study were to examine factors determining pre-service teachers' acceptance of AI in education and investigate gender differences in AI acceptance.
Methods: The study used a survey based on the Technology Acceptance Model 3 (TAM3) administered to 452 pre-service teachers at a German university. Structural equation modeling, measurement invariance, and multigroup analysis were conducted to analyze the data.
Key Findings:
- Perceived usefulness and perceived ease of use were the most significant factors affecting pre-service teachers' intentions to use AI technology.
- AI anxiety did not significantly affect perceived ease of use.
- Gender differences were found in AI anxiety and perceived enjoyment.
- The relationship between AI anxiety and perceived ease of use was moderated by gender.
Implications: The findings provide insights for developing AI-based educational tools and addressing gender-specific concerns in teacher education programs.
Limitations: The study was limited to one German university, mostly first-year students, and did not employ a specific AI-based educational tool.
Future Directions: Future research should focus on creating new AI acceptance scales, investigating additional moderating variables, and conducting pre- and post-test comparison studies using AI-based applications.
Title and Authors: "Acceptance of artificial intelligence among pre-service teachers: a multigroup analysis" by Chengming Zhang, Jessica Schießl, Lea Plößl, Florian Hofmann, and Michaela Gläser-Zikuda
Published On: 2023
Published By: International Journal of Educational Technology in Higher Education