The main goal of this study was to examine the factors influencing the adoption of AI chatbots by preservice mathematics teachers in China.

Methods: The study employed the UTAUT2 model and Structural Equation Modeling (SEM) to analyze data from 322 preservice mathematics teachers in China. A questionnaire survey based on the UTAUT2 model was used to collect data.

Key Findings:

• Performance expectancy (PE) was the only factor that significantly influenced behavioral intention (BI) to use AI chatbots.
• Behavioral intention significantly influenced usage behavior (UB) of AI chatbots.
• Other factors like effort expectancy, facilitating conditions, habit, hedonic motivation, perceived risk, and social influence did not significantly predict behavioral intention.

Implications: The findings highlight the importance of emphasizing the practical benefits and performance improvements of AI chatbots to increase adoption among preservice mathematics teachers. This insight can guide the development of training programs and integration strategies for AI chatbots in teacher education.

Limitations:

• The study focused only on preservice mathematics teachers with prior experience using AI chatbots.
• The sample size and composition limited the ability to explore indirect effects within the research model.
• The study used a cross-sectional approach rather than a longitudinal design.

Future Directions:

• Include a broader and more varied cohort of participants in future studies.
• Conduct longitudinal research to better understand factors influencing behavioral intention and usage behavior over time.
• Explore additional external factors beyond the UTAUT2 model that may influence AI chatbot adoption in educational settings.

Title and Authors: "Examining Chinese preservice mathematics teachers' adoption of AI chatbots for learning: Unpacking perspectives through the UTAUT2 model" by Tommy Tanu Wijaya, Mingyu Su, Yiming Cao, Robert Weinhandl, and Tony Houghton.

Published On: Accepted on 4 June 2024

Published By: Education and Information Technologies (Springer)