Exploring the mediating role of attitude toward use in GenAI adoption for pre-service music teacher: insights from the UTAUT2 framework

Abstract

Introduction The rapid advancement of Generative AI (GenAI) has transformed educational practices, particularly in music education, offering new tools for enhancing teaching and learning experiences. However, research on its adoption by pre-service music teachers remains limited, particularly in understanding how cognitive and emotional factors influence their acceptance of these tools in real-world teaching contexts. Methods Based on the UTAUT2 framework, this study examines the factors influencing the adoption of GenAI by 848 pre-service music teachers from eight universities in China, focusing on the mediating role of their attitude in the technology acceptance process to enhance its integration into music education. The data were analyzed using Covariance-Based Structural Equation Modeling to test the hypothesized relationships between constructs and evaluate the mediating role of attitude toward use in pre-service music teachers’ adoption of GenAI. Results The hypothesis testing showed that most direct paths were significant, except for the direct effect of price value on behavioral intention. Mediation analysis found that ATU significantly mediated the relationships between predictors and BI. Adding ATU increased the model's explanatory power, with the R 2 for behavioral intention rising from 0.520 to 0.582. Discussion The discussion highlights that attitude toward use plays a crucial role in mediating the adoption of GenAI by pre-service music teachers, emphasizing the importance of both cognitive and emotional factors in technology acceptance. The findings suggest practical implications for educational administrators and GenAI developers to design user-friendly tools, provide supportive resources, and encourage positive attitudes through peer collaboration and hands-on experiences.

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