A Latent Growth Curve Modelling Study on the Impact of AI-Powered Robots on Classroom Enjoyment and Willingness to Attend Classes

Abstract

Artificial intelligence (AI) technologies have been increasingly recognised for their transformative potential in education. However, limited research has examined the emotional and behavioural impacts of AI-powered robots on students. To bridge this gap, the present study explored whether instruction supported by AI-powered robots enhances students' classroom enjoyment and their willingness to attend classes (WTAC). Adopting a longitudinal quasi-experimental design, the study involved 83 Chinese university students who participated in a semester-long course facilitated by three AI robots. Surveys were administered at both the beginning and end of the course to capture changes in the target constructs. Latent Growth Curve Modelling (LGCM) was employed to examine developmental trends and the dynamic relationships between enjoyment and WTAC over time. Findings revealed that AI-powered instruction significantly improved both classroom enjoyment and WTAC throughout the course. Additionally, a strong positive correlation was observed between the two constructs, suggesting a mutually reinforcing relationship between students' emotional engagement and their behavioural willingness to participate. These results are discussed in relation to relevant theoretical frameworks (i.e., control-value theory, theory of planned behaviour and the broaden-and-build theory), offering practical implications for educators and policymakers aiming to effectively integrate AI technologies into classroom instruction.