How Digital Teacher Appearance Anthropomorphism Impacts Digital Learning Satisfaction and Intention to Use: Interaction With Knowledge Type

Digital teachers represent an innovative fusion of media and artificial intelligence (AI) within online educational environments. However, the specific ways in which the appearance anthropomorphism of digital teachers influences the delivery of different knowledge types remain insufficiently understood. Drawing on Embodied Learning Theory and Parasocial Interaction Theory, this study investigates how digital teachers' appearance (cartoonish vs. realistic) interacts with knowledge types (explicit vs. tacit) to affect digital learning satisfaction and usage intention, exploring the mediating roles of physical and social presence. Initially, we implemented a 2×2 experimental design using a large language model (LLM) application, collecting data from 475 participants to empirically test our hypotheses. Subsequently, in-depth interviews were conducted with 21 Chinese university students to further validate and clarify the underlying mechanisms behind these interactions. The results indicate that digital teachers with a cartoonish appearance are more effective for delivering explicit knowledge, whereas digital teachers with a realistic appearance excel in conveying tacit knowledge. Both physical presence and social presence were found to significantly mediate these effects. This research enriches our understanding of AI-enhanced online education by highlighting the alignment effect between digital teacher appearance and the type of knowledge delivered, and by uncovering the underlying psychological mechanisms. Additionally, it offers practical insights for the design of digital human appearances in educational interfaces and broader AI-human interaction scenarios.