The Influence Mechanism of Language Arousal in AI Digital Human Teachers on Learning Experience: The Mediating Role of Psychological Distance

While AI digital human teachers are increasingly utilized in the field of education, current designs often prioritize technical implementation while overlooking the psychological adaptability mechanisms inherent in instructional communication. (1) Grounded in social presence theory and cognitive load theory, this study investigates the impact of AI teachers' language arousal levels (high vs. low) on students' learning experiences and examines the pivotal mediating role of psychological distance in instructional outcomes. (2) A single-factor between-subjects experimental design was employed, where 100 participants were randomly assigned to either a high-arousal language group (enthusiastic and vivid) or a low-arousal language group (steady and calm) for a learning session. (3) Data analysis reveals that language arousal significantly and positively affects instructional outcomes (p<0.001); specifically, the high-arousal strategy yielded significantly higher scores in learning satisfaction, continuance intention, and perceived learning effectiveness compared to the low-arousal group. Furthermore, psychological distance serves as a key mediator, as high-arousal language conveys emotional cues that bridge the gap between students, the AI teacher, and the instructional content, thereby reducing cognitive defenses. (4) This study identifies psychological distance as a critical psychological mechanism for successful AI instruction, providing empirical evidence for the anthropomorphic design of AI educational tools and facilitating a paradigm shift in AI teachers from mere speech synthesis to emotional instructional communication.