Design Research on AI-Driven Virtual Teachers

Design Research on AI-Driven Virtual Teachers

This research focuses on the design of AI-driven virtual teachers to promote the development of personalized and intelligent education. In the post-pandemic era, the demand for online education has surged, but traditional virtual teacher products have limitations in responding to personalized needs and real-time knowledge updates. To address this, this paper proposes an innovative virtual teacher information model that combines technologies such as natural language processing, computer vision, and knowledge graphs. This model supports adaptive teaching, provides personalized learning experiences, and interacts with students through automatic knowledge updates. Through comparative analysis and technical analysis of virtual teachers, this paper demonstrates the advantages of AI-driven virtual teachers in aspects such as interactivity, knowledge base, emotional computing, and cost-effectiveness. Research results show that virtual teachers not only achieve significant results in knowledge updates, personalized teaching, and emotional interaction but also provide a viable path for educational technology innovation. Future research and technological development can further enhance the potential of virtual teachers in educational equity and learning efficiency.