원문정보
초록
영어
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.
목차
1. Introduction
1.1 Research Background
1.2 Research Purpose and Significance
1.3 Research Methods
2. Literature Review
3. Theoretical Research
3.1 Definition of Virtual Teachers
3.2 Digital Humanities Theory
4. Virtual Teacher Information Model
4.1 Comparative Study of Virtual and Human Teachers
4.2 Key Technology Selection
4.3 Characteristics of Virtual Teachers
4.4 Virtual Teacher Information Model
4.5 Technological Integration and Research Synthesis
5. Research Result and Analysis
6. Conclusion
References
