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<p>Driven by the concept of wisdom education and the development needs of the times, personalized teaching has become a new requirement for the quality of talent cultivation under the national innovation-driven development strategy, and it is the inevitable trend of the current education and teaching reform. This paper builds a personalized teaching system in the era of smart education, based on the characteristics of local comprehensive universities. Face recognition technology is used to analyze the learning behavior of students in the smart campus, combined with virtualization technology and bilateral resources to integrate the teaching service model to realize the distribution of teaching service demand, and the classroom behavior is analyzed by deep intelligence through natural language processing technology. The proposed personalized teaching system is being implemented at Henan University of Science and Technology for specific practical analysis. The practical results show that the occupancy rate of students’ behavior in class 2 with the personalized teaching system is 0.3525 higher than that in class 1 with the traditional teaching system, and the occupancy rate of teachers’ behavior is 0.5422, with a higher conversion rate of teachers’ and students’ behavior. It shows that the new personalized teaching system is student-oriented and can effectively cultivate the quality of students is of great significance for the educational and teaching reform of the same type of colleges and universities.</p>
</abstract>

Driven by the concept of wisdom education and the development needs of the times, personalized teaching has become a new requirement for the quality of talent cultivation under the national innovation-driven development strategy, and it is the inevitable trend of the current education and teaching reform. This paper builds a personalized teaching system in the era of smart education, based on the characteristics of local comprehensive universities. Face recognition technology is used to analyze the learning behavior of students in the smart campus, combined with virtualization technology and bilateral resources to integrate the teaching service model to realize the distribution of teaching service demand, and the classroom behavior is analyzed by deep intelligence through natural language processing technology. The proposed personalized teaching system is being implemented at Henan University of Science and Technology for specific practical analysis. The practical results show that the occupancy rate of students’ behavior in class 2 with the personalized teaching system is 0.3525 higher than that in class 1 with the traditional teaching system, and the occupancy rate of teachers’ behavior is 0.5422, with a higher conversion rate of teachers’ and students’ behavior. It shows that the new personalized teaching system is student-oriented and can effectively cultivate the quality of students is of great significance for the educational and teaching reform of the same type of colleges and universities.

Research and Practice of Personalized Teaching System of Local Comprehensive University Based on Artificial Intelligence Technology

Henan University of Science and Technology

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Driven by the concept of wisdom education and the development needs of the times, personalized teaching has become a new requirement for the quality of talent...

Research and Practice of Personalized Teaching System of Local Comprehensive University Based on Artificial Intelligence Technology

Data publikacji: 31 sty 2024

Zakres stron: -

Otrzymano: 22 gru 2023

Przyjęty: 30 gru 2023

DOI: https://doi.org/10.2478/amns-2024-0253

Słowa kluczowe
Face recognition, Virtualization technology, Natural language processing, Intelligent education, Personalized teaching system

© 2024 Shanshan Li et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research and Practice of Personalized Teaching System of Local Comprehensive University Based on Artificial Intelligence Technology

Data publikacji: 31 sty 2024

Zakres stron: -

Otrzymano: 22 gru 2023

Przyjęty: 30 gru 2023

DOI: https://doi.org/10.2478/amns-2024-0253

Słowa kluczoweFace recognition, Virtualization technology, Natural language processing, Intelligent education, Personalized teaching system

© 2024 Shanshan Li et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Słowa kluczowe
Face recognition, Virtualization technology, Natural language processing, Intelligent education, Personalized teaching system