The classroom interaction and learning effect are enhanced by the intelligent teaching system in the high-quality development of colleges and universities

Abstract

In recent years, Artificial Intelligence (AI) technology has developed rapidly, bringing new opportunities for the innovation of education. This paper adopts Bayesian network and Agent technology to construct an intelligent teaching system, which can formulate and implement guided learning strategies according to the individual, actively collect the most interesting information for the learners through the intelligent Agent proxy server, automatically generate a variety of questions and exercises, and reasonably plan and adjust the learning content and progress. Introducing knowledge points as the foundation of teaching resources, establishing connections between them, constructing dynamic knowledge tree models, and implementing intelligent interactive teaching strategies in the teaching system. Teaching research shows that with the empowerment of the intelligent teaching system, the effective interactive behavior of teachers and students covers up to 92.75% of the classroom time, which is significantly higher than the traditional coverage rate of 78.89%, effectively improving the effect of teacher-student interactions in the university classroom, while the academic performance of the experimental class has also been significantly improved. The intelligent teaching system is more effective in enhancing the high-quality development of universities.

Keywords

• bayesian network
• agent technology
• intelligent teaching system
• knowledge tree modeling
• 97p10