A Cognitive Behavioral Computing Model Combined with DM’s Teaching Quality Improvement

Abstract

There are more and more ideas of applying data research science to replace theoretical research science, including monitoring and evaluation of school teaching quality. In order to distinguish different types of learners through knowledge and behavior performance, so as to better improve the teaching quality of teachers, a data mining model based on knowledge expression and calculation mode is provided. According to all the key cognitive and behavioral input parameters and cognitive and behavioral index factors, through the collection of artificial neural networks, sensitivity analysis, data mining, and classification regression trees, they are divided into three types of differences, so as to better adopt differentiation strategies for learners with different types. The experimental results also show that the behavior parameters are far more critical than the knowledge parameters. The research results show that the model is effective in supporting teachers' work in the education system.