Optimization of computer-aided english classroom teaching system based on data mining

Abstract

The conventional computer-assisted classroom teaching system has a small number of concurrent users and long information retrieval time. For this reason, we first designed a computer-assisted classroom teaching system based on data mining. Secondly, use the improved decision tree TG-C4.5 algorithms to conduct data mining on the learning behavior data to achieve the goal of predictive classification of performance. Finally, solve the problem that educators who lack data mining knowledge understand the mining results, integrate the algorithm into the education assistance system, realize the visualization of the predictive analysis results, and give personalized prompts to students' learning behaviors, thereby improving the teaching assistance the system makes it personalized.