Analysis of Concentration in English Education Learning Based on CNN Model

Abstract

Obtaining the learning behavior of terminal learners solves the problem of inability to understand students’ concentration in class. When learners learn English, they can obtain learning concentration to understand learners’ concentration, in order to analyze the influence coefficient of various learning behavior data on learning concentration. This paper will design and implement a terminal data acquisition tool to collect the device perception information in the learning environment of learners, and capture the learner’s touch screen operation data based on the virtual simulation experiment, and then use the improved neural network to process the collected terminal sensor data for learning behavior. We identify and obtain the learner’s learning activity state, and finally fit the learner’s behavioral data weight through a linear regression equation, monitor the learner’s learning state, and explore the influencing factors of learning concentration.