Research on the Interactive Application of an Online Learning Platform for English Writing Based on the FBM Behavior Model

Abstract

The development of information technology makes the establishment of an online learning platform for English writing feasible. This paper deconstructs the user behavior of the online learning platform for English writing based on motivation, ability and trigger mechanism in the FBM model and models online learning behavior towards FBM. The combination of stack autoencoder and Gaussian mixture model constitutes a deep clustering model of learning motivation to analyze students’ online learning behaviors and personal information and identify different learning motivations of learning groups. Student behaviors were correlated with English writing scores, with a Spearman rank correlation coefficient of 0.811 for the number of coursework studies and 0.613 for the number of platform discussions.