Analysis and Modelling Of English Learning Behaviour Based on Data Mining Technology

Abstract

This paper presents an in-depth exploration into the analysis and modelling of English learning behaviour leveraging data mining technology. In today's digital age, understanding the intricacies of how individuals acquire a second language is paramount for optimizing educational strategies and enhancing learning outcomes. By employing advanced data mining techniques, we aim to uncover patterns, trends, and underlying dynamics within English learning datasets, shedding light on the diverse behaviours exhibited by learners. Furthermore, this research transcends analysis, as we endeavour to construct robust models capable of simulating and predicting English learning trajectories. By leveraging insights derived from extensive data exploration, we aim to develop predictive models that offer personalized recommendations and adaptive learning pathways tailored to individual learner profiles. Ultimately, this paper contributes to the ongoing discourse surrounding language acquisition by providing valuable insights into English learning behaviours. By harnessing the power of data mining technology, we aspire to empower educators, policymakers, and digital learning platforms with the tools necessary to cultivate more efficient and inclusive approaches to English language education.