Analysis and Modeling of English Learning Behavior Based on Data Mining Technology

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Ming Shi


This paper investigates the application of data mining technology to analyze and model English learning behaviors, leveraging data from online learning platforms, educational applications, and institutional databases. By examining a diverse array of data types—including behavioral, performance, interaction, and demographic data—this study aims to uncover patterns and insights that enhance our understanding of the English language learning process. Employing various data mining techniques such as classification, clustering, association rule mining, regression analysis, sequential pattern mining, and text mining, we develop comprehensive models that capture the complexities of learner behavior. The findings demonstrate the potential of data mining to inform personalized educational strategies, optimize instructional methods, and improve learner outcomes. This research contributes to the field of educational data science by providing detailed analysis and practical recommendations for leveraging data mining in English language instruction.

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