Open Access Article

Title: Exploration of English learning mode based on mobile learning platform assisted by data mining

Authors: Dan Zhao; Wenfeng Teng

Addresses: Xinxiang Vocational and Technical College, Xinxiang 453000, China ' The 22nd Research Institute of China Electronics Technology Group Corporation, Henan 453000, China

Abstract: As information technology develops, the use of mobile learning tools in English instruction is spreading rather rapidly. This study combines data mining techniques to explore effective methods for optimising English learning modes on mobile learning platforms. Firstly, using K-means clustering analysis to identify students' learning behaviour characteristics and identify student groups with different learning styles. Then, the Apriori algorithm is applied to mine the association rules between learning behaviour and learning outcomes, further revealing the key factors that affect learning outcomes. In addition, tracking students' learning progress and emotional changes through time series analysis provides a design basis for personalised learning paths for the platform. The research results indicate that optimisation strategies based on data mining can help improve learning effectiveness and support teachers and platform developers to provide more targeted learning suggestions.

Keywords: K-means; Apriori; data mining; time series analysis.

DOI: 10.1504/IJICT.2025.144055

International Journal of Information and Communication Technology, 2025 Vol.26 No.2, pp.67 - 81

Received: 08 Dec 2024
Accepted: 16 Dec 2024

Published online: 22 Jan 2025 *