Title: Analysing the influencing factors of mobile English learning for college students: improved principal component analysis

Authors: Na Wang; Lili Wang; Yanli Li; Bin Zhang

Addresses: College of Foreign Languages, Tangshan University, Tangshan, 063000, China ' College of Foreign Languages, Tangshan University, Tangshan, 063000, China ' College of Foreign Languages, Tangshan University, Tangshan, 063000, China ' Department of Technology, Intelligent Instrument Factory of North China University of Science and Technology, Tangshan, 063000, China

Abstract: Traditional methods for analysing the influencing factors of mobile English learning for college students cannot handle noise and redundant information in the data, reduce data dimensions, and cannot extract the most representative and explanatory factors for data variation. To address this issue, this article proposes an analysis method for the influencing factors of mobile English learning among college students based on an improved principal component analysis method. This method utilises fuzzy association rule algorithm to mine data on the impact of mobile English learning among college students. We constructed evaluation indicators from multiple dimensions to evaluate the influencing factors of mobile English learning among college students. Construct an evaluation function and analyse the influencing factors, and determine the indicators closely related to college students' mobile English learning through the score of the evaluation function. The experimental results show that the accuracy of the analysis of influencing factors in this article's method remains above 90%, and the analysis time does not exceed 2 minutes.

Keywords: improving principal component analysis method; college students; mobile English learning; influence factor.

DOI: 10.1504/IJCEELL.2025.143796

International Journal of Continuing Engineering Education and Life-Long Learning, 2025 Vol.35 No.1/2, pp.32 - 45

Received: 26 Jan 2024
Accepted: 09 Sep 2024
Published online: 07 Jan 2025 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article