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

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.

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Publication Details

Journal
International Journal of Continuing Engineering Education and Life-Long Learning
Published
2025-01-01
DOI
https://doi.org/10.1504/ijceell.2025.143796
Primary Topic
Educational Technology and Pedagogy
Type
article
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article

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

Lili Wang, Yanli Li, Na Wang, Bin Zhang
International Journal of Continuing Engineering Education and Life-Long Learning
Educational Technology and Pedagogy
article

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

Lili Wang, Yanli Li, Na Wang, Bin Zhang
article en

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.

International Journal of Continuing Engineering Education and Life-Long LearningVol. 35(1/2)
North China University of Science and Technology (CN), Tangshan College (CN)
Quality Education
Openalex Percentile: Top 100%
Educational Technology and Pedagogy
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