Title: Research on modelling and analysis of factors influencing students' classroom communication ability based on support vector machine

Authors: Jue Wang; Xi Chen; Yang Zhang

Addresses: School of Foreign Languages, Northeast Normal University, Changchun 130024, China ' The Affiliated Elementary School of Shenzhen, Futian Academy of Educational Sciences, Shenzhen 518040, China ' School of Foreign Languages, Northeast Normal University, Changchun 130024, China

Abstract: In order to improve students' classroom learning effect, the influencing factors of communication ability were analysed. The traditional method of analysing students' classroom ability neglects the ordering of classroom communication ability factors, which results in poor fitting effect and high CPU consumption. This paper proposes an analysis model of influencing factors of students' classroom communication ability based on support vector machine (SVM). The sample data were converted and cleaned to establish a SVM model for influencing factors and students' classroom communication ability. The trained SVM model was used to analyse the degree of influence of each factor on students' classroom communication ability, and the factors were ranked in importance, so as to clarify the influencing factors of students' classroom communication ability. The simulation results show that the prediction results obtained by the research method are close to the fitting curve of the actual results. The CPU consumption of system operation is 15.88 Hz, which is lower than the traditional method.

Keywords: support vector machine; students' classroom communication ability; SVM model; trained SVM model.

DOI: 10.1504/IJCEELL.2022.124938

International Journal of Continuing Engineering Education and Life-Long Learning, 2022 Vol.32 No.4, pp.403 - 417

Received: 09 Apr 2020
Accepted: 03 Aug 2020
Published online: 18 Aug 2022 *

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