Affiliations: School of Foreign Language Education, Jilin University, Changchun, Jilin, China
Correspondence:
[*]
Corresponding author. Xiaolei Qin, School of Foreign Language Education, Jilin University, Changchun, Jilin, China. E-mail: [email protected].
Abstract: The process of international integration is accelerating continuously, which puts forward certain requirements for the current college students’ communicative ability and English ability. Therefore, it is necessary to further improve the students’ cross-cultural communicative ability in combination with English teaching. This paper combines machine learning and fuzzy mathematics methods to build an evaluation model of English cross-cultural communication ability. Moreover, based on the basic assumptions of college students’ oral communication ability evaluation, this paper builds a basic model for college students’ oral communication ability evaluation. In addition, through factor analysis and correlation analysis, this paper verifies the hypothesis of the student’s oral communication ability evaluation model and obtains an optimized university student’s oral communication ability evaluation model. After the model’s hypothesis testing and a series of statistical analysis, the evaluation system of college students’ oral communication ability is finally obtained. Finally, this article combines the investigation and analysis to test the performance of the model constructed in this article. The research results show that the capability evaluation model constructed in this paper has good performance.
Keywords: Machine learning, fuzzy mathematics, English cross-cultural, communicative ability
