Improvement of English key competences based on machine learning and artificial intelligence technology

• Published in: Journal of intelligent & fuzzy systems Vol. 40; no. 2; pp. 2069 - 2081
• Main Authors: Zhao, Tingting, Cai, Yuanyuan
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.01.2021; Sage Publications Ltd
• Subjects: Algorithms; Artificial intelligence; Correlation analysis; Machine learning; Model accuracy; Redundancy; Technology assessment; English; key competences; artificial intelligence; intelligent recognition; Machine learning
• ISSN: 1064-1246; 1875-8967
• DOI: 10.3233/JIFS-189228

How to apply artificial intelligence technology to help education reform is a problem that teaching researchers need to solve urgently. Using artificial intelligence technology to improve the key competences of English subjects is the new direction of current English teaching development. This research combines machine learning technology to analyze the key competences assessment of English teaching disciplines and builds an evaluation model corresponding to the threshold. Moreover, on the basis of orderly mutual information, this study combines the maximum correlation and minimum redundancy theory to select the attribute algorithm to optimize the key competences assessment function of English subjects. In addition, in this study, the performance of the research model is analyzed through a comparative test, and the results are analyzed through actual numerical comparison and error comparison. The research results show that the recognition accuracy of this research model is closer than that of the real score, has higher accuracy, and has certain practical effects.