Data mining artificial intelligence technology for college english test framework and performance analysis system

• Published in: Journal of intelligent & fuzzy systems Vol. 40; no. 2; pp. 3489 - 3499
• Main Author: Shen, Lin
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.01.2021; Sage Publications Ltd
• Subjects: Algorithms; Artificial intelligence; Data mining; Design; Diagnostic systems; Machine learning; Model testing; Prediction models; Questions; Three dimensional models; Data mining; artificial intelligence; testing framework; performance analysis
• ISSN: 1064-1246; 1875-8967
• DOI: 10.3233/JIFS-189386

This article first studies and designs the college English test framework and performance analysis system. The author analyzes a large number of data collected by the system in three dimensions: using data mining title association models, using machine learning to merge college English score prediction models, and finally diagnosing on the basis of the sexual evaluation model, the author designed and implemented a test paper algorithm based on the association rules of the question type, and carried out relevant verification from the three aspects of test paper time, test question recommendation and improvement according to scores. Finally, according to the needs analysis, the author uses the diagnostic evaluation model and related test paper algorithm to design and implement the diagnostic evaluation model, which is added to the college English diagnostic practice system. It can be obtained through comparative experiments that the paper-based algorithm based on the diagnostic evaluation model proposed in this paper can effectively give better practice guidance and test question recommendation to the learner’s learning status and knowledge point problem obstacles, and can effectively improve learning. The achievements of the authors have broad application prospects and research value.