A Knowledge Rule Mining Method for the Evaluation of Bilingual Teaching Quality in Universities Based on Genetic Algorithm

Abstract:

Bilingual teaching is the inevitable reform and development trend of higher education, and it is a very important job for us to evaluate the bilingual teaching quality. Currently, we do not have an effective evaluation system for bilingual teaching quality. In this study, the factors which affect bilingual teaching quality are analyzed and the evaluation index system of bilingual teaching quality in universities is established firstly. Then, a knowledge rule mining method for the evaluation of bilingual teaching quality in universities based on an improved genetic algorithm is proposed. In the algorithm, selection operator, dual crossover operator and dual mutation operator are used to generate new knowledge rules. Knowledge rules are evaluated by their accuracy, coverage and reliability. Experimental results show that this knowledge rule mining method is feasible and valid.

• Periodical: Applied Mechanics and Materials (Volumes 556-562)
• Pages: 3788-3792
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.556-562.3788
• Online since: May 2014
• Authors: Tai Shan Yan*, Guan Qi Guo, Wu Li, Wen Bin Li
• Keywords: Bilingual Teaching in Universities, Evaluation of Teaching Quality, Genetic Algorithm (GA), Knowledge Rule Mining

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