Teaching Quality Assessment System Based on Support Vector Machine Technology

Wen-xue Huang, Xin Gao, Ning Wang, Yan-chao Yang, Ying Yan


A scientific, objective and accurate assessment of teaching quality is helpful in finding the relevant problems. So a highly accurate, quick and easy-to-implement teaching quality assessment system is necessary to build. The index value of the pulsed GTAW pool dynamic process by support vector machine inference and support vector machine neural networks is implemented in the teaching quality evaluation system. The teaching quality assessment system was tested on 30 teachers in a college. The results show that the assessment system is increasingly evidence-based. And the system can improve teaching quality and teaching management implementation.


teaching quality; evaluation system; support vector machine technology

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Copyright (c) 2017 Wen-xue Huang, Xin Gao, Ning Wang, Yan-chao Yang, Ying Yan

International Journal of Emerging Technologies in Learning (iJET) – eISSN: 1863-0383
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