Title
Teaching Quality Assessment System Based On Support Vector Machine Technology
Abstract
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.
Year
DOI
Venue
2016
10.3991/ijet.v11i11.6251
INTERNATIONAL JOURNAL OF EMERGING TECHNOLOGIES IN LEARNING
Keywords
Field
DocType
teaching quality, evaluation system, support vector machine technology
Data mining,Evaluation system,Inference,Computer science,Support vector machine,Artificial intelligence,Artificial neural network,Multimedia,Machine learning
Journal
Volume
Issue
ISSN
11
11
1863-0383
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Wenxue Huang110.82
Xin Gao210.82
Ning Wang323087.46
Yanchao Yang4136.14
Ying Yan585.11