DocumentCode :
2519287
Title :
The intelligent methods for teaching quality comprehensive assessment
Author :
Li, Lanchun ; Wang, Shuangcheng ; Leng, Cuiping
Author_Institution :
Sch. of Foreign Studies, Shanghai Lixin Univ. of Commerce, Shanghai, China
fYear :
2011
fDate :
23-25 May 2011
Firstpage :
2503
Lastpage :
2507
Abstract :
One of the important methods implied into teaching management is the comprehensive assessment of the teaching quality. Currently, this has been held based on weighted sum of those indexes among index system, which can not efficiently make use of the information dependency between historical information and indexes. In solving this dilemma, hierarchical naive Bayesian network was created, which can more efficiently utilize the dependency information between historical information and indexes when the three-class indexes can be either discrete or successive. In doing so, not only can comprehensive assessment of teaching quality realized, but also the quantitative analysis for the index contribution can be reached.
Keywords :
belief networks; teaching; hierarchical naive Bayesian network; historical information; index contribution; index system; information dependency; intelligent method; quality comprehensive assessment; teaching management; teaching quality; three-class index; Accuracy; Bayesian methods; Business; Education; Estimation; Indexes; Machine learning; Classifier; Comprehensive assessment; Contribution analysis; Hierarchical naive Bayesian network; Teacher teaching quality;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference (CCDC), 2011 Chinese
Conference_Location :
Mianyang
Print_ISBN :
978-1-4244-8737-0
Type :
conf
DOI :
10.1109/CCDC.2011.5968630
Filename :
5968630
Link To Document :
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