Title :
Evaluating College English Teachers´ Teaching by Artificial Neural Network
Author_Institution :
Dept. of Coll. English Studies, Hohai Univ., Changzhou, China
Abstract :
Evaluating college English teachers´ teaching quality impartially scientifically is very important for improving English teaching quality and promoting teaching innovation. At present, the evaluating methods of college teaching quality have lots of disadvantages, such as subjectivity, short of impartiality, bad flexibility when meeting an emergency, etc. This article, starting off with evaluating target of our college, establishes an artificial neural network (BP) model of teaching quality, which evaluates college English teachers´ teaching quality. It testifies that the model is preferable and possesses powerful adaptability when it is applied to our college English teachers´ teaching quality.
Keywords :
backpropagation; educational administrative data processing; neural nets; teaching; English teaching quality; artificial neural network; college english teachers; teaching innovation; Adaptation models; Artificial neural networks; Educational institutions; Indexes; Training; English teaching quality; artificial neural network; evaluation; innovation;
Conference_Titel :
Control Engineering and Communication Technology (ICCECT), 2012 International Conference on
Conference_Location :
Liaoning
Print_ISBN :
978-1-4673-4499-9
DOI :
10.1109/ICCECT.2012.216