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The Model of Research for Teaching Quality Evaluation Based on Neural Network

Author: YangXinJia
Tutor: LongXiHua
School: Xi'an University of Science and Technology
Course: Applied Mathematics
Keywords: Artificial neural network Teaching quality evaluation model Principal component analysis BP algorithm Algebraic algorithm
CLC: O242.1
Type: Master's thesis
Year: 2011
Downloads: 248
Quote: 4
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Abstract


The research of education quality has more and more attention by people with the unceasing deepening and developing of current higher education teaching reforms. It is focused on the improvement of teaching quality and teaching evaluation is key measure to improve the quality of education and teaching. Therefore, the establishing and perfecting of teaching quality evaluation system for education management has the extremely vital significance.In this paper, the teaching quality evaluation model is constructed, which based on BP neural network and INI neural network and combines characteristics of neural network with the research of teaching quality evaluation actuality and characteristic,and the BP algorithm and algebra algorithm which used in the model has the theoretical analysis and the contrast of training and provides a feasible solution results for the teaching quality evaluation model. Concretely,this paper deal with the research in the aspect as follows:(l)The main problems and difficulties are discussed and analyzed in the constructing perfect system of teaching quality evaluation, and this paper gives the solutions and analyzes the advantages and disadvantages of the past teaching quality evaluation method. The teaching quality evaluation model based on neural network is constructed on the ground that summarizing the existing liver methods of teaching quality evaluation model and against the limitations of the existing evaluation method.(2) Firstly, the paper introduces the basic principle of principal component analysis and finds that extracting principal component from the correlation coefficient matrix of the index ,which can’t reflect the difference information of variation degree of index. And then it gives the theoretical proof information of improved principal component analysis which can solve this problem. Lastly, the paper reduces the valuation index using the improved principal component analysis for the promise of retaining the original information. It avoids that the network model is too complicated to impact the result of prediction.(3) The paper introduces the knowledge of neural network domain comprehensively and researches the model constructing and training of BP neural network based on the dimension reduction systematically, and then the network structure and learning algorithm of teaching quality evaluation model based on the BP neural network are determined and the training results are analyzed.(4) According to the problems of BP algorithm, this paper uses algebra algorithm and gives the basic theory and advantages of that, and then it was applied to the teaching quality evaluation model based on neural network. Through the concrete instances, the paper analyzes the training results for using algebra algorithm and explains the validity and accuracy of the teaching quality model based on algebra algorithm.

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CLC: > Mathematical sciences and chemical > Mathematics > Computational Mathematics > Mathematical modeling, approximate calculation > Mathematical modeling
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