基于神经网络的高职教师教学质量评价模型的构建

针对神经网络的结构特性、自适应和自学习功能，提出了基于BP神经算法建立高职教师教学质量评价系统，确定了系统的数学模型，采用各评价指标作为其输入，教学效果作为输出，该模型在收敛速度、网络的适应能力方面是可行的、适用的。实验结果表明：该数学模型克服了传统分析评价教学过程中的复杂性和人为因素干扰，具有方便、准确、可靠、快速的特点，辨识精度高。

Construction of Teaching Quality Evaluating Model in Higher Vocational Colleges - Based on the Neural Network

In view of the construction features, self-adaptation and self-learning functions of neural network, this article puts forward a teaching quality evaluating model in higher vocational colleges which is based on the BP neural network algorithm. A systematic math model is specified, in which all kinds of evaluating indexes are viewed as the input information while the teaching effect is viewed as the output information. This model is workable and adaptable when speed restraining and network adaptability are concerned. Results of experiments show that this math model overcomes the complexity and disturbing elements of human beings which are normally found in the traditional analyzing and evaluating process towards teaching. Convenience, exactness, reliability, speediness are also features of this new model.