基于BP神经网络的高校教师教学质量评价模型

Research on Evaluation Model of University Teachers' Teaching Quality Based on BP Neural Network

针对目前大多数高校采用单一的教学评价机制来衡量教师教学质量的片面性,在充分考虑被评对象的差异性、评教主体的单一性以及评教方法的难操作性的基础上建立了全方位教学质量评价体系,构建了综合评价体系及2个体系下的7个二级指标,并以此为基础建立两级神经网络。训练结果表明:该网络能较好地拟合训练数据,预测效果显著,说明基于神经网络的教学质量评价模型是合理可行的。

Because of the one-sidedness in most universities through using single teaching evaluation mechanism to evaluate the teachers＇ teaching quality, a full range of teaching quality evaluation system was presented after that we fully considered the differences of evaluated objects, the single subject and the difficult manipulate evaluation method. 7 indicators under the 2 level systems （ comprehensive evaluation system and two-stage system） were build, and based on this we established 2-level neural network. The training results show that the network can fit the training data and the effect is significant, so the teaching quality evaluation of the neural network model is reasonable and feasible.