Comprehensive evaluation of teachers is a one of the important components of educational evaluation.The traditional comprehensive evaluation methods for teachers have played a certain positive role in promoting the improvement of teaching level,but these methods cannot escape the direct influence of human factors on the evaluation results.As a new technology,artificial neural network,has opened up new avenues for the study of uncertainty and nonlinear problems with their own abilities such as simulating human thinking,nonlinear mapping,and self-learning,and has been applied widely in appraisal fields.This paper introduces artificial neural networks(BP neural network)into the comprehensive evaluation of teachers,overcoming the direct impact of human factors on the evaluation results.Simulation experiments show that neural network is completely feasible for the comprehensive evaluation of teachers,providing a convenient and practical tool for the comprehensive evaluation of teachers in higher vocational colleges.
Teacher EvaluationArtificial Neural NetworkBP Neural NetworkEvaluation Index System
NETL
NSTL
万方数据
