The Research And Development For Teacher' Evaluation System Based On Neural Net

Teacher teaching evaluation is the most key procedure for quality of teaching.Especially,with education information go ahead rapidly,it is a very difficult problem that traditional quality of teaching is appraised appropriately by modern informational technology.At the same time,how to evaluate quality of teaching toward teachers also is a key issue,which affects the development of network teaching.Under above background,development for evaluation model of quality of teaching combined by computer intelligent algorithm is hopeful.Teaching evaluation of teacher,some existing questions,basic theories and measures of traditional teaching evaluation for teachers in regular institutes,and other things are discussed in this dissertation.With BP neural network technology conducted in evaluation of quality of teaching and a set of index system about evaluation of quality of teaching toward advanced vocational college followed,the basic data sets was fulfilled by some ways,such as teaching expertise's evaluation,mutual evaluation between teachers,students' evaluation,and so on.The samples are handled by normalization formula.On the basis of it,training network corresponding to first-class indexes of evaluation is accomplished.Evaluation model of BP neural network trained a amount of sample data in Matlab simulation tool,which demonstrates result of data training is objective and appropriate.Finally,including teaching evaluation system including evaluation model mentioned above on basis of simulating experiment on teaching evaluation model of BP neural network.Many functional modules are included in this system,such as online evaluation for quality of teaching,management of evaluation result,general information inquiry.Through assessment of system,we can gain access to large amounts of data that is utilized in deep-seated teaching analysis and decision-making.