Evaluating College English Teachers' Teaching by Artificial Neural Network

Dong Jun
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Abstract

Evaluating college English teachers' teaching quality impartially scientifically is very important for improving English teaching quality and promoting teaching innovation. At present, the evaluating methods of college teaching quality have lots of disadvantages, such as subjectivity, short of impartiality, bad flexibility when meeting an emergency, etc. This article, starting off with evaluating target of our college, establishes an artificial neural network (BP) model of teaching quality, which evaluates college English teachers' teaching quality. It testifies that the model is preferable and possesses powerful adaptability when it is applied to our college English teachers' teaching quality.
用人工神经网络评价大学英语教师教学
科学公正地评价大学英语教师的教学质量,对于提高英语教学质量,促进教学创新具有十分重要的意义。目前,高校教学质量评价方法存在主观性强、缺乏公正性、在紧急情况下灵活性差等弊端。本文从我校的教学质量评价目标出发,建立了一个人工神经网络(BP)教学质量评价模型,对大学英语教师的教学质量进行了评价。将该模型应用到我国大学英语教师的教学质量中,证明了该模型的优越性和较强的适应性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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