摘要
教育在生活中是必不可少的一部分,随着高校的扩招,社会及学校也越来越关心学生的学习质量。对于高校来说,如何提升教师的教学质量是需要考虑的一个问题。在教学评价中,因为教学的多样性、学生自身的因素、教务部门的主管因素等使得教学评价难以客观、公正。BP神经网络是一种自适应的前馈型学习网络,它在人工智能领域中起着重要作用。在此,根据BP神经网络的特点,分析教学质量评价的因素,构建一个用于教学质量评价的BP神经网络模型,经过检验证明,BP神经网络可以很好地进行教学质量评价。
Education is an essential part of life.With the expansion of college enrollment,the society and school are more and more concerned about students'learning quality.For colleges and universities,how to improve the teaching quality of teachers is a problem to be considered.In the teaching evaluation,because of the diversity of teaching,the factors of students themselves,and the factors in charge of the educational administration department,it is difficult to make the teaching evaluation objective and fair.BP neural network is a kind of adaptive feedfor⁃ward learning network,which plays an important role in the field of artificial intelligence.In this paper,according to the characteristics of BP neural network,the factors of teaching quality evaluation are analyzed,and a BP neural network model for teaching quality evaluation is constructed.
作者
邱丹萍
QIU Dan-ping(Department of Software Engineering,Guangdong Baiyun College,Guangzhou 510450)
出处
《现代计算机》
2020年第33期44-46,共3页
Modern Computer
基金
校级项目:基于BP人工神经网络在教学质量评价体系中的应用研究(No.2019BYKYK04)。
关键词
教学评价
BP神经网络
Teaching Evaluation
BP Neural Network
