大数据背景下高校学生评教降噪研究  

A Research into Noise Reduction Methods in Students’Evaluation of Teaching Under the Background of Big Data

作　　者：陈江薇[1] Chen Jiangwei(Hebei Agricultural University,Baoding 071000,China)

机构地区：[1]河北农业大学,河北保定071000

出　　处：《继续教育研究》2021年第3期158-160,共3页Continuing Education Research

基　　金：2018—2019年度河北省高等教育教学改革研究与实践项目立项研究内容。

摘　　要：学生评教工作的目的就是为了督促教师改进教学方法,提高教学质量。学生评价结果的客观公正是保证教学质量改进的关键一环。在全样本大数据背景下,利用数据挖掘的方法探索消除学生网络评教数据噪声方法,引导高校学生客观评价,保证评教数据的客观真实性,是高等教育教学一项亟待改进的工作。本文通过大数据背景下的数据挖掘对学生评教进行量化研究,找出学生评教规律,从而划分出学生评教噪声数据,研究降噪方法,减少噪声数据,促进学生评教工作的进一步规范,提高学生评教有效性。The purpose of students’making evaluation of teaching is to urge teachers to improve their teaching methods and quality.The objectiveness and fairness of students’evaluation results are an essential link that will ensure improvement of teaching quality.Under the background of full sample big data,it is urgent to improve higher education teaching by exploring the method of eliminating the noise of students’on-net teaching evaluation data by using data mining method and guiding college students to make objective evaluation to ensure an objective authenticity of teaching evaluation data.Through data mining under the background of big data,this paper makes a quantitative research into students’evaluation of teaching for the purpose of finding out the patterns of students’evaluation of teaching,so as to categorize the noise data of teaching evaluation and develop noise reduction methods to eliminate such noises.By doing so,the teaching evaluation work can be further standardized,and the effectiveness of students’evaluation of teaching can be enhanced.

关 键 词：学生评教 噪声数据 

分 类 号：G647.6[文化科学—高等教育学]