基于大数据背景下的数据挖掘的高校思想政治教学评价指标体系。
Evaluation Index System of Ideological and Political Teaching in Colleges and Universities Based on Data Mining under the Background of Big Data.
机构信息
Henan Polytechnic Institute, Nanyang, Henan 47300, China.
出版信息
Comput Intell Neurosci. 2022 Jul 12;2022:4286656. doi: 10.1155/2022/4286656. eCollection 2022.
The big data age has given rise to a new approach for evaluating PIE in colleges and institutions. It is conducive for promoting the development of teaching evaluation in universities and colleges, as well as improving the overall quality of political and ideological education (PIE) in universities and colleges, by using the big data idea and data mining theory to study the Evaluation Index System (EIS) of PIE in universities and colleges. The PIE EIS in universities and colleges is a critical component in achieving PIE Evaluation. It is the main carrier and intuitive manifestation of the evaluation standards of teaching. It clearly defines the content, scope, and scale of the evaluation of political and ideological theory teaching. By using the decision tree algorithm in data mining, it can help process data, complete the data feedback, and determine the indicators of each level of EIS for PIE in universities and colleges. Finally, the effect of this EIS is judged by experiment. The result shows that more than 40% of students are satisfied with the quality of political and ideological course teaching, 36.8% are satisfied with the analysis of the implementation of political and ideological classes in schools, and overall are satisfied with the political and ideological teaching in universities and colleges.
大数据时代的到来为高校思想品德测评提供了一种新的方法。利用大数据理念和数据挖掘理论来研究高校思想品德测评的评价指标体系(EIS),有利于促进高校教学评价的发展,提高高校思想品德教育的整体质量。高校思想品德测评 EIS 是实现思想品德测评的关键组成部分,是教学评价标准的主要载体和直观体现,明确了对思想政治理论课教学评价的内容、范围和尺度。通过数据挖掘中的决策树算法,可以帮助处理数据、完成数据反馈,并确定高校思想品德测评 EIS 的各个层次的指标。最后,通过实验判断该 EIS 的效果。结果表明,超过 40%的学生对思想政治课的教学质量表示满意,36.8%的学生对学校开展思想政治课的情况分析表示满意,对高校的思想政治教学总体上表示满意。
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