A Method of Unstructured Information Process in Computer Teaching Evaluation System Based on Data Mining Technology

Author(s):  
Quan Liu ◽  
Yongjun Peng
2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Yong-tong Ma

The purpose is to enrich the evaluation system of physical education (PE) teaching in colleges and universities and to improve PE teaching methods and improve teaching quality. Based on big data information fusion and data mining technology, firstly, the related theories of teaching evaluation are analyzed and expounded, as well as the characteristics and principles of the construction of college PE teaching evaluation system. Secondly, from the perspective of evaluation index system of sports teachers’ teaching and students’ sports teaching, the content and evaluation index of college sports teaching evaluation are analyzed under the background of big data information fusion and data mining by questionnaire survey. Combined with model test, the results show that traditional college sports teacher pays more attention to the design and teaching methods of PE and ignore the learning process of students. The evaluation process of PE ignores the individual differences of students, the feedback method lacks openness, and the evaluation process is isolated. Based on the big data technology and teaching evaluation theory, the evaluation index is designed for PE teaching in colleges and universities. The average value of the first layer indexes is above 4, and the coefficient of variation is less than 0.2, which can basically reflect the content of PE teaching evaluation and provide some reference for the research of PE teaching evaluation.


2017 ◽  
Vol 14 (1) ◽  
pp. 7-12 ◽  
Author(s):  
Xiaoqi Liu

As the teaching management informationization level is higher and higher, Network based teaching evaluation system has been widely used, and a lot of evaluation of the original data has been accumulated. This research, taking recent five years teaching evaluation data of the college work for as basis, analyzes teachers’ personal factors and teaching operation factors respectively with the data mining technology of decision tree ID3 algorithm. By calculating the factors of information entropy and information gain value, the corresponding decision tree is gained. The teaching evaluation results are made use of really rather than become a mere formality, and thus provide powerful basis for the effectiveness and scientificalness of teaching evaluation.


2020 ◽  
Vol 16 (2) ◽  
pp. 18-33 ◽  
Author(s):  
Hongli Lou

This article proposes a new idea for the current situation of procedural evaluation of college English based on Internet of Things. The Internet of Things is used to obtain the intelligent data to enhance the teaching flexibility. The data generated during the process of procedural evaluation is carefully analyzed through data mining to infer whether the teacher's procedural evaluation in English teaching can be satisfied.


2014 ◽  
Vol 678 ◽  
pp. 43-46
Author(s):  
Hong Xin Wan ◽  
Yun Peng

Computer teaching should emphasize the engineering practicality, creativity, and pay more attention to the project and its application. It is important to evaluate the teaching effect. An evaluation system and corresponding algorithm are presented in this paper. There is a certain correlation between some evaluation factors, and the factors can be divided into key factors and secondary factors by rough set. The evaluation algorithm based on the key factors can reduce redundant factors and improve the efficiency. We designed a clustering algorithm based on fuzzy set on evaluation entities, which can reduce the dada size and improve the accuracy of the algorithm. Through the example analysis the algorithm of factors reduction based on rough set and clustering method based on fuzzy set are described in detail.


2013 ◽  
Vol 303-306 ◽  
pp. 1361-1364
Author(s):  
Wen Juan Li ◽  
Shi Min Wang

Due to the huge loss to the bank caused by credit risk in the financial debt crisis of the international Banking industry in 1980s, the research on Credit Assessment Methods is becoming the central issue of the study of financial theory in China and abroad. This paper builded the assets financial evaluation system of credit risk level based on the association rules-Apriori algorithm of data mining technology, which aimed the problems and the serious shortage of risk quantification study in domestic banks credit risk management. At the same time, taking into account the actual situation of our country, this paper analyzed that there are certain difficulties to use modern credit risk measurement models to evaluation the credit risk of commercial banks. And it suggests building a credit portfolio risk measurement model suitable for China's commercial banks with using logistic regression model of data mining technology.


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