Author(s):  
Zhifang Wang ◽  
Jia Liu

Massive open online courses (MOOC) transcends the time and space limits of traditional classroom teaching, and promotes the sharing of teaching resources. However, the effect of this emerging teaching mode is yet to be determined. In this paper, the big data analysis is introduced to evaluate the MOOC teaching quality. Taking several online courses as an example, a video player was de-signed to compute the learning time using the Hadoop platform. On this basis, the author constructed a teaching quality evaluation platform. In addition, the learning cost coefficient was calculated by the naive Bayesian model, and the evaluation results were analysed in details. The research findings shed practical new light on the evaluation of MOOC teaching quality.


Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Lijun Li ◽  
Wentao Wang ◽  
Fei Bian

With the increasing demand for applied and professional talents, the talent market has been in short supply. Although there are many talents in the talent market, the quality of talents cannot keep up with the development of quantity. Therefore, it is of great practical significance to establish a visual evaluation system of personnel training quality in the field of higher education. In view of the unreasonable evaluation and unclear weight relationship in the evaluation of educational indicators, this paper puts forward a big data analysis model to comprehensively evaluate teaching evaluation indicators, which has more scientific significance. In this paper, different systems in the index system are used as the analysis objects and the first-level weight relationship is normalized, which can distribute the weights more reasonably. Through the big data analysis method, the teaching quality evaluation system is more reasonable and scientific. In this paper, the quality index system for higher education background is designed and constructed and the weight relationship of different educational indicators is analyzed through big data, and four main indicators are obtained; then, the weight relationship of secondary indicators is analyzed, and finally, the weight relationship of all indicators is formed. The results show that the weight relationship of four indexes is 0.3285, 0.1973, 0.2967, and 0.1755, and the evaluation model of education quality is given.


Author(s):  
Xue-yan Li

Internet technology has developed rapidly, and online teaching has become the development trend of teaching in higher vocational colleges, which is conducive to modern learning methods for students and innovative teaching models for teachers. However, online teaching is still in the preliminary stage of development, and there is no unified standard for teaching quality evaluation. For this reason, big data technology can be integrated into the evaluation of higher vocational online teaching. This article first introduces the concept of online teaching quality evaluation, and then The application advantages of big data technology in the evaluation of network teaching quality are analyzed, and the key points of the construction of a higher vocational network teaching quality evaluation system based on big data analysis are explored in detail.


2019 ◽  
Vol 9 (1) ◽  
pp. 01-12 ◽  
Author(s):  
Kristy F. Tiampo ◽  
Javad Kazemian ◽  
Hadi Ghofrani ◽  
Yelena Kropivnitskaya ◽  
Gero Michel

2020 ◽  
Vol 25 (2) ◽  
pp. 18-30
Author(s):  
Seung Wook Oh ◽  
Jin-Wook Han ◽  
Min Soo Kim

2020 ◽  
Vol 14 (1) ◽  
pp. 151-163
Author(s):  
Joon-Seo Choi ◽  
◽  
Su-in Park

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