Research on Online Teaching Quality Management in Higher Vocational Colleges Based on Data Mining Algorithm

In order to evaluate the quality of online teaching in higher vocational colleges quantitatively under the theory of constructivism learning context, a quality management model of online teaching in higher vocational colleges based on constructivism learning context theory and data mining algorithm was proposed. First, a fitting parameter analysis model of online teaching quality in higher vocational colleges under this theory is constructed, and then the fitting benefit parameters are extracted by combining the reliability index parameter analysis with the AMOS model based on the index parameters of acting constructively, social interaction and context, and using advanced thinking data analysis methods, such as inference, analysis and identification. Then, according to the characteristic elements of online teaching participants in higher vocational colleges to complete tasks and achieve goals, the fuzzy C-means clustering big data mining algorithm is adopted to carry out quantitative analysis and characteristic elements analysis in the online teaching quality assessment process under the constructivism learning context theory, so as to determine the internal composition of online teaching quality model in higher vocational colleges, that is, online teaching quality elements. These quality factors are then coded in the first and second layers using knowledge transfer methods and rough set concept analysis methods. At the same time, the process characteristic parameters of all factors were analyzed, and the concepts were classified according to the big data mining model. Then, the theoretical parameter analysis model of online teaching quality in higher vocational colleges is constructed to realize the evaluation and quantitative analysis of online teaching quality in higher vocational colleges under the constructivism learning situation theory. Finally, factor analysis and reliability test are achieved by using KMO and Bartlett tests. The results of simulation analysis show that the reliability and accuracy of online teaching quality management evaluation in higher vocational colleges are good, and the credibility level is high under the constructivism learning situation theory.

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Publication Details

Journal
International Journal of High Speed Electronics and Systems
Published
2025-03-20
DOI
https://doi.org/10.1142/s0129156425404486
Primary Topic
AI and HR Technologies
Type
article
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article

Research on Online Teaching Quality Management in Higher Vocational Colleges Based on Data Mining Algorithm

Xueliang Mao, Wenxiao Wang
International Journal of High Speed Electronics and Systems
AI and HR Technologies
article

Research on Online Teaching Quality Management in Higher Vocational Colleges Based on Data Mining Algorithm

Xueliang Mao, Wenxiao Wang
article en

Abstract

In order to evaluate the quality of online teaching in higher vocational colleges quantitatively under the theory of constructivism learning context, a quality management model of online teaching in higher vocational colleges based on constructivism learning context theory and data mining algorithm was proposed. First, a fitting parameter analysis model of online teaching quality in higher vocational colleges under this theory is constructed, and then the fitting benefit parameters are extracted by combining the reliability index parameter analysis with the AMOS model based on the index parameters of acting constructively, social interaction and context, and using advanced thinking data analysis methods, such as inference, analysis and identification. Then, according to the characteristic elements of online teaching participants in higher vocational colleges to complete tasks and achieve goals, the fuzzy C-means clustering big data mining algorithm is adopted to carry out quantitative analysis and characteristic elements analysis in the online teaching quality assessment process under the constructivism learning context theory, so as to determine the internal composition of online teaching quality model in higher vocational colleges, that is, online teaching quality elements. These quality factors are then coded in the first and second layers using knowledge transfer methods and rough set concept analysis methods. At the same time, the process characteristic parameters of all factors were analyzed, and the concepts were classified according to the big data mining model. Then, the theoretical parameter analysis model of online teaching quality in higher vocational colleges is constructed to realize the evaluation and quantitative analysis of online teaching quality in higher vocational colleges under the constructivism learning situation theory. Finally, factor analysis and reliability test are achieved by using KMO and Bartlett tests. The results of simulation analysis show that the reliability and accuracy of online teaching quality management evaluation in higher vocational colleges are good, and the credibility level is high under the constructivism learning situation theory.

International Journal of High Speed Electronics and SystemsVol. 35(03)
Jiaozuo University (CN)
Openalex Percentile: Top 94%
AI and HR Technologies
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