Construction of evaluation standard system of university practice teaching under the background of big data

The purpose of this study is to explore the method and application of constructing the evaluation standard system of university practice teaching under the background of big data. Based on teaching evaluation theory, combined with big data technology, the paper constructs a practical teaching evaluation model through questionnaire survey and data collection. In the data analysis, the multiple linear regression model is used to predict the practical teaching effect, and the detailed empirical analysis is carried out. It is found that the model can predict the practical teaching effect and explain the variability of the actual data well. However, the study also revealed the existence of problems such as data quality, sample bias, and model limitations, which need further research and verification. In general, this study provides a preliminary framework for the evaluation of practical teaching in colleges and universities, and is expected to help colleges and universities improve the quality and effect of practical teaching.

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Publication Details

Journal
Journal of Computational Methods in Sciences and Engineering
Published
2024-11-01
DOI
https://doi.org/10.1177/14727978241296990
Citations
2
Primary Topic
AI and Multimedia in Education
Type
article
Field-Weighted Citation Impact
0.69
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article

Construction of evaluation standard system of university practice teaching under the background of big data

Xiaolin Sun, Fangqun Gan, Ke Wu, Ruimin Zhang et al.
2 citations
Journal of Computational Methods in Sciences and Engineering
AI and Multimedia in Education
0.69
article

Construction of evaluation standard system of university practice teaching under the background of big data

Xiaolin Sun, Fangqun Gan, Ke Wu, Ruimin Zhang, Wu Ji
article en
2 citations

Abstract

The purpose of this study is to explore the method and application of constructing the evaluation standard system of university practice teaching under the background of big data. Based on teaching evaluation theory, combined with big data technology, the paper constructs a practical teaching evaluation model through questionnaire survey and data collection. In the data analysis, the multiple linear regression model is used to predict the practical teaching effect, and the detailed empirical analysis is carried out. It is found that the model can predict the practical teaching effect and explain the variability of the actual data well. However, the study also revealed the existence of problems such as data quality, sample bias, and model limitations, which need further research and verification. In general, this study provides a preliminary framework for the evaluation of practical teaching in colleges and universities, and is expected to help colleges and universities improve the quality and effect of practical teaching.

Journal of Computational Methods in Sciences and EngineeringVol. 24(6)
Changzhou Institute of Technology (CN), Yunnan Open University (CN), Hong Kong Metropolitan University (HK)
Openalex Percentile: Top 22%
AI and Multimedia in Education
0.69
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