The sustainable development of mathematics subject: An empirical analysis based on the academic attention and literature research

The exploration of the correlation between subject network attention and literature research in China can aid in comprehending the development trend of Chinese scientific and technological journals. Currently, many scholars have done a lot of research based on the network media index, but the relati...

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Published inHeliyon Vol. 9; no. 8; p. e18750
Main Authors Zhao, Yulin, Li, Junke, Liu, Kai
Format Journal Article
LanguageEnglish
Published England Elsevier 01.08.2023
Subjects
Online AccessGet full text
ISSN2405-8440
2405-8440
DOI10.1016/j.heliyon.2023.e18750

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Abstract The exploration of the correlation between subject network attention and literature research in China can aid in comprehending the development trend of Chinese scientific and technological journals. Currently, many scholars have done a lot of research based on the network media index, but the relationship between the discipline attention represented by it and literature research has not been fully verified. This paper used CNKI and Baidu Index as data sources to establish a RAPF experimental framework based on relationship analysis and prediction, and selected high school mathematics subjects in China for effective demonstration. First, RAPF extracted core keywords using text tools and word frequency statistics. Second, it constructed a relationship model between subject attention and literature research based on Spearman and LOOCV. Finally, it made predictions through time series and regression analysis. The results showed a correlation between subject attention and literature research, and the model fit was 0.774, with a relative error of less than 2%. Short-term predictions found that some keywords received less online attention, and 2022-2024 may be the crucial development period for mathematical education research, with an annual literature research volume of approximately 380 articles. This paper summarized the mathematical subject themes centered on content, culture, literacy, and integration, and also provided a reference for the development of the subject through experimental prediction. In the next two years, China's mathematics literature research still needs to delve deeper, broaden its breadth, enhance its height, and ensure a steady improvement in the quality and quantity of literature research.
AbstractList The exploration of the correlation between subject network attention and literature research in China can aid in comprehending the development trend of Chinese scientific and technological journals. Currently, many scholars have done a lot of research based on the network media index, but the relationship between the discipline attention represented by it and literature research has not been fully verified. This paper used CNKI and Baidu Index as data sources to establish a RAPF experimental framework based on relationship analysis and prediction, and selected high school mathematics subjects in China for effective demonstration. First, RAPF extracted core keywords using text tools and word frequency statistics. Second, it constructed a relationship model between subject attention and literature research based on Spearman and LOOCV. Finally, it made predictions through time series and regression analysis. The results showed a correlation between subject attention and literature research, and the model fit R² was 0.774, with a relative error of less than 2%. Short-term predictions found that some keywords received less online attention, and 2022–2024 may be the crucial development period for mathematical education research, with an annual literature research volume of approximately 380 articles. This paper summarized the mathematical subject themes centered on content, culture, literacy, and integration, and also provided a reference for the development of the subject through experimental prediction. In the next two years, China's mathematics literature research still needs to delve deeper, broaden its breadth, enhance its height, and ensure a steady improvement in the quality and quantity of literature research.
The exploration of the correlation between subject network attention and literature research in China can aid in comprehending the development trend of Chinese scientific and technological journals. Currently, many scholars have done a lot of research based on the network media index, but the relationship between the discipline attention represented by it and literature research has not been fully verified. This paper used CNKI and Baidu Index as data sources to establish a RAPF experimental framework based on relationship analysis and prediction, and selected high school mathematics subjects in China for effective demonstration. First, RAPF extracted core keywords using text tools and word frequency statistics. Second, it constructed a relationship model between subject attention and literature research based on Spearman and LOOCV. Finally, it made predictions through time series and regression analysis. The results showed a correlation between subject attention and literature research, and the model fit R2 was 0.774, with a relative error of less than 2%. Short-term predictions found that some keywords received less online attention, and 2022-2024 may be the crucial development period for mathematical education research, with an annual literature research volume of approximately 380 articles. This paper summarized the mathematical subject themes centered on content, culture, literacy, and integration, and also provided a reference for the development of the subject through experimental prediction. In the next two years, China's mathematics literature research still needs to delve deeper, broaden its breadth, enhance its height, and ensure a steady improvement in the quality and quantity of literature research.The exploration of the correlation between subject network attention and literature research in China can aid in comprehending the development trend of Chinese scientific and technological journals. Currently, many scholars have done a lot of research based on the network media index, but the relationship between the discipline attention represented by it and literature research has not been fully verified. This paper used CNKI and Baidu Index as data sources to establish a RAPF experimental framework based on relationship analysis and prediction, and selected high school mathematics subjects in China for effective demonstration. First, RAPF extracted core keywords using text tools and word frequency statistics. Second, it constructed a relationship model between subject attention and literature research based on Spearman and LOOCV. Finally, it made predictions through time series and regression analysis. The results showed a correlation between subject attention and literature research, and the model fit R2 was 0.774, with a relative error of less than 2%. Short-term predictions found that some keywords received less online attention, and 2022-2024 may be the crucial development period for mathematical education research, with an annual literature research volume of approximately 380 articles. This paper summarized the mathematical subject themes centered on content, culture, literacy, and integration, and also provided a reference for the development of the subject through experimental prediction. In the next two years, China's mathematics literature research still needs to delve deeper, broaden its breadth, enhance its height, and ensure a steady improvement in the quality and quantity of literature research.
The exploration of the correlation between subject network attention and literature research in China can aid in comprehending the development trend of Chinese scientific and technological journals. Currently, many scholars have done a lot of research based on the network media index, but the relationship between the discipline attention represented by it and literature research has not been fully verified. This paper used CNKI and Baidu Index as data sources to establish a RAPF experimental framework based on relationship analysis and prediction, and selected high school mathematics subjects in China for effective demonstration. First, RAPF extracted core keywords using text tools and word frequency statistics. Second, it constructed a relationship model between subject attention and literature research based on Spearman and LOOCV. Finally, it made predictions through time series and regression analysis. The results showed a correlation between subject attention and literature research, and the model fit R2 was 0.774, with a relative error of less than 2%. Short-term predictions found that some keywords received less online attention, and 2022–2024 may be the crucial development period for mathematical education research, with an annual literature research volume of approximately 380 articles. This paper summarized the mathematical subject themes centered on content, culture, literacy, and integration, and also provided a reference for the development of the subject through experimental prediction. In the next two years, China's mathematics literature research still needs to delve deeper, broaden its breadth, enhance its height, and ensure a steady improvement in the quality and quantity of literature research.
The exploration of the correlation between subject network attention and literature research in China can aid in comprehending the development trend of Chinese scientific and technological journals. Currently, many scholars have done a lot of research based on the network media index, but the relationship between the discipline attention represented by it and literature research has not been fully verified. This paper used CNKI and Baidu Index as data sources to establish a RAPF experimental framework based on relationship analysis and prediction, and selected high school mathematics subjects in China for effective demonstration. First, RAPF extracted core keywords using text tools and word frequency statistics. Second, it constructed a relationship model between subject attention and literature research based on Spearman and LOOCV. Finally, it made predictions through time series and regression analysis. The results showed a correlation between subject attention and literature research, and the model fit was 0.774, with a relative error of less than 2%. Short-term predictions found that some keywords received less online attention, and 2022-2024 may be the crucial development period for mathematical education research, with an annual literature research volume of approximately 380 articles. This paper summarized the mathematical subject themes centered on content, culture, literacy, and integration, and also provided a reference for the development of the subject through experimental prediction. In the next two years, China's mathematics literature research still needs to delve deeper, broaden its breadth, enhance its height, and ensure a steady improvement in the quality and quantity of literature research.
ArticleNumber e18750
Author Liu, Kai
Zhao, Yulin
Li, Junke
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educational research
empirical research
High school mathematics
literacy
Literature research
mathematics
prediction
regression analysis
Relationship modeling
Short-term forecasting
Subject attention
sustainable development
time series analysis
Title The sustainable development of mathematics subject: An empirical analysis based on the academic attention and literature research
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