Analyzing the Spatio-Temporal Characteristics and Influencing Factors of aI + Education Network Attention in China

被引:0
|
作者
Zhao, Yulin [1 ,2 ,3 ]
Li, Junke [1 ,2 ,4 ]
Liu, Kai [1 ,2 ,3 ]
Wang, Jiang'E [2 ,4 ]
机构
[1] School of Information Engineering, Suqian University, Jiangsu, Suqian,223800, China
[2] School of Computer and Information, Qiannan Normal University for Nationalities, Guizhou, Duyun,558000, China
[3] Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou, Duyun,558000, China
[4] Key Laboratory of Machine Learning and Unstructured Data Processing of Guizhou, Duyun,558000, China
关键词
D O I
暂无
中图分类号
C [社会科学总论];
学科分类号
03 ; 0303 ;
摘要
The Internet is a tool for free expression of will, primarily reflecting the public's willingness to pay attention. Therefore, it is of great significance to use network attention to guide the implementation of Artificial Intelligence (AI) + Education.First, this study takes the AI + Educationnetwork attention of 31 provinces and cities in China as the research object and selects the relevant data from the Baidu Index and the National Bureau of statistics from 2012 to 2020. Then, the study uses the methods of elasticity coefficient, geographical concentration index, and panel model to analyze the spatiotemporal characteristics and influencing factors of AI + Education.Finally, the future development trends in AI + Educationis predicted. The results show that the time characteristics of AI + Educationare apparent, and there are specific interannual differences. The spatial difference between AI + Educationattention is narrowing, and the spatial balance is gradually improving. The Internet, level of economic development, education funding, and vocational education are the main factors influencing the attention of AI + Education.According to the forecast results, the attention to AI + Educationin eastern and central China will generally rise in the next 2 years, while some parts of western China will slightly decline. Therefore, in the future development, national and regional governments should pay attention to the policy guidance of regional differences, strengthen the promotion of new teaching methods, and attach importance to the intelligent construction of vocational education, to promote the integrated development of AI and Education. © 2022 Yulin Zhao et al.
引用
收藏
相关论文
共 50 条
  • [1] Analyzing the Spatio-Temporal Characteristics and Influencing Factors of "AI plus Education" Network Attention in China
    Zhao, Yulin
    Li, Junke
    Liu, Kai
    Wang, Jiang'e
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2022, 2022
  • [2] Spatio-temporal characteristics of the novel coronavirus attention network and its influencing factors in China
    Guo, Xiaojia
    Zhang, Jing
    Wu, Xueling
    PLOS ONE, 2021, 16 (09):
  • [3] Investigating spatio-temporal characteristics and influencing factors for green energy consumption in China
    Ma, Xiaowei
    Weng, Shimei
    Zhao, Jun
    Liu, Huiling
    Huang, Hongyun
    GEOSCIENCE FRONTIERS, 2024, 15 (03)
  • [4] Spatio-temporal distribution characteristics and influencing factors of COVID-19 in China
    Youliang Chen
    Qun Li
    Hamed Karimian
    Xunjun Chen
    Xiaoming Li
    Scientific Reports, 11
  • [5] Spatio-temporal distribution characteristics and influencing factors of COVID-19 in China
    Chen, Youliang
    Li, Qun
    Karimian, Hamed
    Chen, Xunjun
    Li, Xiaoming
    SCIENTIFIC REPORTS, 2021, 11 (01)
  • [6] Spatio-temporal differentiation characteristics and influencing factors of hand, foot, and mouth disease in China
    Song Y.
    Liu Y.
    Zhang Y.
    Wang S.
    Dili Xuebao/Acta Geographica Sinica, 2022, 77 (03): : 574 - 588
  • [7] Spatio-temporal characteristics and influencing factors of state owned construction land supply in China
    Zhou C.
    Jin W.
    Zhang G.
    Li M.
    Wang S.
    Dili Xuebao/Acta Geographica Sinica, 2019, 74 (01): : 16 - 31
  • [8] Spatio-temporal evolution characteristics and influencing factors of carbon emission reduction potential in China
    Li, Zhangwen
    Zhang, Caijiang
    Zhou, Yu
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2021, 28 (42) : 59925 - 59944
  • [9] Spatio-temporal distribution characteristics and influencing factors of drought in the Liaohe river basin, China
    Gong, Yuanshan
    FRONTIERS IN ENVIRONMENTAL SCIENCE, 2022, 10
  • [10] Spatio-temporal evolution characteristics and influencing factors of carbon emission reduction potential in China
    Zhangwen Li
    Caijiang Zhang
    Yu Zhou
    Environmental Science and Pollution Research, 2021, 28 : 59925 - 59944