Proceedings of the 6th International Conference on Humanities and Social Science Research (ICHSSR 2020)

Research Hotshots and Development Trend of Intelligent Education in China—Analysis Method Based on Multidimensional Scaling

Authors
Quan Jiangtao, Cui Can
Corresponding Author
Cui Can
Available Online 1 May 2020.
DOI
https://doi.org/10.2991/assehr.k.200428.076How to use a DOI?
Keywords
intelligent education, multidimensional scaling, research hotshot, development trend
Abstract
A deep understanding of the research hotshot and development trend in the field of intelligent education in China will help researchers to grasp the latest development of intelligent education more accurately and promote the rapid development of intelligent education in China. This paper adopts the method of multidimensional scale analysis, using BICOMB 2.0, SPSS 23.0 and other software, taking CSSCI as the source of literature data, analyzes the research hotshot and development trend of intelligent education in China. The research shows that the current research focus of intelligent education mainly includes the basic theory research of intelligent education, the application research of artificial intelligence technology in education, the research of intelligent education teaching mode and so on. The future research of intelligent education should pay attention to the fields of higher education and maker education, strengthen the construction of educational practice and teaching mode, and promote educational reform and personnel training.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Cite this article

TY  - CONF
AU  - Quan Jiangtao
AU  - Cui Can
PY  - 2020
DA  - 2020/05/01
TI  - Research Hotshots and Development Trend of Intelligent Education in China—Analysis Method Based on Multidimensional Scaling
BT  - Proceedings of the 6th International Conference on Humanities and Social Science Research (ICHSSR 2020)
PB  - Atlantis Press
SP  - 350
EP  - 353
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.200428.076
DO  - https://doi.org/10.2991/assehr.k.200428.076
ID  - Jiangtao2020
ER  -