Visualization Analysis of Chinese Learning Space Evaluation Research Base on Citespace
- DOI
- 10.2991/978-94-6463-040-4_53How to use a DOI?
- Keywords
- learning space; co-word analysis; CiteSpace; visualization
- Abstract
At present, domestic research on learning space is in a period of vigorous development. This research uses the visualization software CiteSpace and the Python programming tool are used to collect the literature data on the topic of learning space through CNKI database. Based on these, the research conducts data analysis on the screened 1351 literature data in the ten years from 2011 to 2021, digging out the information of authors, research institutions, research keywords and highlight words in the field of learning space research. As the result, it is found that current trending keywords of learning space research include smart education, classroom, libraries, learning space, deep learning, machine learning, Artificial intelligence, flipped classroom, etc. Main research topic include future classrooms, libraries, model of instruction, artificial intelligence, deep learning, and educational reform.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Yilong Xu AU - Hongbo Yu AU - Fujing Zhao PY - 2022 DA - 2022/12/27 TI - Visualization Analysis of Chinese Learning Space Evaluation Research Base on Citespace BT - Proceedings of the 2022 3rd International Conference on Artificial Intelligence and Education (IC-ICAIE 2022) PB - Atlantis Press SP - 349 EP - 355 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-040-4_53 DO - 10.2991/978-94-6463-040-4_53 ID - Xu2022 ER -