Open Access
ARTICLE
Research on Teaching Method of Children’s Image Cognition Based on AR Technology
Jie Gui1,2,*, Joohyun Suh3
1 Jiangsu Vocational College of Electronics and Information, Huai’an, 223003, China
2 Completion of Doctoral Course, Sangmyung University, Seoul, 03016, Korea
3 Department of Family Welfare, Sangmyung University, Seoul, 03016, Korea
* Corresponding Author: Jie Gui. Email:
Journal on Internet of Things 2022, 4(4), 197-213. https://doi.org/10.32604/jiot.2022.037182
Received 01 October 2022; Accepted 04 November 2022; Issue published 18 July 2023
Abstract
In this paper, the research on the teaching method of children’s image cognition based on AR technology is carried out. By analyzing the principle of AR technology to recognize images, we understand that AR technology can promote children’s image cognition, and this teaching method is in line with the Tower of Experience theory. It further analyzes the current situation of children’s image cognition teaching with simple teaching methods, backward AR teaching tools, and poor perception of teaching objects. Teachers’ traditional image teaching methods cannot effectively and efficiently improve children’s image cognition. Therefore, based on AR technology, two commonly used image cognition teaching methods are proposed: AR interactive picture book education and AR interactive game education. Both of these educational methods can improve children’s ability to recognize images.
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APA Style
Gui, J., Suh, J. (2022). Research on teaching method of children’s image cognition based on AR technology. Journal on Internet of Things, 4(4), 197-213. https://doi.org/10.32604/jiot.2022.037182
Vancouver Style
Gui J, Suh J. Research on teaching method of children’s image cognition based on AR technology. J Internet Things . 2022;4(4):197-213 https://doi.org/10.32604/jiot.2022.037182
IEEE Style
J. Gui and J. Suh, "Research on Teaching Method of Children’s Image Cognition Based on AR Technology," J. Internet Things , vol. 4, no. 4, pp. 197-213. 2022. https://doi.org/10.32604/jiot.2022.037182