Artificial intelligence is driving human society towards intelligent development, including in the field of education. In order to understand people's attitudes towards the impact of AI on education and the level of impact of AI on education, this study uses R language and Rstudio environment as text mining tools and conducts research in two aspects: First, we used a YouTube API to retrieve 1,774 pieces of text data from 10 Ted videos talking about ai on education. We then cleaned the data using stop words, performed word segmentation and word frequency analysis (DFM), and used sentiment analysis to explore whether people’s attitudes towards the content were positive or negative. Secondly, using "AI influence education" as the keyword, we crawled the ERIC (Institute of Education Sciences) website and collected a total of 86 research articles. We cleaned the data by using stop words, performed word segmentation and word frequency (DFM), and then used topic modeling methods to discover the five major aspects of AI's impact on education. This study uses text mining technology, and the results show that people's attitude intentions are positive (3888 points) rather than negative (1494 points), indicating that the public is mostly optimistic about the impact of AI. At the same time, in the current research articles, five major aspects of AI's impact on education were found, including technology, health, policy, career, and teaching, indicating that AI's impact is broad and must be discussed from a more comprehensive perspective.

Authors:
Chia Wei Wang, National Taiwan Normal University, Taiwan
Dani Madrid-Morales, University of Sheffield, United Kingdom
Hsiu-Te Sung, National Taiwan Normal University, Taiwan

About the Presenter(s)
Mr. Wang Jiawei is currently a higher vocational teacher and a doctoral student in the Department of Industrial Education at National Taiwan Normal University. His research focuses on technical and vocational education and digital learning.

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