The purpose of this review is to explore the impact of AI technology on learning, and through a comprehensive analysis of the relevant literature, summarize and summarize the main research directions in this field. In this study, the relevant literature of "Artificial Intelligence technology and educational learning" in the CNKI database was used as the data source, and bibliometric analysis and content analysis were used to map the knowledge of researchers, institutions and keywords to identify major topics, key researchers and research hotspots. Combined with Excel software statistics, the journal bar chart and the annual document volume line chart. Through the analysis of the atlas one by one, the following conclusions are drawn: the research journals on this topic can be roughly divided into three categories: comprehensive education journals, educational technology journals and higher education journals; since 2016, the annual publication volume has increased rapidly; there are many researchers and institutions, but the cooperation is not close enough; "artificial intelligence", "intelligent education", "man-machine collaboration" are the current research hotspots, "study analysis" and "influencing factors" are the future research trends. The challenge of educational AI in the future lies in how to deeply integrate artificial intelligence technology, not only stay in the field of knowledge and skills, but also pay more attention to the field of "emotion".

Sinuo Sun. Visualized Analysis of the Impact of AI Technology on Learning Based on CiteSpace. The Frontiers of Society, Science and Technology (2024), Vol. 6, Issue 7: 126-135. https://doi.org/10.25236/FSST.2024.060718.

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