In the current digital era, the field of education is undergoing unprecedented changes. Artificial Intelligence (AI), as a revolutionary technology, has demonstrated its unique advantages in various fields such as healthcare, finance, and manufacturing. To explore the application of AI in education and teaching, as well as its evolving trends, we analyzed 1364 CSSCI papers from the China National Knowledge Infrastructure (CNKI) database from 2014 to 2023. Employing bibliometrics and knowledge mapping methods, we established a detailed view of the development trends and research hotspots in AI-driven education and teaching research. The Citespace software was employed for visual analysis of critical data such as authors, institutions, and keywords, including the collaboration networks of authors and institutions, keyword frequency and centrality, and the evolution of research topics. Our analysis revealed that AI-driven education and teaching research from 2014 to 2023 can be divided into three developmental stages: nascent (2014–2016), rapid development (2017–2019), and stable development (2020–2023). What's more, we identified close cooperation among core institutions and authors, determined multiple hotspot topics in AI within education and teaching, and revealed the developmental trajectory of these topics.

Xin Huang. Reviewing Researches on Artificial Intelligence—Driven Education and Teaching from 2014 to 2023: A CiteSpace-based Visual Analysis. Frontiers in Educational Research (2024) Vol. 7, Issue 1: 6-16. https://doi.org/10.25236/FER.2024.070102.

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