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Knowledge Mapping and Evolutionary Analysis of Artificial Intelligence Research in Higher Education: A Systematic Approach Using CiteSpace
Abstract
The rapid evolution of Artificial Intelligence (AI) within higher education has prompted significant research into its integration and impact. This paper explores the development and current trends in AI research in higher education, utilizing CiteSpace to construct a comprehensive knowledge map. By analyzing multidimensional data such as keywords, authors, institutions, and journals, the study identifies key research hotspots and emerging trends. Findings indicate a rising publication trajectory, with Price's Law suggesting the lack of a consistent core group of influential contributors. Topics such as AI systems, adaptive learning models, big data integration, and intelligent environments are currently prevalent, reflecting shifts in research priorities. The paper offers insights into the systemic growth and structural evolution of AI in education, providing a foundation for advancing innovative educational ecosystems.
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