KNOWLEDGE GRAPH ANALYSIS OF PRESCHOOL RESEARCH IN THE AGE OF ARTIFICIAL INTELLIGENCE: CITESPACE DISCIPLINARY STRUCTURE VISUALIZATION
DOI:
https://doi.org/10.34256/Keywords:
artificial intelligence, preschool education, disciplinary structureAbstract
This study employs CiteSpace-based knowledge graph analysis to investigate the structural evolution, thematic trends, and global collaboration patterns in preschool education research under the influence of artificial intelligence (AI) from 2014 to 2025. By analyzing literature from the Web of Science Core Collection, the study identifies a significant shift in research focus—from early themes like “intervention” and “school readiness” to recent concerns such as “teacher burnout,” “health,” and the sociocultural dimensions of education. The application of AI technologies in preschool settings spans personalized learning, educational robotics, intelligent play tools, and developmental assessments, showcasing strong interdisciplinarity that integrates machine learning, affective computing, and developmental psychology. The analysis of institutional impact reveals a hierarchical distribution, where small institutions can exert outsized influence, while journal citation data reflect the growing prominence of interdisciplinary and technical journals over traditional education outlets. The international collaboration network presents a core-periphery structure dominated by Western countries, with limited South-South cooperation. Keyword and clustering analyses further indicate a paradigm shift from a technocratic approach to a more child-centered, relational, and culturally sensitive research orientation. However, the field still faces challenges such as fragmented theoretical frameworks, underutilization of qualitative methodologies, and geopolitical imbalances in knowledge production. The study concludes that future research in preschool education should focus on building inclusive theoretical systems, promoting interdisciplinary collaboration, and fostering equitable global discourse. This work offers empirical insights and strategic guidance for academics, policymakers, and practitioners committed to advancing high-quality, context-sensitive early childhood education in the AI era.
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