Date of Award

2026

Document Type

Dissertation

Degree Name

Doctor of Education (EdD)

Department

Education

First Advisor

Heting Chu, Ph.D.

Second Advisor

Joy-Anne D’Anca, Ed.D.

Third Advisor

Paula Lester, Ph.D.

Abstract

Research on artificial intelligence (AI) in K–12 education has expanded rapidly over the past two decades, producing a growing and sometimes fragmented body of scholarly literature. As new AI applications, including machine learning systems, intelligent tutoring systems, and generative AI tools, continue to emerge, understanding how this research has evolved over time is increasingly important for educators, policymakers, and researchers. This study conducted a bibliometric analysis of scholarly publications on AI in K–12 education to address the following three research questions. How has research on artificial intelligence in K–12 education evolved over time? Who are the significant contributors to AI research in K–12 education? What are the key themes and trends in AI research within the K–12 context? Data for the present research were gathered from Scopus and Web of Science, the two largest citation databases. The present author then analyzed the data bibliometrically. This study indicates that the field is international in scope but concentrated among a relatively small number of highly active contributors, with the United States and China emerging as the leading countries. A limited group of key authors, institutions, and publication sources has played a central role in shaping the field’s development. Keyword co-occurrence analysis identified major areas of focus centered on technical approaches, AI literacy and educational implementation, human and social concerns, and generative AI. Overall, the findings suggest that AI research in K–12 education has developed into a rapidly expanding and increasingly interconnected field shaped by both technological innovation and educational concerns.

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