Decade-Spanning Bibliometric Visual Analytics for AI Literacy

With the rapid development and widespread application of artificial intelligence (AI), AI literacy has rapidly emerged as a concept to measure people's ability to master and apply AI in the new era. This study is based on bibliometric software and conducts a comprehensive bibliometric analysis of AI literacy research over the past decade, exploring the evolving trends in this field. The analysis results show that AI literacy research is growing exponentially, with the United States, China, Germany, and the United Kingdom being the major contributing countries in this field. The research topics cover multiple dimensions such as artificial intelligence education, academic integrity, bibliometrics, technology acceptance models, professional development, and AI-assisted writing. This study provides important insights for future academic exploration and educational policy formulation in the field of AI literacy.

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Published
2025-02-21
DOI
https://doi.org/10.1145/3732299.3732340
Primary Topic
Online Learning and Analytics
Type
article
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article

Decade-Spanning Bibliometric Visual Analytics for AI Literacy

Liandi Ding, Jia Liu, Qiqi Zhou
Online Learning and Analytics
article

Decade-Spanning Bibliometric Visual Analytics for AI Literacy

Liandi Ding, Jia Liu, Qiqi Zhou
article en

Abstract

With the rapid development and widespread application of artificial intelligence (AI), AI literacy has rapidly emerged as a concept to measure people's ability to master and apply AI in the new era. This study is based on bibliometric software and conducts a comprehensive bibliometric analysis of AI literacy research over the past decade, exploring the evolving trends in this field. The analysis results show that AI literacy research is growing exponentially, with the United States, China, Germany, and the United Kingdom being the major contributing countries in this field. The research topics cover multiple dimensions such as artificial intelligence education, academic integrity, bibliometrics, technology acceptance models, professional development, and AI-assisted writing. This study provides important insights for future academic exploration and educational policy formulation in the field of AI literacy.

Jingchu University of Technology (CN), Wuhan Branch of the National Science Library (CN)
Quality Education
Openalex Percentile: Top 85%
Online Learning and Analytics
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Decade-Spanning Bibliometric Visual Analytics for AI Literacy — Liandi Ding, Jia Liu, et al. · (2025) | TGRS Research Map | TGRS