A Bibliometric analysis of Artificial Intelligence in Education based on CiteSpace: Trends and Research Status
Year: 2025
Type: conference-paper
Abstract: Artificial intelligence is reshaping educational theories and models in an irreversible manner and has transformed the human-human teaching into human-machine teaching. Artificial Intelligence in Education (AIED) has intrigued significant scholarly interest. However, with the increasing number of papers published every year, the research frontier changed rapidly and little research focusing on the current research status and directions which helps researchers understand the latest outcomes and main barriers. Hence, this study provides an overall insight into this field based on bibliometric analysis. Around 898 publications were selected from Web Of Science, with the terms of generative artificial intelligence, educational technology and so on, from 2000 to 2025, as the database. This article presents several visual charts generated by CiteSpace, including the trend of publication volume, the collaboration network of countries and institutions and the core authors. Major keywords also are demonstrated by the co-occurrence map and their evolutionary process is shown in chronological order. A shift of research direction from machine learning to the quality of AI teaching in tertiary institutions, reflected by the list of Top 10 keywords with the strongest citation burst.
Authors: Yitong Chen, Ziyi Qiu, Tongyu Liu, Peng Pan
Institution: Tianjin University of Technology
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: gold
OpenAlex ID: W4413987000