Artificial intelligence in education research during 2013–2023: A review based on bibliometric analysis

Research on Artificial Intelligence in Education (AIED) has rapidly progressed in recent years, and understanding the research trends and development is essential for technological innovations and implementations in education. Using a bibliometric analysis of 6843 publications from Web of Science an...

Full description

Saved in:
Bibliographic Details
Published inEducation and information technologies Vol. 29; no. 13; pp. 16387 - 16409
Main Authors Guo, Shuchen, Zheng, Yuanyuan, Zhai, Xiaoming
Format Journal Article
LanguageEnglish
Published New York Springer US 01.09.2024
Springer
Springer Nature B.V
Subjects
Online AccessGet full text
ISSN1360-2357
1573-7608
DOI10.1007/s10639-024-12491-8

Cover

More Information
Summary:Research on Artificial Intelligence in Education (AIED) has rapidly progressed in recent years, and understanding the research trends and development is essential for technological innovations and implementations in education. Using a bibliometric analysis of 6843 publications from Web of Science and Scopus, we found that China, US, India, Spain, and Germany led the research profuctivity. AIED research is concerned more with higher education compared to K-12 education. Fifteen research trends emerged from the analysis, such as Educational Robots and Large Data Mining. Research has primarily leveraged technologies of machine learning, decision trees, deep learning, speech recognition, and computer vision in AIED. The major implementations of AI include educational robots, automated grading, recommender systems, learning analytics, and intelligent tutoring systems. Among the implementations, a majority of AIED research was conducted in seven major subject domains, chief among them being science, technology, engineering and mathematics (STEM) and language disciplines, with a focus on computer science and English education.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1360-2357
1573-7608
DOI:10.1007/s10639-024-12491-8