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...
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Published in | Education and information technologies Vol. 29; no. 13; pp. 16387 - 16409 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
New York
Springer US
01.09.2024
Springer Springer Nature B.V |
Subjects | |
Online Access | Get full text |
ISSN | 1360-2357 1573-7608 |
DOI | 10.1007/s10639-024-12491-8 |
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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. |
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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 |