Artificial Intelligence in Education: a Text Mining-Based Review of the Past 56 Years

dc.authoridCantekin, Omer Faruk/0000-0001-5096-3233
dc.authoridEkin, Cansu Cigdem/0000-0003-4838-9708
dc.authorscopusid59549541700
dc.authorscopusid57428018900
dc.authorscopusid55488995000
dc.authorscopusid57221951670
dc.contributor.authorEkin, C.C.
dc.contributor.authorCantekin, Ö.F.
dc.contributor.authorPolat, E.
dc.contributor.authorHopcan, S.
dc.date.accessioned2025-02-05T18:35:32Z
dc.date.available2025-02-05T18:35:32Z
dc.date.issued2025
dc.departmentAtılım Universityen_US
dc.department-tempEkin C.C., Computer Engineering, Atilim University, Ankara, Incek, 06830, Türkiye; Cantekin Ö.F., Department of Social Work, Gazi University, Çankaya/Ankara, Türkiye; Polat E., Department of Computer Education & Instructional Technology Hasan Ali Yucel Education Faculty, Istanbul University- Cerrahpasa, Istanbul, 34452, Türkiye; Hopcan S., Department of Computer Education & Instructional Technology Hasan Ali Yucel Education Faculty, Istanbul University- Cerrahpasa, Istanbul, 34452, Türkiyeen_US
dc.description.abstractArtificial Intelligence in Education (AIED) is a broad and multifarious area of study that spans across various academic fields. Due to the high numbers of studies in this field, it seems too challenging to analyze all of them in depth in a single study. Additionally, there is a lack of research that provides a comprehensive overview of the main trends and topics in AIED. This study, hence, aims to fill this gap by using text mining techniques to examine how artificial intelligence (AI)-related research in education has evolved over time. To this end, a total of 11,027 articles indexed by the Scopus database in the field of education between 1967 and 2023 were examined. Based on the findings, there has been a significant increase in AIED since 2014, covering 73% of the publications. Over the past three decades, AIED research has increasingly concentrated on engineering student populations and conference proceedings. Notably, AI solutions are extensively employed in education, with a strong focus on personalization, assessment, and evaluation. They also play a prominent role in research review processes, such as text mining and topic modeling for summarizing research findings. The findings contribute to the field, enhancing our understanding of the patterns of AI’s integration into education and offering guidance for prospective research endeavors. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.en_US
dc.description.woscitationindexSocial Science Citation Index
dc.identifier.citationcount0
dc.identifier.doi10.1007/s10639-024-13225-6
dc.identifier.issn1360-2357
dc.identifier.scopus2-s2.0-85217379852
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1007/s10639-024-13225-6
dc.identifier.wosWOS:001391747400001
dc.identifier.wosqualityQ1
dc.institutionauthorEkin, Cansu Cigdem
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofEducation and Information Technologiesen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAieden_US
dc.subjectArtificial Intelligence In Education (Aied)en_US
dc.subjectLatent Dirichlet Allocationen_US
dc.subjectText Miningen_US
dc.subjectTopic Modelingen_US
dc.titleArtificial Intelligence in Education: a Text Mining-Based Review of the Past 56 Yearsen_US
dc.typeArticleen_US
dc.wos.citedbyCount0
dspace.entity.typePublication

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