Scientific Trends Towards the Use of Generative Artificial Intelligence Tools in Early Childhood STEM Education: A Bibliometric Analysis

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  • SDG 4 · Nitelikli Eğitim

Özet

This study aims to analyze scientific publications on the use of productive artificial intelligence tools in STEM education during early childhood between 2021 and 2025 using bibliometric methods. In this context, the international literature published during the relevant period was examined to identify scientific production trends, prominent authors, influential studies, institutional and international collaboration networks, and thematic focuses. A total of 1, 224 documents were included in the analysis. During the data analysis process, the Bibliometrix (Biblioshiny) software running on the R program was used; publication trends, keyword frequencies, citation analyses, author and institution collaborations, and scientific mapping techniques were utilized. The analysis findings show that academic interest in productive artificial intelligence tools has increased significantly between 2021 and 2025. The study also systematically identifies key trends, application areas, and research gaps related to the integration of these technologies into educational processes.

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Tam Kayıt
AlanDeğerDil
dc.contributor.authorÇakir, Zehra
dc.contributor.authorUğraş, Mustafa
dc.date.accessioned2026-10-29T19:08:01.942493758Z
dc.date.available2026-10-29T19:08:01.942493758Z
dc.date.issued2026
dc.description.abstractThis study aims to analyze scientific publications on the use of productive artificial intelligence tools in STEM education during early childhood between 2021 and 2025 using bibliometric methods. In this context, the international literature published during the relevant period was examined to identify scientific production trends, prominent authors, influential studies, institutional and international collaboration networks, and thematic focuses. A total of 1, 224 documents were included in the analysis. During the data analysis process, the Bibliometrix (Biblioshiny) software running on the R program was used; publication trends, keyword frequencies, citation analyses, author and institution collaborations, and scientific mapping techniques were utilized. The analysis findings show that academic interest in productive artificial intelligence tools has increased significantly between 2021 and 2025. The study also systematically identifies key trends, application areas, and research gaps related to the integration of these technologies into educational processes.
dc.identifier.doi10.4018/979-8-3373-9074-1.ch002
dc.identifier.endpage67
dc.identifier.isbn979-833739076-5
dc.identifier.isbn979-833739074-1
dc.identifier.scopus2-s2.0-105032593486
dc.identifier.startpage41
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/bayburt/11078
dc.language.isoen
dc.publisherIGI Global
dc.relation.ispartofGenerative AI-Enhanced Science Education From Early Childhood to Higher Education
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subject.otherArtificial intelligence
dc.subject.otherEngineering education
dc.subject.otherInformation analysis
dc.subject.otherPublishing
dc.subject.otherSTEM (science, technology, engineering and mathematics)
dc.subject.otherAnalysis process
dc.subject.otherArtificial intelligence tools
dc.subject.otherBibliometric
dc.subject.otherBibliometrics analysis
dc.subject.otherCollaboration network
dc.subject.otherEarly childhoods
dc.subject.otherInstitutional collaboration
dc.subject.otherInternational collaborations
dc.subject.otherScientific publications
dc.subject.otherSTEM education
dc.subject.otherInternational cooperation
dc.titleScientific Trends Towards the Use of Generative Artificial Intelligence Tools in Early Childhood STEM Education: A Bibliometric Analysis
dc.typeBook Chapter
rdl.citation.openalex0
rdl.citation.scopus0
rdl.oa.statusgreen
rdl.sdgSDG04
rdl.source.indexSCOPUS