Exploring the transformative power of GenAI in education: an exploratory journey from social studies classes

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Özet

The potential of GenAI in educational settings has attracted considerable attention, yet practical explorations of its use in K-12 classrooms are still scarce. This research aims to explore the role of GenAI models in social studies, focusing on their influence on learning-teaching processes and understanding of AI. While exploring the influence of GenAI on pedagogical aspects from the perspective of the teacher and students, this qualitative study also embraces AI as a cross-curricular theme and seeks to understand how GenAI-supported teaching activities shape students’ AI understanding. The study group of this research, conducted according to the basic qualitative research design, consisted of 21 middle school students studying in one class and a social studies teacher who implemented the practices. The primary data collection tool for the research was semi-structured interview forms. In the relevant research, a teaching framework supported by GenAI, combining “Teaching with AI” and “Teaching about AI” was developed. During the four-week process, the practitioner teacher covered the curricular outcomes using lesson plans designed in alignment with this framework. In the semi-structured interviews, students stated that engaging in activities supported by GenAI not only made the learning process more effective and interesting but also enhanced their understanding regarding AI. The teacher highlighted that GenAI models encouraged constructivist learning environments, ensured the active involvement of all students, including those in inclusive education, and contributed to AI learning through their engaging structure. Additionally, the teacher highlighted technology’s drawbacks, including encouraging dependence on convenience and potentially providing inaccurate information. The relevant findings of the study, serving as first observations, are expected to provide valuable insights for future research. At this point, it is recommended that further studies be conducted to explore the transformative potential of GenAI in education, especially by employing experimental designs. An additional suggestion, on the other hand, is to disseminate AI throughout the entire curriculum of all subjects within a specific educational level as a cross-curricular theme, as opposed to limiting its teaching to merely a singular, isolated subject area.

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https://rdlopen.rawdatalibrary.net/r/bayburt/11414Resmi atıflarda kullanılan kalıcı adres
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https://doi.org/10.1007/s10639-025-13814-zYayıncı resmi DOI adresi
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dc.contributor.authorYetişensoy, Okan
dc.date.accessioned2026-10-29T19:08:22.206342959Z
dc.date.available2026-10-29T19:08:22.206342959Z
dc.date.issued2025
dc.description.abstractThe potential of GenAI in educational settings has attracted considerable attention, yet practical explorations of its use in K-12 classrooms are still scarce. This research aims to explore the role of GenAI models in social studies, focusing on their influence on learning-teaching processes and understanding of AI. While exploring the influence of GenAI on pedagogical aspects from the perspective of the teacher and students, this qualitative study also embraces AI as a cross-curricular theme and seeks to understand how GenAI-supported teaching activities shape students’ AI understanding. The study group of this research, conducted according to the basic qualitative research design, consisted of 21 middle school students studying in one class and a social studies teacher who implemented the practices. The primary data collection tool for the research was semi-structured interview forms. In the relevant research, a teaching framework supported by GenAI, combining “Teaching with AI” and “Teaching about AI” was developed. During the four-week process, the practitioner teacher covered the curricular outcomes using lesson plans designed in alignment with this framework. In the semi-structured interviews, students stated that engaging in activities supported by GenAI not only made the learning process more effective and interesting but also enhanced their understanding regarding AI. The teacher highlighted that GenAI models encouraged constructivist learning environments, ensured the active involvement of all students, including those in inclusive education, and contributed to AI learning through their engaging structure. Additionally, the teacher highlighted technology’s drawbacks, including encouraging dependence on convenience and potentially providing inaccurate information. The relevant findings of the study, serving as first observations, are expected to provide valuable insights for future research. At this point, it is recommended that further studies be conducted to explore the transformative potential of GenAI in education, especially by employing experimental designs. An additional suggestion, on the other hand, is to disseminate AI throughout the entire curriculum of all subjects within a specific educational level as a cross-curricular theme, as opposed to limiting its teaching to merely a singular, isolated subject area.
dc.identifier.doi10.1007/s10639-025-13814-z
dc.identifier.eissn1573-7608
dc.identifier.endpage25626
dc.identifier.issn1360-2357
dc.identifier.issue17
dc.identifier.scopus2-s2.0-105019809513
dc.identifier.startpage25577
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/bayburt/11414
dc.identifier.volume30
dc.identifier.wosWOS:001599489400001
dc.language.isoen
dc.publisherSpringer
dc.relation.ispartofEducation and Information Technologies
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectArtificial intelligence
dc.subjectCross-curricular integration
dc.subjectGenAI models
dc.subjectQualitative research
dc.subjectSocial studies education
dc.subject.classificationEducation & Educational Research
dc.subject.otherARTIFICIAL-INTELLIGENCE
dc.subject.otherAI
dc.subject.otherCHALLENGES
dc.subject.otherCURRICULUM
dc.titleExploring the transformative power of GenAI in education: an exploratory journey from social studies classes
dc.typeArticle
rdl.citation.openalex2
rdl.citation.scopus2
rdl.citation.wos1
rdl.oa.statusclosed
rdl.scopus.quartileQ1
rdl.sdgSDG04
rdl.source.indexSCOPUS
rdl.source.indexWOS
rdl.wos.indexSocial Science Citation Index (SSCI)